Logo: University of Southern California

Events Calendar



Select a calendar:



Filter March Events by Event Type:



Events for the 2nd week of March

  • Repeating EventMeet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Mon, Mar 04, 2019

    Viterbi School of Engineering Undergraduate Admission

    Workshops & Infosessions


    This half day program is designed for prospective freshmen (HS juniors and younger) and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.

    Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m.

    Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!

    RSVP

    Location: Ronald Tutor Campus Center (TCC) - USC Admission Office

    Audiences: Everyone Is Invited

    View All Dates

    Posted By: Viterbi Admission

    OutlookiCal
  • CS Colloquium: Rahul Chatterjee (Cornell University) - Empiricism-Informed Secure System Design: From Improving Passwords to Helping Domestic Violence Victims

    Mon, Mar 04, 2019 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Rahul Chatterjee, Cornell University

    Talk Title: Empiricism-Informed Secure System Design: From Improving Passwords to Helping Domestic Violence Victims

    Series: CS Colloquium

    Abstract: Security often fails in practice due to a lack of understanding of the nuances in real-world systems. For example, users choose weak passwords to deal with the several usability issues with passwords, which in turn degrades the security of passwords. I will talk about how we can build better security mechanisms by combining methodical empiricism with analytical frameworks. First, in the context of passwords, I will show how to improve the usability of passwords by allowing users to log in with typos in their passwords. I will detail in the talk how to do so without giving attackers any additional advantage to impersonate a user.

    In the second part of my talk, I will talk about my recent research direction on how traditional authentication mechanisms fail to properly model digital attacks by domestic abusers, and therefore are ineffective for victims. As a result, abusers can spy on, stalk, or harass victims using seemingly innocuous apps and technologies. I will finish with some recent progress that I have made in helping victims of tech abuse, and provide some future research directions.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Rahul Chatterjee is a Ph.D. candidate at Cornell University, working on computer security. Prior to joining Cornell, Rahul received his masters from the University of Wisconsin-Madison and bachelors from the Indian Institute of Technology (IIT), Kharagpur. Rahul's research focuses on user authentication, in particular passwords and biometrics. Lately, he is also conducting research on how to help stop technology abuse in the context of domestic violence. His co-authored papers have been covered by several media outlets, including The New York Times, and the MIT Tech Review. His work on password typos was recognized with the distinguished student paper award at IEEE S&P (2016).

    Host: Muhammad Naveed

    Location: Ronald Tutor Hall of Engineering (RTH) - 115

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

    OutlookiCal
  • Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series

    Mon, Mar 04, 2019 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Muriel Médard, MIT

    Talk Title: Guessing Random Additive Noise Decoding (Grand)

    Abstract: We introduce a new algorithm for Maximum Likelihood (ML) decoding based on guessing noise. The algorithm is based on the principle that the receiver rank orders noise sequences from most likely to least likely. Subtracting noise from the received signal in that order, the first instance that results in an element of the code-book is the ML decoding. For common additive noise channels, we establish that the algorithm is capacity achieving for uniformly selected code-books, providing an intuitive alternate approach to the channel coding theorem. When the code-book rate is less than capacity, we identify exact asymptotic error exponents as the block-length becomes large. We illustrate the practical usefulness of our approach in terms of speeding up decoding for existing codes.

    Joint work with Ken Duffy, Kishori Konwar, Jiange Li, Prakash Narayana Moorthy, Amit Solomon.

    Biography: Muriel Médard is the Cecil H. Green Professor in the Electrical Engineering and Computer Science (EECS) Department at MIT and leads the Network Coding and Reliable Communications Group at the Research Laboratory for Electronics at MIT. She has co-founded three companies to commercialize network coding, CodeOn, Steinwurf and Chocolate Cloud. She has served as editor for many publications of the Institute of Electrical and Electronics Engineers (IEEE), of which she was elected Fellow, and she has served as Editor in Chief of the IEEE Journal on Selected Areas in Communications. She was President of the IEEE Information Theory Society in 2012, and served on its board of governors for eleven years. She has served as technical program committee co-chair of many of the major conferences in information theory, communications and networking. She received the 2009 IEEE Communication Society and Information Theory Society Joint Paper Award, the 2009 William R. Bennett Prize in the Field of Communications Networking, the 2002 IEEE Leon K. Kirchmayer Prize Paper Award, the 2018 ACM SIGCOMM Test of Time Paper Award and several conference paper awards. She was co-winner of the MIT 2004 Harold E. Edgerton Faculty Achievement Award, received the 2013 EECS Graduate Student Association Mentor Award and served as Housemaster for seven years. In 2007 she was named a Gilbreth Lecturer by the U.S. National Academy of Engineering. She received the 2016 IEEE Vehicular Technology James Evans Avant Garde Award, the 2017 Aaron Wyner Distinguished Service Award from the IEEE Information Theory Society and the 2017 IEEE Communications Society Edwin Howard Armstrong Achievement Award. She is a member of the National Academy of Inventors.

