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Events for December
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MS CSCI/DSCI Drop-in Academic Advising
Wed, Dec 01, 2021 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
Virtual Academic Advising Drop-in Hours for continuing MS students in CS or Data Science Programs will be available for the month of December. If you have a quick question that doesn't require a 20 minute appointment, please come to our drop in hours. Students may be placed into the waiting room upon arrival.
Zoom access link for all sessions:
ZOOM LINK SENT TO STUDENTS DIRECTLY. CHECK EMAIL FOR LINK.
Wednesday, December 1st --- 10am -- 11am
Wednesday, December 1st --- 2:30pm -- 3:30pm
Wednesday, December 8th --- 10am -- 11am
Wednesday, December 8th --- 2:30pm -- 3:30pm
Wednesday, December 15th --- 10am -- 11am
Wednesday, December 15th --- 2:30pm -- 3:30pmLocation: Online
Audiences: Graduate
Contact: USC Computer Science
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Center of Autonomy and AI, Center for Cyber-Physical Systems and the Internet of Things, and Ming Hsieh Institute Seminar Series
Wed, Dec 01, 2021 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Mi Zhang , Machine Learning Systems Lab at Michigan State University
Talk Title: Empowering the Next Billion Devices with Deep Learning
Series: Center for Cyber-Physical Systems and Internet of Things
Abstract: The proliferation of edge devices and the gigantic amount of data they generate make it no longer feasible to transmit all the data to the cloud for processing. Such constraints fuel the need to move the intelligence from the cloud to the edge where data reside. In this talk, I will present our works on how we bring the power of deep learning to edge devices to realize the vision of Artificial Intelligence of Things (AIoT).
First, I will present our work on designing adaptive frameworks that empower AI-embedded edge devices to adapt to the inherently dynamic runtime resources to enable elastic on-device AI. Second, we shift from the single edge device setting to the distributed setting for the task of distributed on-device inference. I will focus on one killer application of edge computing, and present a distributed workload-adaptive framework for low-latency high-throughput large-scale live video analytics. Third, I will present our work on designing a distributed on-device training framework that significantly enhances the on-device training efficiency without compromising the training quality. Lastly, I will talk about our work on developing automated machine learning (AutoML) techniques to address the device deluge challenge which acts as one key barrier of achieving the vision of AIoT.
Biography: Mi Zhang is an Associate Professor and the Director of the Machine Learning Systems Lab at Michigan State University. He received his Ph.D. from University of Southern California and B.S. from Peking University. Before joining MSU, he was a postdoctoral scholar at Cornell University. His research lies at the intersection of mobile/edge/IoT systems and machine intelligence, spanning areas including On-Device/Edge AI, Automated Machine Learning (AutoML), Federated Learning, Systems for Machine Learning, Machine Learning for Systems, and AI for Health and Social Good. He has received a number of awards for his research. He is the 4th Place Winner of the 2019 Google MicroNet Challenge, the Third Place Winner of the 2017 NSF Hearables Challenge, and the champion of the 2016 NIH Pill Image Recognition Challenge. He is the recipient of seven best paper awards and nominations. He is also the recipient of the National Science Foundation CRII Award, Facebook Faculty Research Award, Amazon Machine Learning Research Award, and MSU Innovation of the Year Award.
Host: Pierluigi Nuzzo and Bhaskar Krishnamachari
Webcast: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQLocation: Online
WebCast Link: https://usc.zoom.us/webinar/register/WN_p5OEJlPxQlakO4hqovuGEQ
Audiences: Everyone Is Invited
Contact: Talyia White
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MS CSCI/DSCI Drop-in Academic Advising
Wed, Dec 01, 2021 @ 02:30 PM - 03:30 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
Virtual Academic Advising Drop-in Hours for continuing MS students in CS or Data Science Programs will be available for the month of December. If you have a quick question that doesn't require a 20 minute appointment, please come to our drop in hours. Students may be placed into the waiting room upon arrival.
Zoom access link for all sessions:
ZOOM LINK SENT TO STUDENTS DIRECTLY. CHECK EMAIL FOR LINK.
Wednesday, December 1st --- 10am -- 11am
Wednesday, December 1st --- 2:30pm -- 3:30pm
Wednesday, December 8th --- 10am -- 11am
Wednesday, December 8th --- 2:30pm -- 3:30pm
Wednesday, December 15th --- 10am -- 11am
Wednesday, December 15th --- 2:30pm -- 3:30pm
Location: Online
Audiences: Graduate
Contact: USC Computer Science
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AME Seminar
Wed, Dec 01, 2021 @ 03:30 PM - 04:30 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Emilie Dressaire, UCSB
Talk Title: Pushing boundaries: flow in low permeability media
Abstract: Generating and controlling fluid flow in low permeability environments is a challenge in natural and engineered systems. In this talk, I will discuss two studies involving the opening of fractures in a soft substrate and the clogging of microchannels.
The injection of fluid in brittle elastic materials drive the formation of cracks. Besides, when the pressure is released, the fluid flows out of the crack, in a process called backflow. Using a model experiment, we characterize the growth of a disk-like crack that propagates upon injection of the fluid, and its collapse as the injection pressure is released. The viscous dissipation, elastic deformation, and toughness of the matrix are important physical parameters that control the fluid flow in the crack or blister. This strategy is commonly used in rocks of low permeability and could find applications in bioengineering.
Yet the increase in permeability is only transient. A solution to avoid the closing of the crack formed by injection is to use suspensions of particles. However, the behavior of particles in confined systems remains mainly qualitative. I will discuss recent results obtained on the clogging of microchannels. When a suspension of particles flows in a microchannel, deposition and assembly can lead to the formation of a clog, followed by a stable aggregate of fixed porosity. I will present a model for the growth of the aggregate at the pore scale, which allows us to rationalize the evolution of the flow rate in networks of microchannels. Bridging the injection of fluid in elastic media with suspension dynamics is a promising route to advance printing in soft materials.
Biography: Emilie Dressaire received a B.S. in Engineering from ESPCI, France, in 2005, and a Ph.D. in Mechanical Engineering from Harvard University in 2009. She joined the Mechanical and Aerospace Engineering Department at NYU Tandon School of Engineering in 2014 and CNRS in 2017. She is now a faculty member in the Department of Mechanical Engineering at UCSB. She currently serves as a Member-at-Large on the Executive Committee of APS Division of Fluid Dynamics. Her research interests are centered around the areas of small scale fluid mechanics and soft matter physics, specifically focusing on interdisciplinary projects to develop bio-inspired methods to control and monitor fluid flows.
Host: AME Department
More Info: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09
Webcast: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09Location: Seaver Science Library (SSL) - 202
WebCast Link: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://usc.zoom.us/j/97427241653?pwd=UGd2aXY2b3dsQkxMdzdvcnNBMjRJZz09
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Drop-In Q&A for Prospective Graduate Students
Thu, Dec 02, 2021 @ 09:00 AM - 09:30 AM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
This webinar is designed for those that have specific questions they want answered. Questions will be submitted using the Q&A function and will be answered verbally by a USC Viterbi representative.
