Select a calendar:
Filter March Events by Event Type:
SUNMONTUEWEDTHUFRISAT
Events for March 26, 2024
-
Gas Turbine Engine Accident Investigation GTAI 24-2Tue, Mar 26, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
This specialized accident investigation course is directed to fixed-wing turbojet and turboprop as well as turbine-powered rotary-wing aircraft. The course examines specific turbine engine investigation methods and provides technical information related to material factors and metallurgical failure investigation. This is a fundamental accident investigation course. Individuals with many years of engine investigations may find this course too basic. It is assumed that the attendee has a basic understanding of jet engines.
Location: Century Boulevard Building (CBB) - 960
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AGTAI2
-
Helicopter Accident Investigation HAI 24-2
Tue, Mar 26, 2024 @ 08:00 AM - 04:00 PM
Aviation Safety and Security Program
University Calendar
The course examines the investigation of helicopter accidents to include processes used to determine the cause. The course includes interactive lectures, various case studies, examination of component wreckage in the classroom, and helicopter wreckage examination in the laboratory. The course includes an examination of helicopter rotor systems, controls, performance variables, flight hazards, and material characteristics involved in helicopter operations and accidents. Although Aircraft Accident Investigation (AAI) is not a prerequisite, it is assumed that the attendee has either completed AAI or has some previous experience in aircraft accident investigation.
Location: Century Boulevard Building (CBB) - 920
Audiences: Everyone Is Invited
Contact: Daniel Scalese
Event Link: https://avsafe.usc.edu/wconnect/CourseStatus.awp?&course=24AHAI2
-
CS Colloquium: Xiang Anthony Chen - Catalyzing AI Advances with Human-Centered Interactive Systems
Tue, Mar 26, 2024 @ 10:00 AM - 11:00 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Xiang Anthony Chen, UCLA
Talk Title: Catalyzing AI Advances with Human-Centered Interactive Systems
Abstract: Despite the unprecedented advances in AI, there has always been a gap between how well an AI model performs and how such performance can serve humanity. In this seminar, I will describe my past work to close this gap. Specifically, I develop human-centered interactive systems that catalyze advances in AI to achieve three levels of objectives: aligning with human values, assimilating human intents, and augmenting human abilities. Further, I will discuss my ongoing and future research, focused on AI for scientific discovery, AI with Theory of Mind, and AI-mediated human communication. This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Xiang ‘Anthony' Chen is an Assistant Professor in UCLA's Department of Electrical & Computer Engineering. He received a Ph.D. in the School of Computer Science at Carnegie Mellon University. Anthony's area of expertise is Human-Computer Interaction (HCI). His research employs human-centered design methods to build systems that catalyze advances in AI to better serve humanity, supported by NSF CAREER Award, ONR YIP Award, Google Research Scholar Award, Intel Rising Star Award, Hellman Fellowship, NSF CRII Award, and Adobe Ph.D. Fellowship. Anthony’s work has resulted in 55+ publications with three best paper awards and three honorable mentions in top-tier HCI conferences.
Host: Heather Culbertson
Location: Olin Hall of Engineering (OHE) - 136
Audiences: Everyone Is Invited
Contact: CS Faculty Affairs
-
DREAM Industry Mentorship speaker series- Nick Daze
Tue, Mar 26, 2024 @ 11:00 AM - 12:00 PM
USC Viterbi School of Engineering
University Calendar
DREAM (Direct Response to Engineers Aspirations from Mentors) connects students with experienced industry professionals from a variety of tech and destination companies who help them create a vision for their futures, align their careers around purpose, and build character in the context of growth, reinvention, and constant change. Industry mentors discuss how professional challenges present opportunities for character and leadership development. This event features Nick Daze on his journey as an entrepreneur and CEO at Heirloom, a startup building the future of self-sovereign identity on the blockchain. Co-sponsored with Annenberg School of Communication.