    Host: Prof. Urbashi Mitra, ubli@usc.edu

    More Info: http://csc.usc.edu/seminars/2019Spring/medard.html

    More Information: 19.03.04 Muriel Medard CSCUSC Seminar.pdf

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Posted By: Brienne Moore

    OutlookiCal
  • Resume Lab - Bring your Laptop!

    Mon, Mar 04, 2019 @ 04:30 PM - 05:30 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Labs are an activity where you can work on your resume in the presence of a career advisor to get tips on the spot.

    Bring your Laptop!

    For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: All Viterbi Students

    Posted By: RTH 218 Viterbi Career Connections

    OutlookiCal
  • CS Colloquium: Tatsunori Hashimoto (Stanford University) - Beyond the average case: machine learning for atypical examples

    Tue, Mar 05, 2019 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Tatsunori Hashimoto, Stanford University

    Talk Title: Beyond the average case: machine learning for atypical examples

    Series: CS Colloquium

    Abstract: Although machine learning systems have improved dramatically over the last decade, it has been widely observed that even the best systems fail on atypical examples. For example, prediction models such as image classifiers have low accuracy on images from minority cultures, and generative models such as dialogue systems are often incapable of generating diverse, atypical responses. In this talk, I will discuss two domains where high performance on typical examples is insufficient.

    The first is learning prediction models that perform well on minority groups, such as non-native English speakers using a speech recognition system. We demonstrate that models with low average loss can still assign high losses to minority groups, and this gap can amplify over time as minority users that suffer high losses stop using the model. We develop an approach using distributionally robust optimization that learns models that perform well over all groups and mitigate the feedback loop.

    The second domain is learning natural language generation (NLG) systems, such as a dialogue system. It has been frequently observed that existing NLG systems which produce high-quality samples rely heavily on typical responses such as "I don't know" and fail to generate the full diversity of atypical but valid human responses.
    We carefully quantify this problem through a new evaluation metric based on the optimal classification error between human- and model-generated text and propose a new, edit-based generative model of text whose outputs are both diverse and high-quality.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Tatsunori (Tatsu) Hashimoto is a 3rd year post-doc in the Statistics and Computer Science departments at Stanford, supervised by Professors Percy Liang and John Duchi. He holds a Ph.D from MIT where he studied random walks and computational biology under Professors Tommi Jaakkola and David Gifford, and a B.S. from Harvard in Statistics and Math. His work has been recognized in NeurIPS 2018 (Oral), ICML 2018 (Best paper runner-up), and NeurIPS 2014 Workshop on Networks (Best student paper).

    Host: Yan Liu

    Location: Olin Hall of Engineering (OHE) - 132

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

    OutlookiCal
  • Internship/Job Search Open Forum

    Tue, Mar 05, 2019 @ 01:00 PM - 02:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Increase your career and internship knowledge on the job/internship search by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners.

    For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: All Viterbi Students

    Posted By: RTH 218 Viterbi Career Connections

    OutlookiCal
  • Civil and Environmental Engineering Seminar

    Tue, Mar 05, 2019 @ 03:00 PM - 04:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Saahastaranshu R. Bhardwaj, PhD, Purdue University

    Talk Title: Multi-Hazard Resilience: The Need of the Hour

    Abstract: Climate change has resulted in novel hazard patterns, with increasing severity and probability of multi-hazard scenarios. The field of structural engineering requires innovative approaches to address the challenges posed by climate change (e.g., multi-hazards), and to explore new frontiers in science and engineering (e.g., space habitat systems). There is a push for developing resilient and sustainable structural systems to cater these needs of science and industry.

    This seminar describes recent large-scale experimental and numerical investigations to evaluate the multi-hazard response of steel-plate composite and reinforced concrete walls. The investigations involved subjecting the specimens to combined loading scenarios (e.g., seismic and thermal loading, multi-axial loading, gravity and fire loading). A particularly challenging aspect of the experiments involving multi-hazard loads is the design and construction of test set-ups. The seminar presents the design of experiments and summarizes the observations. The analysis and design tools developed to consider interaction of multi-hazard loading are also discussed.