WebCast Link: https://usc.zoom.us/webinar/register/WN_a0cbNz_jQieaByFuoP32WQ
Audiences: Everyone Is Invited
Contact: William Schwerin
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[Theory Seminar] Vaggos Chatziafratis (Northwestern Unviersity) - Hierarchical Clustering: Recent Progress and Open Questions
Thu, Dec 02, 2021 @ 10:30 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Vaggos Chatziafratis, Northwestern University
Talk Title: Hierarchical Clustering: Recent Progress and Open Questions
Abstract: Hierarchical Clustering is an important tool for unsupervised learning whose goal is to construct a hierarchical decomposition of a given dataset describing relationships at all levels of granularity simultaneously. Despite its long history, Hierarchical Clustering was underdeveloped from a theoretical perspective, partly because of a lack of suitable objectives and algorithms with guarantees. In this talk, I want to tell you about the recent progress in the area with an emphasis on approximation algorithms and hardness results, and also highlight some interesting open problems.
Biography: Vaggos Chatziafratis' primary interests are in Algorithms and Machine Learning Theory. He is currently a postdoc at Northwestern and he will be a FODSI fellow at MIT and Northeastern starting January. He will also be joining UC Santa Cruz in Fall 2022 as an Assistant Professor.
Before that, he was at Google Research in New York, where he was part of the Algorithms and Graph Mining teams. Prior to that, he received his Ph.D. in Computer Science at Stanford, advised by Tim Roughgarden and co-advised by Moses Charikar. He received a Diploma in EECS from the National Technical University of Athens, Greece.
Host: Curtis Bechtel
Location: Henry Salvatori Computer Science Center (SAL) - 213
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Astani Civil and Environmental Engineering Seminar
Thu, Dec 02, 2021 @ 11:00 AM - 12:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Kofi Christie, Postdoctoral Research Associate, Princeton University
Talk Title: Sustainable membrane-based carbon mineralization
Abstract: Please see attached abstract and bio.
Host: Dr. Amy Childress
Webcast: https://usc.zoom/j/99680049945? Meeting ID: 996 8004 9945 Passcode: 905716More Information: K. Christie-Abstract_Bio 12-02-2021.pdf
Location: Michelson Center for Convergent Bioscience (MCB) - 101
WebCast Link: https://usc.zoom/j/99680049945? Meeting ID: 996 8004 9945 Passcode: 905716
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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NL Seminar-Event Extraction and Reasoning in Multimedia News Data
Thu, Dec 02, 2021 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Manling Li, Univ of Illinois at Urbana-Champaign
Talk Title: Event Extraction and Reasoning in Multimedia News Data
Abstract: Reminder: Meeting hosts only admit guests that they know to the Zoom meeting. Hence, you're highly encouraged to use your USC account to sign into Zoom.
If you are an outside visitor, please inform us at nlg DASH seminar DASH host AT isi DOT edu beforehand so we'll be aware of your attendance and let you in.Event understanding is an essential ability for humans to acquire information. With the rise of multimedia, automated event understanding and narration require machines to not only obtain the local structures of events from multimedia data i.e., who, what, where, and when), but also performs global understanding and inference i.e., what is likely to happen, and why. However, current event understanding is text-only, local, and lacks reasoning. Real events that are multimedia, interconnected, and probabilistic. This talk will present Multimedia Event Extraction to extract events and their arguments from multimedia data, and use event knowledge to enhance multimedia pretraining models. Based on the extracted knowledge, I will introduce how to induce event schemas (knowledge of complex event patterns) by learning a temporal graph model. After that, I will talk about how to use event knowledge to support real applications, such as timeline summarization.
Biography: Manling Li is a fourth year Ph.D. student at the Computer Science Department of University of Illinois Urbana Champaign. Manling has won the Best Demo Paper Award at ACL 20, the Best Demo Paper Award at NAACL 21, C.L. Dave and Jane W.S. Liu Award, and has been selected as Mavis Future Faculty Fellow. She is a recipient of the Microsoft Research PhD Fellowship. She has more than 30 publications on knowledge extraction and reasoning from multimedia data.
Host: Jon May and Thamme Gowda
More Info: https://nlg.isi.edu/nl-seminar/
Webcast: https://youtu.be/MLITKOKIHY0Location: Information Science Institute (ISI) - Virtual Only
WebCast Link: https://youtu.be/MLITKOKIHY0
Audiences: Everyone Is Invited
Contact: Pete Zamar
Event Link: https://nlg.isi.edu/nl-seminar/
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Create a Neo-Bank Over Lunch With Finch! (Viterbi, Virtual)
Thu, Dec 02, 2021 @ 01:00 PM - 02:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Learn more about creating neo-bank from Finch's business leaders. We've created a hands-on experience to look over the app's customer journey so we can identify key points of traction, feedback. We're also going to chat about working for a start-up and current opportunities, both remote and based in NYC.
RSVP for this virtual session on Viterbi Gateway.
Finch democratizes investment access and empowers customers to make their money work for them! Finch is an all-in-one checking and investment account that lets customers earn investment returns by automatically investing their checking balance into a portfolio designed to match their unique risk profile. Finch further pushes the envelope by enabling customers instant access to their money when they need it (even the invested part!). Finch is a productive checking account that puts your money to work for you! Finch empowers you to achieve your full financial potential. Finch was selected as a 2019 TechCrunch Top Pick, and we were part of the 2019 Barclays Accelerator, powered by Techstars in New York. We are currently growing our team in New York.
Q & A
Are you interested in undergraduates, masters, or PhD?
Everyone.
What majors are you recruiting for?
Computer Science, IT, Graphic Design and similar
Can you offer Visa sponsorship?
Yes.
Are you willing to hire a student on CTP or OPT?
Yes.
What types of internships and full-time opportunities will be presented?
Spring internship and full-time jobs.Location: Virtual Platform
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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Virtual First-Year Admission Information Session
Thu, Dec 02, 2021 @ 04:00 PM - 05:00 PM
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
Our virtual information session is a live presentation from a USC Viterbi admission counselor designed for high school students and their family members to learn more about the USC Viterbi undergraduate experience. Our session will cover an overview of our undergraduate engineering programs, the application process, and more on student life. Guests will be able to ask questions and engage in further discussion toward the end of the session.
Register here!Audiences: Everyone Is Invited
Contact: Viterbi Admission
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Drop-In Q&A for Prospective Graduate Students
Thu, Dec 02, 2021 @ 04:00 PM - 04:30 PM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
This webinar is designed for those that have specific questions they want answered. Questions will be submitted using the Q&A function and will be answered verbally by a USC Viterbi representative.
WebCast Link: https://usc.zoom.us/webinar/register/WN_MYe4mGEpQGWUDZnivSKgNw
Audiences: Everyone Is Invited
Contact: William Schwerin
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CAIS++ A Showcase of Undergrad AI Projects
Thu, Dec 02, 2021 @ 06:00 PM - 08:00 PM
Thomas Lord Department of Computer Science
Student Activity
Hi,
We are CAIS++, the undergraduate branch of USC's Center for Artificial Intelligence in Society (CAIS). Our mission is to advance AI for Social Good, and our group of 150+ students has worked with professors, startups, and community organizations to develop cutting-edge AI solutions for societal problems.
We're inviting you to our Fall 2021 Projects Showcase on Thursday, December 2nd from 6:00-8:00 pm both in person and on Zoom (specifics below). Our student teams will be presenting the AI research projects that they have worked on this semester, along with some paper and method reviews.
We will be recruiting new undergraduate members directly into our projects in Spring 2022, so coming to our showcase is a great way to learn about CAIS++ and see the type of work we do!
Hope to see you there!