Location: Michelson Center for Convergent Bioscience (MCB) - 102
Audiences: Everyone Is Invited
Contact: Elisabeth Arnold Weiss
Event Link: https://cglink.me/2nB/r395856
-
Where are the Jobs? Uncovering the Hidden Job Market
Tue, Mar 26, 2024 @ 12:00 PM - 01:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
THIS EVENT WILL BE HOSTED HYBRID: IN-PERSON & ONLINE SIMULTANEOUSLY
Zoom link: https://usc.zoom.us/meeting/register/tJArcOutrDkoHtwd36V2fdNrxXPcWfsMmnSl
Increase your career and internship knowledge on networking by attending this professional development Q&A moderated by Viterbi Career Connections staff. For more information about all workshops, please visit viterbicareers.usc.edu/workshops.
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: All Viterbi
Contact: RTH 218 Viterbi Career Connections
Event Link: https://usc.zoom.us/meeting/register/tJArcOutrDkoHtwd36V2fdNrxXPcWfsMmnSl
-
Lockheed Martin Office Hours
Tue, Mar 26, 2024 @ 12:00 PM - 04:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Lockheed Martin Virtual Office Hours
Sign up for a 15-minute virtual meeting with Lockheed Martin recruiting Margaret Paulin to discuss career questions, application tips, or recruitment-specific topics about Lockheed Martin!
These virtual office hours will be hosted on Teams on March 26th from 12-4 pm.
Go to Viterbi Career Gateway > Events for event details and to signup
Please only sign up for a single meeting time slot.
Use your USC email.
A link to the virtual meeting will be emailed to you 24 hours before the event.
Location: Virtual
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
-
CAIS Webinar: Dr. Jessica Ridgway (University of Chicago) - Predictive Analytics for Engagement in HIV Care
Tue, Mar 26, 2024 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Dr. Jessica Ridgway, University of Chicago
Talk Title: Predictive Analytics for Engagement in HIV Care
Abstract: Engagement in care is essential for the health of people with HIV, but only half of people with HIV in the U.S. receive regular medical care. Dr. Ridgway will discuss her research utilizing machine learning models based on electronic medical record data to predict engagement in care among people with HIV. She has developed machine learning models using structured data as well as natural language processing of unstructured clinical notes. She will discuss challenges and pitfalls in utilizing electronic medical record data for HIV-related predictive modeling, as well as implications for implementation in clinical practice.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Jessica Ridgway, MD, MS, is an Associate Professor of Medicine in the Section of Infectious Diseases and Global Health and Director of Medical Informatics at the University of Chicago. She is Director of Predictive Analytics for the Chicago Center for HIV Elimination. Her research focuses on utilizing large electronic medical record databases to understand HIV epidemiology across the continuum of care and implementation of clinical informatics interventions to improve HIV care and prevention.
Host: USC Center for Artificial Intelligence in Society (CAIS)
More Info: https://usc.zoom.us/webinar/register/WN_gEn8OHXBQnmpYiWc9hJimw
Location: Zoom only - https://usc.zoom.us/webinar/register/WN_gEn8OHXBQnmpYiWc9hJimw
Audiences: Everyone Is Invited
Contact: CS Events
Event Link: https://usc.zoom.us/webinar/register/WN_gEn8OHXBQnmpYiWc9hJimw
-
ECE-EP Seminar - Zaijun Chen, Tuesday, March 26th at 2pm in EEB 248
Tue, Mar 26, 2024 @ 02:00 PM - 03:30 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Zaijun Chen, University of Southern California
Talk Title: Large-Scale Photonic Circuits for AI Computing and Metrology
Series: ECE-EP Seminar
Abstract: The rapid expansion of artificial intelligence (AI), internet of things (IoT) and 5G/6G mobile networks is creating an urgent need for energy-efficient, scalable computing hardware. Optical computing is emerging to enable new computing paradigms with high optical bandwidth, parallel processing, and low-loss data movement. However, the scalability of existing optical accelerators is limited by the electro-optic conversion efficiency, large photonic device footprints, lack of optical nonlinearity, etc. In this talk, I will present our computing approaches to overcomes these bottlenecks with hyperdimensional multiplexing. Our experimental results have realized large-scale AI processing in models with half a million parameters, a full-system energy efficiency at few femtojoule per operation (fJ/OP) and computing density of 6 TOP/(mm2·s). This computing efficiency and density outperform the state-of-the-art digital processors for the first time, with 100 folds improvement. In the last part, I will cover some interferometry techniques based on laser frequency combs for broadband, high-speed precision sensing and metrology at quantum-limited sensitivity.