    A resilient community comprises of resilient assets. The multi-hazard evaluation capabilities can be employed to develop innovative and resilient structures for habitation on earth and elsewhere! The talk includes a discussion of potential research areas that warrant innovative structural systems and / or multi-hazard evaluation.


    Host: Sonny Astani Department of Civil and Environmental Engineering

    Location: Ray R. Irani Hall (RRI) - 101

    Audiences: Everyone Is Invited

    Posted By: Salina Palacios

    OutlookiCal
  • Epstein Institute Seminar - ISE 651

    Tue, Mar 05, 2019 @ 03:30 PM - 04:50 PM

    Daniel J. Epstein Department of Industrial and Systems Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Stan Uryasev, Professor, University of Florida

    Talk Title: How to Supplement Risk Regulations to Avoid Industrial Catastrophes

    Host: Dr. Suvrajeet Sen

    More Information: March 5, 2019.pdf

    Location: Ethel Percy Andrus Gerontology Center (GER) - 206

    Audiences: Everyone Is Invited

    Posted By: Grace Owh

    OutlookiCal
  • Civil and Environmental Engineering Alumni & Industry Spotlight

    Tue, Mar 05, 2019 @ 07:00 PM - 08:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    The Viterbi Industry & Alumni Spotlight is a great opportunity for you to connect with USC alumni and industry professionals that have been in your shoes. They will share their experiences on how they got to where they are in their career and offer words of wisdom along the way. This is an undergraduate only event.

    Location: Seeley G. Mudd Building (SGM) - 101

    Audiences: Undergrad

    Posted By: RTH 218 Viterbi Career Connections

    OutlookiCal
  • Repeating EventMeet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Wed, Mar 06, 2019

    Viterbi School of Engineering Undergraduate Admission

    Workshops & Infosessions


    This half day program is designed for prospective freshmen (HS juniors and younger) and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.

    Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m.

    Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!

    RSVP

    Location: Ronald Tutor Campus Center (TCC) - USC Admission Office

    Audiences: Everyone Is Invited

    View All Dates

    Posted By: Viterbi Admission

    OutlookiCal
  • Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar Series

    Wed, Mar 06, 2019 @ 03:00 AM - 04:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dorsa Sadigh, Computer Science and Electrical Engineering at Stanford University

    Talk Title: Interactive Autonomy: A human-centered approach to learning and control

    Series: Center for Cyber-Physical Systems and Internet of Things

    Abstract: Today's society is rapidly advancing towards robotics systems that interact and collaborate with humans, e.g., semi-autonomous vehicles interacting with drivers and pedestrians, medical robots used in collaboration with doctors, or service robots interacting with their users in smart homes. Formalizing interaction is a crucial component in seamless collaboration and coordination between humans and today's robotics systems. In this talk, I will first discuss our recent results on efficient and active learning of predictive models of humans' preferences by eliciting comparisons from humans. I will then formalize interactive autonomy, and our approach in design of learning and control algorithms that influence humans in interactive settings. I will further analyze the global implications of human-robot interaction and its societal impacts in the setting of autonomous driving.

    Biography: Dorsa Sadigh is an assistant professor in Computer Science and Electrical Engineering at Stanford University. Her research interests lie in the intersection of robotics, learning and control theory, and algorithmic human-robot interaction. Specifically, she works on developing efficient algorithms for autonomous systems that safely and reliably interact with people. Dorsa has received her doctoral degree in Electrical Engineering and Computer Sciences (EECS) at UC Berkeley in 2017, and has received her bachelor's degree in EECS at UC Berkeley in 2012. She is awarded the Amazon Faculty Research Award, the NSF and NDSEG graduate research fellowships as well as the Leon O. Chua departmental award departmental award.

    Host: Paul Bogdan

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Posted By: Talyia White

    OutlookiCal
  • CS Colloquium: Behnam Neyshabur (New York University) - Why Do Neural Networks Learn?

    Wed, Mar 06, 2019 @ 09:00 AM - 10:00 AM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Behnam Neyshabur, New York University

    Talk Title: Why Do Neural Networks Learn?

    Series: CS Colloquium

    Abstract: Neural networks used in practice have millions of parameters and yet they generalize well even when they are trained on small datasets. While there exists networks with zero training error and a large test error, the optimization algorithms used in practice magically find the networks that generalizes well to test data. How can we characterize such networks? What are the properties of networks that generalize well? How do these properties ensure generalization?
    In this talk, we will develop techniques to understand generalization in neural networks. Towards the end, I will show how this understanding can help us design architectures and optimization algorithms with better generalization performance.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.