Room: MCB 101
Zoom link: tinyurl.com/F21SHOWCAIS
Location: Michelson Center for Convergent Bioscience (MCB) - 101
WebCast Link: tinyurl.com/F21SHOWCAIS
Audiences: Everyone Is Invited
Contact: USC Computer Science
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Prospective Graduate Student Webinar: Chat with a USC Rep
Fri, Dec 03, 2021 @ 09:00 AM - 10:00 AM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Online webinars are held throughout the year via Zoom and hosted by Viterbi School representatives. All that is needed to participate is a computer with internet access. Webinars are designed for prospective students to learn more about:
Master's & Ph.D. Programs
Application Requirements
Tuition & Funding
There will also be ample time for questions.
Register
WebCast Link: https://usc.zoom.us/webinar/register/WN_VpuBLtevRYazKcD3C7P2Ow
Audiences: Everyone Is Invited
Contact: USC Viterbi Graduate Admission
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D.R.E.A.M. Pitch Industry Mentorship Panel
Fri, Dec 03, 2021 @ 10:00 AM - 11:20 AM
USC Viterbi School of Engineering
University Calendar
This panel features dream pitches from students with additive feedback from industry mentors from a variety of tech and destination companies. Please contact Elisabeth Arnold Weiss at arnolde@usc.edu if you would like to attend this event.
D.R.E.A.M. (Direct Response to Engineers Aspirations from Mentors) is an initiative that leverages insights from industry mentors who directly respond to students dream pitches, an original leadership communication assignment in WRIT 340 where students create a vision for their future selves, align their efforts around purpose, and build a consistent character and identity in the context of growth, reinvention, and constant change. To achieve that vision, they design a detailed career roadmap which encourages adaptability and determination, frees up cognitive resources to embrace new opportunities, and instills mental flexibility, long-range thinking, and a sense of agency about the future.
Location: Virtual (Zoom)
Audiences: Everyone Is Invited
Contact: Elisabeth Arnold Weiss
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PhD Thesis Proposal - Arka Sadhu
Fri, Dec 03, 2021 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
University Calendar
Ph.D. Thesis Proposal - Arka Sadhu
Friday, Dec 3rd, 2021: 12pm-2pm
Title: Grounding Language in Images and Videos
Thesis Committee members: Prof. Ram Nevatia, Prof. Xiang Ren, Prof. Yan Liu, Prof. Stefanos Nikolaidis, Prof. Toby Mintz.
Abstract: Language grounding in images and videos -- the task of associating linguistic symbols to perceptual experiences and actions -- is fundamental to developing multi-modal models which can understand and jointly reason over images, videos and text.
It has garnered wide interest from multiple disciplines such as computer vision, natural language processing, and robotics. An essential element in this space involves formulating tasks that investigate a particular phenomenon inherent in image or video understanding in isolation, thereby encouraging the community to develop more robust models. In this thesis proposal, I will articulate four vision-language tasks developed during the course of my Ph.D., namely, grounding unseen words, spatio-temporal localization of entities in a video, video question-answering, and visual semantic role labeling in videos. For each of these tasks, I will further discuss the development of corresponding datasets, evaluation protocols, and model frameworks.
Zoom Link: https://usc.zoom.us/j/92383912262?pwd=N25ETlRMVFRiWTlKdGxtN09UVHhlQT09WebCast Link: https://usc.zoom.us/j/92383912262?pwd=N25ETlRMVFRiWTlKdGxtN09UVHhlQT09
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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PhD Thesis Proposal - Chen-Yu Wei
Fri, Dec 03, 2021 @ 01:00 PM - 02:30 PM
Thomas Lord Department of Computer Science
University Calendar
Time: 1:00-2:30pm, December 3rd
Committee: Haipeng Luo (host), Rahul Jain, David Kempe, Vatsal Sharan, Jiapeng Zhang
Title: Robust and Adaptive Online Reinforcement Learning
Abstract: Online reinforcement learning (RL) studies how an agent learns to behave in an unknown environment from scratch. In this thesis, I focus on the theoretical foundations of this learning paradigm, with emphasis on designing algorithms that are robust to the non-stationarity of the environment, where the non-stationarity may come from natural drift, adversarial manipulation, or the existence of other agents. While being robust, most of our algorithms are also "adaptive" at the same time in the sense that they do not sacrifice nice performance guarantees if the environment happens to be stationary. More broadly speaking, the performance of our algorithms automatically scale with some intrinsic properties that reflect the difficulty of the problem.
For future work, I plan to characterize the fundamental limit of RL in large state space, a central topic in theoretical RL. We hope to answer the following questions: "what are the minimal assumptions to be made so that RL algorithms can find near-optimal policies with polynomial number of samples", and the similar question under the restriction of "polynomial computational time".WebCast Link: https://usc.zoom.us/j/96695544670?pwd=VnZJUzRLam9scVpHbFRTYUVmQlk4Zz09
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Ming Hsieh Institute Seminar Series on Integrated Systems
Fri, Dec 03, 2021 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Jie Gu, Associate Professor, Northwestern University
Talk Title: Exploring New Dimensions of CMOS Deep Learning Accelerators with Neural CPU Architecture and Compute-in-Memory Circuits
Host: Mike Chen, Hossein Hashemi, Manuel Monge, Constantine Sideris
More Information: MHI IS Seminar - Jie Gu_Flyer.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Jenny Lin
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Viterbi Voices Live Chat: Do More Than Engineering
Sun, Dec 05, 2021 @ 07:00 PM - 08:00 PM
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
Join us for this student hosted live chat! During this hour long event, we will be answering your questions about Engineering+ at USC Viterbi. These engineering students use their classes, extracurriculars, and free time to do more than just engineering.
Register here!
Audiences: Everyone Is Invited
Contact: Viterbi Admission
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LEAPFROG Lander Flight Ops | Call for Applications
Mon, Dec 06, 2021 @ 12:00 PM - 01:00 PM
Astronautical Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. David Barnhart, Director of SERC
Talk Title: LEAPFROG Lander Flight Ops | Call for Applications
Abstract: LEAPFROG is a unique prototype lander designed at USC and is an approved STEP Pilot program through NASA's Artemis in conjunction with UC San Diego and UC Berkeley. In Summer 2022, we will execute flight competitions where universities from around the country will have the opportunity to test their software on LEAPFROG landers. Up to three students will be eligible for paid internships for the SUMMER 2022 Flight Competition from USC. For more information, visit our website at either leapfrog.isi.edu or www.isi.edu/centers/serc/join_us
Virtual Event Link: https://usc.zoom.us/j/92579469862
Host: Prof. David Barnhart
Audiences: Everyone Is Invited
Contact: Dell Cuason/ Prof. Barnhart
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"DODONA": Intro to USC's 3rd Satellite
Mon, Dec 06, 2021 @ 02:00 PM - 03:00 PM
Astronautical Engineering
Conferences, Lectures, & Seminars
Speaker: Prof. David Barnhart, Director of SERC
Talk Title: "DODONA": Intro to USC's 3rd Satellite
Abstract: A seminar presented by Space Engineering Research Center (SERC) team on USC's 3rd Satellite planned launch! "DODONA" is USC and the SERC's 3rd Satellite flight project in its history, slated to be launched early January 2022. This will be USC's first optical satellite launch and operations, and the SERC's first operation of the USC Ground Station to command the satellite from campus!