Biography: Zaijun Chen is a research assistant professor at the Ming Hsieh Department of Electrical and Computer Engineering at USC. He accomplished his Ph.D. degree (summa cum laude) in Prof. Theodor W. Haensch's (Nobel laureate 2005) group at Max-Planck Institute of Quantum Optics (MPQ) in 2019, and postdoc with Prof. Dirk Englund at MIT. He is a recipient of 2023 SPIE best paper award for Machine learning and Artificial intelligence, 2023 Sony faculty Innovation Award, 2023 Optica Foundation Challenge Award, and leading PI in a 2023 DARPA project (NaPSAC). He is an early career editor of Advanced Photonics.
Host: ECE-Electrophysics
More Information: Zaijun Chen Seminar Announcement.pdf
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Marilyn Poplawski
-
PhD Dissertation Defense - Aniruddh Puranic
Tue, Mar 26, 2024 @ 03:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Dissertation Defense - Aniruddh Puranic Committee: Jyotirmoy V. Deshmukh (Chair), Gaurav Sukhatme, Stefanos Nikolaidis, and Stephen Tu Title: Sample-Efficient and Robust Neurosymbolic Learning from Demonstrations Abstract: Learning-from-demonstrations (LfD) is a popular paradigm to obtain effective robot control policies for complex tasks via reinforcement learning (RL) without the need to explicitly design reward functions. However, it is susceptible to imperfections in demonstrations and also raises concerns of safety and interpretability in the learned control policies. To address these issues, this thesis develops a neurosymbolic learning framework which is a hybrid method that integrates neural network-based learning with symbolic (e.g., rule, logic, graph) reasoning to leverage the strengths of both approaches. Specifically, this framework uses Signal Temporal Logic (STL) to express high-level robotic tasks and its quantitative semantics to evaluate and rank the quality of demonstrations. Temporal logic-based specifications allow us to create non-Markovian rewards and are also capable of defining interesting causal dependencies between tasks such as sequential task specifications. This dissertation presents the LfD-STL framework that learns from even suboptimal/imperfect demonstrations and STL specifications to infer reward functions; these reward functions can then be used by reinforcement learning algorithms to obtain control policies. Experimental evaluations on several diverse set of environments show that the additional information in the form of formally specified task objectives allows the framework to outperform prior state-of-the-art LfD methods. Many real-world robotic tasks consist of multiple objectives (specifications), some of which may be inherently competitive, thus prompting the need for deliberate trade-offs. This dissertation then further extends the LfD-STL framework by a developing metric - performance graph - which is a directed graph that utilizes the quality of demonstrations to provide intuitive explanations about the performance and trade-offs of demonstrated behaviors. This performance graph also offers concise insights into the learning process of the RL agent, thereby enhancing interpretability, as corroborated by a user study. Finally, the thesis discusses how the performance graphs can be used as an optimization objective to guide RL agents to potentially learn policies that perform better than the (imperfect) demonstrators via apprenticeship learning (AL). The theoretical machinery developed for the AL-STL framework examines the guarantees on safety and performance of RL agents. https://usc.zoom.us/j/98964159897?pwd=a2ljaGNEOGcvMkl1WU9yZENPc0M1dz09
Location: Ronald Tutor Hall of Engineering (RTH) - 306
Audiences: Everyone Is Invited
Contact: Aniruddh Puranic
Event Link: https://usc.zoom.us/j/98964159897?pwd=a2ljaGNEOGcvMkl1WU9yZENPc0M1dz09
-
Epstein Institute, ISE 651 Seminar Class
Tue, Mar 26, 2024 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Xuan Song, Assistant Professor, James A. Chisman Faculty Fellow, Department of Industrial & Systems Engr, Iowa Technology Institute
Talk Title: Toward Mild Additive Manufacturing for Extremes
Host: Prof. Yong Chen
More Information: March 26, 2024.pdf
Location: Social Sciences Building (SOS) - SOS Building, B2
Audiences: Everyone Is Invited
Contact: Grace Owh