    Biography: Behnam Neyshabur is a postdoctoral researcher in Yann LeCun's group at New York University. Before that, he was a member of Theoretical Machine Learning program lead by Sanjeev Arora at the Institute for Advanced Study (IAS) in Princeton. In summer 2017, he received a PhD in computer science at TTI-Chicago where Nati Srebro was his advisor. He is interested in machine learning and optimization and his primary research is on optimization and generalization in deep learning.

    Host: Haipeng Luo

    Location: Ronald Tutor Hall of Engineering (RTH) - 109

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

    OutlookiCal
  • CS Colloquium:Sida Wang (Princeton University) - Learning Adaptive Language Interfaces Through Interaction

    Wed, Mar 06, 2019 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Sida Wang, Princeton University

    Talk Title: Learning Adaptive Language Interfaces Through Interaction

    Series: CS Colloquium

    Abstract: The interactivity and adaptivity of natural language have the potential to allow people to better communicate with increasingly AI-driven computer systems. However, current natural language interfaces are mostly static and fall short of their potential. In this talk, I will cover two systems that can quickly learn from interactions, adapt to users, and simultaneously give feedback so that users can adapt to the system. The first system learns from scratch from users in real time. The second starts with a programming language and then learns to naturalize the programming language by interacting with users. Finally, I will present how these ideas can be combined to build a natural language interface for data visualization and discuss my work on modeling interactive language learning more rigorously.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.

    Biography: Sida Wang is a research instructor at Princeton University and Institute for Advanced Study working in the areas of natural language processing and machine learning. He holds a Ph.D. in computer science from Stanford University and a B.A.Sc. from the University of Toronto. He received an outstanding paper award at ACL 2016 and the NSERC Postgraduate Scholarship.

    Host: Joseph Lim

    Location: Ronald Tutor Hall of Engineering (RTH) - 115

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

    OutlookiCal
  • Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar Series

    Wed, Mar 06, 2019 @ 11:30 AM - 12:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Vijay G. Subramanian, Electrical Engineering and Computer Science, University of Michigan

    Talk Title: One If By Land and Two If By Sea: A Glimpse into the Value of Information in Strategic Interactions

    Series: Center for Cyber-Physical Systems and Internet of Things

    Abstract: This work studies sequential social learning (also known as Bayesian observational learning), and how private communication can enable agents to avoid herding to the wrong action/state. Starting from the seminal BHW (Bikhchandani, Hirshleifer, and Welch, 1992) model where asymptotic learning does not occur, we allow agents to ask private and finite questions to a bounded subset of their predecessors. While retaining the publicly observed history of the agents and their Bayes rationality from the BHW model, we further assume that both the ability to ask questions and the questions themselves are common knowledge. Then interpreting asking questions as partitioning information sets, we study whether asymptotic learning can be achieved with finite capacity questions. Restricting our attention to the network where every agent is only allowed to query her immediate predecessor, an explicit construction shows that a 1-bit question from each agent is enough to enable asymptotic learning.

    This is joint work with Shih-Tang Su and Grant Schoenebeck at the University of Michigan. Details of the work can be found at https://arxiv.org/abs/1811.00226


    Biography: I am an Associate Professor in the EECS Department at the University of Michigan. My main research interests are in stochastic modeling, communications, information theory, and applied mathematics. A large portion of my past work has been on probabilistic analysis of communication networks, especially analysis of scheduling and routing algorithms. In the past, I have also done some work with applications in immunology and coding of stochastic processes. My current research interests are on game-theoretic and economic modeling of socio-technological systems and networks, and the analysis of associated stochastic processes.

    Host: Ashutosh Nayyar

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Posted By: Talyia White

    OutlookiCal
  • Astani Civil and Environmental Engineering Seminar

    Wed, Mar 06, 2019 @ 11:30 AM - 12:30 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Lorenzo Valdevit, Ph.D., University of California, Irvine

    Talk Title: Deformation and Damage Mechanisms in Ceramic Nano-Architected Metamaterials

    Abstract: See attached

    Host: Dr. Qiming Wang

    More Information: Seminar Annoucement_Lorenzo Valdevit.docx

    Location: Ray R. Irani Hall (RRI) - 101

    Audiences: Everyone Is Invited

    Posted By: Evangeline Reyes

    OutlookiCal
  • Internship/Job Search Open Forum

    Wed, Mar 06, 2019 @ 01:00 PM - 02:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Increase your career and internship knowledge on the job/internship search by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners.