Virtual Event Link: https://usc.zoom.us/j/99363615054
Host: Prof. David Barnhart
Audiences: Everyone Is Invited
Contact: Dell Cuason/ Prof. Barnhart
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USC MAKERS SHOWCASE!
Mon, Dec 06, 2021 @ 04:00 PM - 06:00 PM
Thomas Lord Department of Computer Science
Student Activity
Hello CSCI Department!
You are invited to come to the USC Makers Fall Showcase, held this Monday, 12/6 at EEB 132 and Zoom (Meeting ID 95712265761)!
Come see what our Makers have been working on for the past semester! We've got all sorts of projects -” from a robot controlled with your arm, to an environmentally friendly smart composting machine, to an intelligent real-time automated drum set -” that we'd love for everyone to check out!
For more information on our projects, check out our Instagram @uscmakers where we'll be posting previews of the projects that you'll be able to see over the next few days. Please direct any questions to uscmakers@gmail.com, and check out our website for more information about our club!
https://viterbimakers.usc.edu/
The event will run from 4:00 to 6:00 PM, and there will be free food. If you cannot make it to the event, we will also be streaming it on Zoom at this link. Hope to see you there!
https://usc.zoom.us/j/95712265761
- USC Makers
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/95712265761
Audiences: Everyone Is Invited
Contact: USC Computer Science
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USC AI Futures Symposium on AI with Common Sense
Tue, Dec 07, 2021 @ 09:00 AM - 12:00 PM
Thomas Lord Department of Computer Science, Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Multiple panelists, USC and collaborators
Talk Title: AI with Common Sense
Series: USC AI Futures Symposium on AI
Abstract: Humans use common sense knowledge to understand how the world works. AI systems still lack common sense knowledge, which is critical in many domains in order to form expectations, manage unexpected situations, and connect with the human experience. This symposium presents an overview of research at USC on acquiring and organizing commonsense knowledge, integrating it into AI systems, and measuring its impact on improving AI system behaviors and interactions with people.
This event is part of the USC AI Futures Symposium Series. Prior events were held in May 2021 with the theme: AI and Data Science, and in January 2021 with the theme: Will AIs Ever Be One of Us?.
Please visit website to register and view updated information https://isi-usc-edu.github.io/USC-CommonSense-Symposium/
Host: Yolanda Gil
Location: Virtual
Audiences: Everyone Is Invited
Contact: Lori Weiss/USC ISI
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Mork Family Department Holiday Luncheon
Tue, Dec 07, 2021 @ 12:00 PM - 02:00 PM
Mork Family Department of Chemical Engineering and Materials Science
Receptions & Special Events
Please come out & join us for the MFD Holiday Luncheon
December 7, 2021
12:00P.M.
VHE Breezeway (located in Epstein Plaza)
Please RSVP HERE by November 29th.
Food, Music, & Games!
Wear your MFD and/or USC Swag!
Location: Vivian Hall of Engineering (VHE) - VHE Breezeway
Audiences: Everyone Is Invited
Contact: Greta Harrison
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Drop-In Weekly Office Hours [Virtual] Posted By: Center for Advanced Research Computing
Tue, Dec 07, 2021 @ 02:30 PM - 05:00 PM
Information Technology Program (ITP)
Workshops & Infosessions
Every Tuesday, office hours are an opportunity for CARC users to ask questions about research computing. No appointment/registration is necessary, but you must use your USC credentials to access the Zoom meeting by clicking "Register" below. For in-person support, we are also in Leavey Library room 3M (basement) during this same time period. Register Here!
Audiences: Everyone Is Invited
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Virtual First-Year Admission Information Session
Tue, Dec 07, 2021 @ 04:00 PM - 05:00 PM
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
Our virtual information session is a live presentation from a USC Viterbi admission counselor designed for high school students and their family members to learn more about the USC Viterbi undergraduate experience. Our session will cover an overview of our undergraduate engineering programs, the application process, and more on student life. Guests will be able to ask questions and engage in further discussion toward the end of the session.
Register here!Audiences: Everyone Is Invited
Contact: Viterbi Admission
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Haier Global Engineering Development Program (GEDP) : You Are the Chosen One!
Tue, Dec 07, 2021 @ 09:00 PM - 10:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Global Engineering Development Program (GEDP) , was founded after Haier's acquisition on GEA in 2016. The program aims to cultivate future technical and business leaders of Haier Group.
Join Zoe Pang, the Global Talent Acquisition Manager at Haier, for a one-hour webinar on 'Haier Global Engineering Development Program (GEDP): You are the chosen one!
WHEN-Tuesday, December 7th from 9-10pm PST at Tencent Meeting
REGISTER ON VITERBI GATEWAY
Highlights about GEDP:
- Elite: only 30 elites are accepted each year
- Rotations: rotations within the engineering functions of Haier across 2 years
- Training: Virtual leadership, technology, and business acumen training
- Development: High level engineering development program
Our targets:
- QS ranking top 200 schools
- Majored in Electrical Engineering or Mechanical Engineering
- Master degree in related field
- Excellent leadership and coordinate ability
- Project experience is preferred
- Chinese Passport / Work visa holder (Work Base: Qingdao, China)
Location: Virtual Platform
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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USC AI Futures Symposium on AI with Common Sense
Wed, Dec 08, 2021 @ 09:00 AM - 12:00 PM
Thomas Lord Department of Computer Science, Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Multiple panelists, USC and collaborators
Talk Title: AI with Common Sense
Series: USC AI Futures Symposium on AI
Abstract: Humans use common sense knowledge to understand how the world works. AI systems still lack common sense knowledge, which is critical in many domains in order to form expectations, manage unexpected situations, and connect with the human experience. This symposium presents an overview of research at USC on acquiring and organizing commonsense knowledge, integrating it into AI systems, and measuring its impact on improving AI system behaviors and interactions with people.
This event is part of the USC AI Futures Symposium Series. Prior events were held in May 2021 with the theme: AI and Data Science, and in January 2021 with the theme: Will AIs Ever Be One of Us?.
Please visit website to register and view updated information https://isi-usc-edu.github.io/USC-CommonSense-Symposium/
Host: Yolanda Gil
Location: Virtual
Audiences: Everyone Is Invited
Contact: Lori Weiss/USC ISI
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MS CSCI/DSCI Drop-in Academic Advising
Wed, Dec 08, 2021 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
Virtual Academic Advising Drop-in Hours for continuing MS students in CS or Data Science Programs will be available for the month of December. If you have a quick question that doesn't require a 20 minute appointment, please come to our drop in hours. Students may be placed into the waiting room upon arrival.
Zoom access link for all sessions:
ZOOM LINK SENT TO STUDENTS DIRECTLY. CHECK EMAIL FOR LINK.
Wednesday, December 1st --- 10am -- 11am
Wednesday, December 1st --- 2:30pm -- 3:30pm
Wednesday, December 8th --- 10am -- 11am
Wednesday, December 8th --- 2:30pm -- 3:30pm
Wednesday, December 15th --- 10am -- 11am
Wednesday, December 15th --- 2:30pm -- 3:30pmLocation: Online
Audiences: Graduate
Contact: USC Computer Science
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Computer Science General Faculty Meeting
Wed, Dec 08, 2021 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: TBD
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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PhD Thesis Proposal - Hikaru Ibayashi
Wed, Dec 08, 2021 @ 02:00 PM - 03:30 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Proposal - Hikaru Ibayashi
Wed, Dec 8, 2021 @ 02:00 PM - 03:30 PM
Committee members: Chair: Prof. Aiichiro Nakano, Prof. Satish Kumar Thittamaranahalli, Prof. Emilio Ferrara, Prof. Yan Liu, Prof. Paulo Branicio (Department of Chemical Engineering and Materials Science)
Title:
Sharpness analysis of neural-networks for high-performance physics simulation
Abstract:
In recent years, deep neural networks have witnessed tremendous success in a wide range of fields. Especially, in physics simulations, neural networks have achieved drastically efficient computation by approximating first-principles simulations. However, such practical successes have opened theoretical problems. One open question is why a simple optimization algorithm such as stochastic gradient descent (SGD) can find solutions that generalize well over non-convex loss surfaces. In this proposal, we leverage the second-order information of loss surface, i.e., sharpness, to lay a theoretical foundation of the generalizability of neural networks. First, we use a novel quasi-potential theory to prove that SGD avoids non-generalizing sharp minima. Secondly, we develop a scale-invariant sharpness measure named "minimum sharpness" to theoretically explain why sharp minima are not generalizing. Finally, as a practical application of the thus-developed theoretical framework, we propose a novel sharpness-regularization scheme for robust neural-network-based molecular dynamics simulations. This research will demonstrate the effectiveness of sharpness analysis to deepen the understanding of neural networks and their successful application in physics simulations.
Zoom link: https://usc.zoom.us/j/7751892842WebCast Link: https://usc.zoom.us/j/7751892842
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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MS CSCI/DSCI Drop-in Academic Advising
Wed, Dec 08, 2021 @ 02:30 PM - 03:30 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
Virtual Academic Advising Drop-in Hours for continuing MS students in CS or Data Science Programs will be available for the month of December. If you have a quick question that doesn't require a 20 minute appointment, please come to our drop in hours. Students may be placed into the waiting room upon arrival.
Zoom access link for all sessions:
ZOOM LINK SENT TO STUDENTS DIRECTLY. CHECK EMAIL FOR LINK.
Wednesday, December 1st --- 10am -- 11am
Wednesday, December 1st --- 2:30pm -- 3:30pm
Wednesday, December 8th --- 10am -- 11am
Wednesday, December 8th --- 2:30pm -- 3:30pm
Wednesday, December 15th --- 10am -- 11am
Wednesday, December 15th --- 2:30pm -- 3:30pm
Location: Online
Audiences: Graduate
Contact: USC Computer Science
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CS Colloquium: Yajie Zhao (USC ICT) - Automating 3D Contents Creation for AR/VR
Wed, Dec 08, 2021 @ 03:30 PM - 04:30 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Yajie Zhao, USC
Talk Title: Automating 3D Contents Creation for AR/VR
Abstract: The last couple of years have shown an incredible boost in performance, quality of real-time applications of AR/VR. The creation of high quality 3D assets, including virtual human, objects and 3D environments is tied with complex capture equipment, massive data, a long production cycle and intensive manual labor by a professional team. And it may still be in the notorious Uncanny Valley. In this talk, I will explore how to produce high quality 3D assets in a low-cost way. I will discuss how to leverage AI-based technologies to automate, accelerate, and simplify the industrial production procedure of 3D contents creation from data capturing to rendering. And bring photorealism to the next level!
This lecture satisfies requirements for CSCI 591: Research Colloquium
Join Zoom Meeting
https://usc.zoom.us/j/97098103729
Meeting ID: 970 9810 3729
Biography: Dr. Yajie Zhao is a computer scientist at USC Institute for Creative Technologies (ICT), University of Southern California. She is currently the acting director of the Vision and Graphics Lab of USC-ICT. Her research interests are high-quality 3D content creation for AR/VR, which includes human digitization, performance capturing, and scene reconstruction/ understanding. Yajie Zhao earned her Ph.D. degree in 2017 from the University of Kentucky under the supervision of Dr. Ruigang Yang.
Host: Aram Galstyan
Audiences: Everyone Is Invited
Contact: Cherie Carter
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Drop-In Q&A for Prospective Graduate Students
Thu, Dec 09, 2021 @ 09:00 AM - 09:30 AM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
This webinar is designed for those that have specific questions they want answered. Questions will be submitted using the Q&A function and will be answered verbally by a USC Viterbi representative.
WebCast Link: https://usc.zoom.us/webinar/register/WN_a0cbNz_jQieaByFuoP32WQ
Audiences: Everyone Is Invited
Contact: William Schwerin
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PhD Thesis Proposal -Yury Zemlyanskiy
Thu, Dec 09, 2021 @ 11:00 AM - 01:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Yury Zemlyanskiy
Title: Parametric and semi-parametric methods for knowledge acquisition from text
Time: 11:00 AM-1:00 PM PST, Dec 9 (Thursday)
Committee: Fei Sha, Leana Golubchik, Xiang Ren, Robin Jia, Jonathan May, and Meisam Razaviyayn (external).
Zoom link: https://usc.zoom.us/j/95672050503
Abstract:
Knowledge acquisition is a crucial characteristic of an intelligent system that allows the processing of large amounts of information. Nonetheless, modern neural networks (e.g., BERT) used in natural language processing typically do not have a dedicated memory component. The knowledge about the world that the models acquire is stored implicitly in the model's parameters. This proves unreliable and makes the models ill-suited for knowledge-intensive tasks that require reasoning over vast amounts of textual data.
My thesis explores alternative parametric and semi-parametric methods to extract and represent knowledge from text. Specifically, the proposed methods seek to establish several desirable properties for the neural network memory component. First, the memory should benefit the model and allow it to reason over large amounts of textual information. Second, the memory should be amendable and adapt to a new context (a different book or collection of articles) on the fly. Finally, certain applications will benefit from the transparent structure of the memory, allowing queries on information about particular objects or entities.
The proposed thesis consists of three sections: the first section focuses on parametric memory for a pre-defined set of entities. The second section explores a semi-parametric approach to capturing entity-centric facts in a long document or entire corpus. Finally, the last section discusses future work on memory specialized for structure prediction tasks.WebCast Link: https://usc.zoom.us/j/95672050503
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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DEN@Viterbi - 'Limited Status: How to Get Started' Virtual Info Session
Thu, Dec 09, 2021 @ 12:00 PM - 01:00 PM
DEN@Viterbi, Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Join USC Viterbi for our upcoming Limited Status: How to Get Started Virtual Information Session via WebEx to learn about the Limited Status enrollment option. The Limited Status enrollment option allows individuals with an undergraduate degree in engineering or related field, with a 3.0 GPA or above to take courses before applying for formal admission into a Viterbi graduate degree program.
USC Viterbi representatives will provide a step-by-step guide for how to get started as a Limited Status student and enroll in courses online via DEN@Viterbi as early as the Fall 2021 semester.
Register Now!WebCast Link: https://uscviterbi.webex.com/uscviterbi/onstage/g.php?MTID=e17797dbf51d6d3a6aa135130d03953e5
Audiences: Everyone Is Invited
Contact: Corporate & Professional Programs
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Prospective Graduate Student Webinar: Chat with a USC Rep
Thu, Dec 09, 2021 @ 02:00 PM - 03:00 PM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Online webinars are held throughout the year via Zoom and hosted by Viterbi School representatives. All that is needed to participate is a computer with internet access. Webinars are designed for prospective students to learn more about:
Master's & Ph.D. Programs
Application Requirements
Tuition & Funding
There will also be ample time for questions.
Register
WebCast Link: https://usc.zoom.us/webinar/register/WN_G_aGS8PeT1q99PI1qir8nA
Audiences: Everyone Is Invited
Contact: USC Viterbi Graduate Admission
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CANCELLED - DEI Committee Meeting
Thu, Dec 09, 2021 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly DEI Committee meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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PhD Thesis Proposal - Sarah Cooney
Thu, Dec 09, 2021 @ 03:00 PM - 04:30 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Proposal - Sarah Cooney
Thur, Dec 9, 2021 @ 03:00 PM - 04:30 PM
Committee members: Chair: Prof. Barath Raghavan, Prof. Romesh Govindan, Prof. Heather Culbertson, Prof. Bistra Dilkina, Prof. Hajar Yazdiha (Sociology)
Title:
Toward Sustainable and Resilient Communities
with HCI: Physical Structures and Socio-Cultural Factors
Abstract:
Recently, large-scale global challenges such as shifting weather patterns due to climate change and the Covid-19 pandemic have caused us to be more reliant than ever on the resources and resilience of our local communities. My research looks at how computing can be applied to the challenges of creating sustainable and resilient communities equipped to handle such challenges at the local level. My work covers two complementary threads. The first looks at how technology can be used to influence grassroots redesign of urban spaces to promote sustainability, community resilience, and individual wellbeing. Within this area I have worked on three specific projects which I will discuss in more detail. The second thread looks at sustainability and sustainable HCI from a socio-cultural perspective. Specifically, I have been looking at the way that religion and spirituality can influence the intersections of sustainability and technology use, and I will discuss my ongoing study in this area as well.
Zoom link: https://usc.zoom.us/j/96182449560
WebCast Link: https://usc.zoom.us/j/96182449560
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Virtual First-Year Admission Information Session
Thu, Dec 09, 2021 @ 04:00 PM - 05:00 PM
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
Our virtual information session is a live presentation from a USC Viterbi admission counselor designed for high school students and their family members to learn more about the USC Viterbi undergraduate experience. Our session will cover an overview of our undergraduate engineering programs, the application process, and more on student life. Guests will be able to ask questions and engage in further discussion toward the end of the session.
Register here!Audiences: Everyone Is Invited
Contact: Viterbi Admission
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Drop-In Q&A for Prospective Graduate Students
Thu, Dec 09, 2021 @ 04:00 PM - 04:30 PM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
This webinar is designed for those that have specific questions they want answered. Questions will be submitted using the Q&A function and will be answered verbally by a USC Viterbi representative.
WebCast Link: https://usc.zoom.us/webinar/register/WN_MYe4mGEpQGWUDZnivSKgNw
Audiences: Everyone Is Invited
Contact: William Schwerin
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DEN@Viterbi: How to Apply Virtual Info Session
Fri, Dec 10, 2021 @ 09:00 AM - 10:00 AM
DEN@Viterbi, Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Join USC Viterbi representatives for a step-by-step guide and tips for how to apply for formal admission into a Master's degree or Graduate Certificate program. The session is intended for individuals who wish to pursue a graduate degree program completely online via USC Viterbi's flexible online DEN@Viterbi delivery method.
Attendees will have the opportunity to connect directly with USC Viterbi representatives and ask questions about the admission process throughout the session.
Register Now!WebCast Link: https://uscviterbi.webex.com/uscviterbi/onstage/g.php?MTID=e5b659b5af59cae9d39c38b8b90838d69
Audiences: Everyone Is Invited
Contact: Corporate & Professional Programs
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Medical Imaging Seminar Series
Fri, Dec 10, 2021 @ 10:00 AM - 11:00 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Talk Title: Improved Regularized Simultaneous Multi-slice (SMS) Imaging Reconstruction
Series: Medical Imaging Seminar Series
Abstract: MRI acquisitions are inherently slow, necessitating the use of accelerated imaging. Simultaneous multi- slice (SMS) imaging has gained substantial interest by providing improved coverage with minimum signal- to-noise ratio (SNR) loss in accelerated MRI and has been widely integrated into large-scale projects such as Human Connectome Project. However, ultra-high accelerations are prone to noise amplification and residual aliasing artifacts, necessitating new reconstruction techniques that can successfully suppress both. In this talk, we will present recently developed techniques for regularized SMS reconstruction. We will first introduce two model-based algorithms that simultaneously reduce noise amplification and inter-leakage artifacts. Subsequently, we will concentrate on physics-guided deep learning reconstruction for SMS MRI with applications in fMRI. Finally, we will discuss an alternative way to view the multi-coil encoding operator in physics-guided DL reconstruction for improved generalizability in dynamic contrast-enhanced MRI.
Biography: Omer Burak Demirel is a PhD candidate at the University of Minnesota working with Prof. Mehmet Akçakaya. Prior to the University of Minnesota, he received the B.S. and M.S. degrees from Bilkent University, Ankara, Turkey in January 2015 and June 2017, respectively. His research interests include image processing, MRI acquisition methods, image reconstruction techniques and accelerated MRI. He is a recipient of an AHA predoctoral fellowship focusing on improved image reconstruction techniques for cardiac MRI.
Host: Krishna Nayak, knayak@usc.edu
Webcast: https://usc.zoom.us/j/95249648177?pwd=RHNsSnlhMk0vaEtPeExXRkRPOE55dz09Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
WebCast Link: https://usc.zoom.us/j/95249648177?pwd=RHNsSnlhMk0vaEtPeExXRkRPOE55dz09
Audiences: Everyone Is Invited
Contact: Talyia White
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PhD Thesis Proposal - Séb Arnold
Fri, Dec 10, 2021 @ 03:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Thesis Proposal - Séb Arnold
Friday, Dec 10, 2021 @ 03:00 PM - 05:00 PM
Committee members: Chair: Prof. Maja Mataric, Prof. Fei Sha, Prof. Yan Liu, Prof. Stefanos Nikolaidis, Prof. Jesse Thomason, Prof. Salman Avestimehr (ECE)
Title:
Quickly solving new tasks, with meta-learning and without.
Abstract:
This thesis proposal seeks to answer how learning systems can reuse and adapt their knowledge to quickly solve new test tasks. We first show how to improve the test task performance of meta-learning algorithms (eg, MAML) by carefully choosing which tasks to train on -- even when these test tasks are unknown a priori. We then zero in on these algorithms and uncover modeling pitfalls that completely prevent fast adaptation; fortunately, there exist simple remedies. Leveraging those insights, we conclude with the challenge of quickly solving new tasks using off-the-shelf models, which were trained without meta-learning.
Zoom link: https://usc.zoom.us/j/94965325337
WebCast Link: https://usc.zoom.us/j/94965325337
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Astani Department of Civil and Environmental Engineering Ph.D. Dissertation
Mon, Dec 13, 2021 @ 04:00 PM - 06:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Preetham Aghalaya Manjunatha , Astani Department of Civil and Environmental Engineering
Talk Title: Vision-Based and Data-driven Analytical and Experimental Studies into Condition Assessment and Change Detection of Evolving Civil, Mechanical and Aerospace Infrastructures
Abstract: Civil, mechanical, and aerospace infrastructures are subjected to applied loads and environmental forces like earthquakes, wind, and water waves in their operating lifespan. These factors will slowly deteriorate the structures during their service period, and often subtle observations of substantial damages are challenging. Due to the cost-effectiveness of high-resolution color, depth cameras, location sensors, and Micro Aerial Vehicles (MAVs), image processing, computer vision, and robotics techniques are gaining interest in Non-Destructive Testing (NDT) and condition assessment of infrastructures. In this study, several promising vision-based and data-driven, automated, and semi-automated condition assessment techniques are proposed and evaluated to detect and quantify a class of problems under the umbrella of infrastructure condition assessment.
A synthetic crack generation methodology is introduced to generate zero-labeled samples for training the classical classifiers. This classifier was tested on a real-world dataset using the gradient-based hierarchical hybrid Multi-scale Fractional Anisotropy Tensor (MFAT) filter to segment the cracks. The results demonstrate the promising capabilities of the proposed synthetic crack generation method. Furthermore, the textural noise suppression and refinement are carried out by using an anisotropic diffusion filter. Guidelines are provided to select the parameters for the anisotropic diffusion filter. Further, this study presents the semantic segmentation of the cracks on concrete surface images using a deep Convolutional Neural Network (CNN) that has fewer parameters to learn. Several illustrative examples are presented to demonstrate the capabilities of the CNN-based crack segmentation procedure. The CNN was tested on the four real-world datasets, and the results show the proposed CNN's superiority against four state-of-the-art methods.
As a part of this study, an efficient and autonomous crack change detection, tracking, and evolution methodology is introduced. Among the image registration methods, feature-based registration is robust to the noise, intensity change, and partial affine motion model. This study uses an efficient $k$-d tree-based nearest neighbor search which is faster than the quadratic computational complexity of the current pairwise search. Furthermore, unlike other methods, the fixed camera assumption is relaxed in this study. Another significant contribution is a probabilistic measure of the reliability of the analysis results that can aid the prognosis damage detection models.
After the nearest neighbor search, the SURF-based keypoints are extracted from the images in the previous database and the current one. This is followed by the Random Sample Consensus (RANSAC)-based outliers rejection, bundle adjustment to refine the homographies, gain exposure compensation and multi-band blending for the seamless registration images. Lastly, the registered image is compared to the current images for the change detection in crack physical properties. To demonstrate the capabilities of the proposed method, two datasets were utilized; a real-world dataset, and a synthetic dataset. The experimental results show that the performance of the proposed methodology is suitable for detecting the crack changes in two datasets.
This work also studies the condition assessment of public sewer pipelines. The visual-bags-of-words model was evaluated for classifying the defective and non-defective sewer pipeline images using two feature descriptors. Three classical classifiers are trained and tested on a moderate-sized dataset of 14,404 images. The experimental results demonstrate that the classification accuracy of the visual-bags-of-words model is satisfactory and comparable to deep learning methods given the moderate dataset size.
Lastly, defect detection of the three-dimensional surface of mechanical parts is studied. A preliminary study on a vision-based semi-autonomous spatio-temporal method to detect, locate and quantify the defects such as loose bolts, displacements, pipe chafing, or deformation is proposed. In addition, a probabilistic reliability quantification method based on the ensemble averaging of the Cloud-to-Cloud (C2C) distances is introduced for mechanical systems. Several quantitative and qualitative examples are presented to illustrate the capabilities of the proposed method. The results show that the proposed method is promising and robust to register the complex shapes, and detect and locate the changes in the mechanical systems.
Webcast: https://usc.zoom.us/j/98823087239? Meeting ID: 988 2308 7239 Passcode: 729479WebCast Link: https://usc.zoom.us/j/98823087239? Meeting ID: 988 2308 7239 Passcode: 729479
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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Drop-In Weekly Office Hours [Virtual] Posted By: Center for Advanced Research Computing
Tue, Dec 14, 2021 @ 02:30 PM - 05:00 PM
Information Technology Program (ITP)
Workshops & Infosessions
Every Tuesday, office hours are an opportunity for CARC users to ask questions about research computing. No appointment/registration is necessary, but you must use your USC credentials to access the Zoom meeting by clicking "Register" below. For in-person support, we are also in Leavey Library room 3M (basement) during this same time period. Register Here!
Audiences: Everyone Is Invited
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Virtual First-Year Admission Information Session
Tue, Dec 14, 2021 @ 04:00 PM - 05:00 PM
Viterbi School of Engineering Undergraduate Admission
Workshops & Infosessions
Our virtual information session is a live presentation from a USC Viterbi admission counselor designed for high school students and their family members to learn more about the USC Viterbi undergraduate experience. Our session will cover an overview of our undergraduate engineering programs, the application process, and more on student life. Guests will be able to ask questions and engage in further discussion toward the end of the session.
Register here!Audiences: Everyone Is Invited
Contact: Viterbi Admission
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DEN@Viterbi - 'Limited Status: How to Get Started' Virtual Info Session
Tue, Dec 14, 2021 @ 06:00 PM - 07:00 PM
DEN@Viterbi, Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Join USC Viterbi for our upcoming Limited Status: How to Get Started Virtual Information Session via WebEx to learn about the Limited Status enrollment option. The Limited Status enrollment option allows individuals with an undergraduate degree in engineering or related field, with a 3.0 GPA or above to take courses before applying for formal admission into a Viterbi graduate degree program.
USC Viterbi representatives will provide a step-by-step guide for how to get started as a Limited Status student and enroll in courses online via DEN@Viterbi as early as the Fall 2021 semester.
Register Now!WebCast Link: https://uscviterbi.webex.com/uscviterbi/onstage/g.php?MTID=e2dd0e1b1527d4f16bbd4241ef282076b
Audiences: Everyone Is Invited
Contact: Corporate & Professional Programs
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MS CSCI/DSCI Drop-in Academic Advising
Wed, Dec 15, 2021 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
Virtual Academic Advising Drop-in Hours for continuing MS students in CS or Data Science Programs will be available for the month of December. If you have a quick question that doesn't require a 20 minute appointment, please come to our drop in hours. Students may be placed into the waiting room upon arrival.
Zoom access link for all sessions:
ZOOM LINK SENT TO STUDENTS DIRECTLY. CHECK EMAIL FOR LINK.
Wednesday, December 1st --- 10am -- 11am
Wednesday, December 1st --- 2:30pm -- 3:30pm
Wednesday, December 8th --- 10am -- 11am
Wednesday, December 8th --- 2:30pm -- 3:30pm
Wednesday, December 15th --- 10am -- 11am
Wednesday, December 15th --- 2:30pm -- 3:30pmLocation: Online
Audiences: Graduate
Contact: USC Computer Science
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Astani Department of Civil and Environmental Engineering Ph.D. Dissertation
Wed, Dec 15, 2021 @ 12:00 PM - 02:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Xiaoshu Zeng, CE Ph.D. Candidate, Viterbi School- Astani Department of Civil and Environmental Engineering
Talk Title: Efficient Inverse Analysis with Dynamic and Stochastic Reductions for Large-Scale Models of Multi-Component Systems
Abstract: This work has two main goals: the primary goal of dealing with inverse analysis for large-scale models of multi-component systems and the second goal of dealing with the multi-fidelity uncertainty
quantification (UQ) for models with dissimilar parameterization. The primary goal involves efficient structural dynamic analysis, probabilistic modeling, and inverse analysis for the following reasons:
1. The context is the integrity assessment of the internals of a complex multi-scale structure, a fullyloaded spent nuclear fuel canister (FLSNFC), with the assessment based on dynamic signals on the
exterior surface of the FLSNFC before and after transportation.
2. Since the observed data is inevitably subjected to errors, the inverse analysis usually requires an accurate probabilistic model to capture the uncertainty propagated to the quantities of interest (QoI).
3. An efficient forward model, a dynamic model, is essential to construct a probabilistic model for complex systems.
A first attempt to build an efficient dynamic model is through constructing a global reduced-order basis (ROB). Usually, the complex multi-scale structures are characterized by numerous local vibration modes (or elastic modes) and the usual long-wavelength global vibration modes. Accordingly, a methodology that does not require the computation of the numerous local modes builds a global reduced-order model (ROM) by constructing a global ROB. In this method, the kinematics of the structure is modified to filter the local vibrations. Moreover, the reduced kinematics is combined with the idea of static condensation to achieve higher accuracy.
Due to the high accuracy requirement, a second attempt for dynamic modeling is carried out. For the FLSNFC, a honeycomb basket is placed inside the cylindrical canister, and a fuel assembly (FA)
that holds nearly 100 fuel rods is inserted in each of the 68 basket cells. A multi-level nested CraigBampton (CB) sub-structuring method with shift-invert Lanczos (SIL) eigenvalue solver and filtering of the local vibration modes of the substructures is proposed. This method is adapted to the multi-scale nature and localized connections between the substructures. The CB sub-structuring technique takes advantage of the limited degrees of freedom (DOF) of internal boundary and is applied to modal analysis for two structural levels, the system and the FA levels. As a result, the integrated method achieves a computational gain of four orders of magnitude for the FLSNFC at the expense of negligible errors.
For probabilistic modeling, polynomial chaos expansion (PCE) is an efficient method, but it suffers from the curse of dimensionality. However, a basis adaptation method proposed by Tipireddy and Ghanem (2014) [6] can reduce the dimension of the problem by rotating the input Gaussian random variables such that the quantity of interest (QoI) in the new space has concentrated representation. In this study, we proposed two novel approaches that can accelerate the convergence of the basis adaptation method. In the first approach, the mean and Gaussian coefficients in the adapted space are corrected by information obtained from a pilot PCE. The second approach updates the rotation matrix by taking advantage of the probabilistic information embedded in the higher dimensional adaptation gleaned from an initial adaptation. As a result, both approaches achieve accelerated convergence of the basis adaptation method with negligible additional costs.
The basis adaptation is adequate to reduce the dimension for the scalar QoI problems. To deal with UQ problems with high dimensional QoI and high dimensional parameter space, the integration of Karhunen- Loève expansion (KLE) and basis adaptation is proposed. The KLE first approximates the QoI to reduce the dimension of the QoI to a limited number of KL terms. Then, for each KL term, an adapted PCE is built with the accelerated basis adaptation method to reduce the dimension of the input variables. The PCE models of the KL terms then can be substituted back to the KLE of the QoI to obtain a surrogate probabilistic model of the QoI. Finally, the accuracy of the surrogate model is verified.
The Bayesian method will be used for the inverse analysis of parameter inference given observed data of a possibly damaged model. The process usually involves evaluating the forward model
numerous times, which is intractable for the complex system considered in the present study, even if the dynamic ROM is used. Thanks to the accurate surrogate probabilistic model of the QoI, the physical model required to be evaluated in Bayesian analysis can be replaced by the surrogate model to achieve several orders of computational efficiency. Nevertheless, generating posterior samples of high dimensional parameters can still be challenging. Thus, a block-update Markov Chain Monte Carlo (MCMC) method is applied to address this issue. By appropriately designing the inverse problem, the location and damage types of the internals can be identified based on dynamic signals on the exterior
surface.
The second goal of the work is to propose a novel multi-fidelity UQ method for dissimilar parameterization models. In multi-fidelity UQ, credible prediction and analyses of high-fidelity (HF) models are obtained by leveraging evaluations of a large number of efficient low-fidelity (LF) models.
The efficacy of the technique relies heavily on the correlation of the HF and LF models. We propose using the basis adaption method in the multi-fidelity technique to independently identify the important directions (or adapted variables) for each model, and the important directions assemble a common lower-dimensional space. Since important directions have concentrated information of the QoI and are aligned for different models, the samples generated on the common lower-dimensional manifold have
enhanced correlations. Thus, the proposed method can increase the performance of the multi-fidelity technique, especially for models with dissimilar parameterization.
The two main goals in the thesis are relevant since both involve stochastic reduction for complex multi- component models.
Webcast: Join Zoom Meeting https://usc.zoom.us/j/95953335264?pwd=SnNEY3JST0hVVFZCdzg2MWpwOG5zUT09 Meeting ID: 959 5333 5264 Passcode: 275995Location: Zoom Meeting
Audiences: Everyone Is Invited
Contact: Evangeline Reyes
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MS CSCI/DSCI Drop-in Academic Advising
Wed, Dec 15, 2021 @ 02:30 PM - 03:30 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
Virtual Academic Advising Drop-in Hours for continuing MS students in CS or Data Science Programs will be available for the month of December. If you have a quick question that doesn't require a 20 minute appointment, please come to our drop in hours. Students may be placed into the waiting room upon arrival.
Zoom access link for all sessions:
ZOOM LINK SENT TO STUDENTS DIRECTLY. CHECK EMAIL FOR LINK.
Wednesday, December 1st --- 10am -- 11am
Wednesday, December 1st --- 2:30pm -- 3:30pm
Wednesday, December 8th --- 10am -- 11am
Wednesday, December 8th --- 2:30pm -- 3:30pm
Wednesday, December 15th --- 10am -- 11am
Wednesday, December 15th --- 2:30pm -- 3:30pm
Location: Online
Audiences: Graduate
Contact: USC Computer Science
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Drop-In Q&A for Prospective Graduate Students
Thu, Dec 16, 2021 @ 09:00 AM - 09:30 AM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
This webinar is designed for those that have specific questions they want answered. Questions will be submitted using the Q&A function and will be answered verbally by a USC Viterbi representative.
WebCast Link: https://usc.zoom.us/webinar/register/WN_a0cbNz_jQieaByFuoP32WQ
Audiences: Everyone Is Invited
Contact: William Schwerin
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Drop-In Q&A for Prospective Graduate Students
Thu, Dec 16, 2021 @ 04:00 PM - 04:30 PM
Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
This webinar is designed for those that have specific questions they want answered. Questions will be submitted using the Q&A function and will be answered verbally by a USC Viterbi representative.
WebCast Link: https://usc.zoom.us/webinar/register/WN_MYe4mGEpQGWUDZnivSKgNw
Audiences: Everyone Is Invited
Contact: William Schwerin
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DEN@Viterbi: How to Apply Virtual Info Session
Thu, Dec 16, 2021 @ 05:00 PM - 06:00 PM
DEN@Viterbi, Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Join USC Viterbi representatives for a step-by-step guide and tips for how to apply for formal admission into a Master's degree or Graduate Certificate program. The session is intended for individuals who wish to pursue a graduate degree program completely online via USC Viterbi's flexible online DEN@Viterbi delivery method.
Attendees will have the opportunity to connect directly with USC Viterbi representatives and ask questions about the admission process throughout the session.
Register Now!WebCast Link: https://uscviterbi.webex.com/uscviterbi/onstage/g.php?MTID=ec1322172ce9fee3f985d36b87e395e3f
Audiences: Everyone Is Invited
Contact: Corporate & Professional Programs