    For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: All Viterbi Students

    Posted By: RTH 218 Viterbi Career Connections

    OutlookiCal
  • The Role of Advanced Experimental and Numerical Simulations in the Management of Deteriorated Infrastructure

    Wed, Mar 06, 2019 @ 03:00 PM - 04:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Hussam Mahmoud, PhD, Colorado State University

    Talk Title: The Role of Advanced Experimental and Numerical Simulations in the Management of Deteriorated Infrastructure

    Host: Civil and Environmental Engineering

    Location: Ray R. Irani Hall (RRI) - 101

    Audiences: Everyone Is Invited

    Posted By: Salina Palacios

    OutlookiCal
  • AME Seminar

    Wed, Mar 06, 2019 @ 03:30 PM - 04:30 PM

    Aerospace and Mechanical Engineering

    Conferences, Lectures, & Seminars


    Speaker: Krishna Garikipati, University of Michigan

    Talk Title: Mechano-Chemical Phase Transformations: Computational Framework, Machine Learning Studies and Graph Theoretic Analysis

    Abstract: Phase transformations in a wide range of materials-”for energy, electronics, structural and other applications-”are driven by mechanics in interaction with chemistry. We have developed a general theoretical and computational framework for large scale simulations of these mechano-chemical phenomena. I will begin by presenting our recent work in this sphere, while highlighting some of its more insightful results. In addition to being a platform for investigating mechanically driven phenomena in materials physics, this work is a foundation to explore the potential of recent advances in data-driven modeling. Of interest to us are machine learning advances that may enhance our approaches to solve computational materials physics problems. I will outline the first of several recent studies that we have launched in this spirit. Such combinations of classical high-performance scientific computing and modern data-driven modeling now allow us to access large numbers of states of physical systems. They also motivate the study of mathematical structures for representation, exploration and analysis of systems by using these collections of states. With this perspective, I will offer a view of graph theory that places it in nearly perfect correspondence with properties of stationary and dynamical systems. This has opened up new insights to our earlier, large-scale computational investigations of mechano-chemically phase transforming materials systems. This treatment has potential for eventual decision-making for physical systems that builds on high-fidelity computations.

    Krishna Garikipati is a computational scientist whose work draws upon nonlinear physics, applied mathematics and numerical methods. A very recent interest of his is the development of methods for data-driven computational science. He has worked for quite a few years in mathematical biology, biophysics and materials physics. Some specific problems he has been thinking about recently are: (1) mathematical models of patterning and morphogenesis in developmental biology, (2) mathematical and physical modeling of tumor growth, and (3) mechano-chemically driven phenomena in materials, such as phase transformations and stress-influenced mass transport.

    Host: AME Department

    More Info: https://ame.usc.edu/seminars/

    Location: Seaver Science Library (SSL) - 150

    Audiences: Everyone Is Invited

    Posted By: Tessa Yao

    OutlookiCal
  • CAIS Seminar: Lindsay Young (University of Chicago) - Social Network Analysis and Artificial Intelligence: Methodological Partners in the Study of HIV Prevention and Risk Online

    Wed, Mar 06, 2019 @ 04:00 PM - 05:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Dr. Lindsay Young, University of Chicago

    Talk Title: Social Network Analysis and Artificial Intelligence: Methodological Partners in the Study of HIV Prevention and Risk Online

    Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series

    Abstract: As transmitters of information and progenitors of behavioral norms, social networks are critical mechanisms of HIV prevention and risk in impacted populations like men who have sex with men (MSM), people who inject drugs (PWID), and homeless youth. Today, widespread use of online social networking technologies (e.g., Facebook, Instagram, Twitter) yield unprecedented amounts of relational and communication data far richer than anything previously collected in offline (physical) network settings. However, parsing these complex data into tractable insights and solutions requires an innovative and flexible computational toolkit that extends beyond traditional approaches. In this talk, Dr. Young will discuss her ongoing efforts to unpack how HIV prevention and risk manifest in the Facebook networks of young MSM using a hybrid of computational methods that include social and semantic network analysis and machine learning approaches for textual analysis and predictive modeling. She will conclude with a discussion of the practical implications of this work and outstanding challenges that require further exploration.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Dr. Lindsay Young is a NIH Pathway to Independence Award Postdoctoral Fellow at the University of Chicago Department of Medicine and Chicago Center for HIV Elimination (CCHE). Trained as a social scientist and network methodologist, she now applies those perspectives to understand the social and communicative contexts of HIV risk and prevention among young sexual minorities and other vulnerable populations. She is particularly interested in how online social network data can be leveraged for behavioral research and interventions.


    Host: Milind Tambe

    Location: James H. Zumberge Hall Of Science (ZHS) - 252

    Audiences: Everyone Is Invited

    Posted By: Computer Science Department

    OutlookiCal
  • Trojan Talk with Disney Imagineering

    Wed, Mar 06, 2019 @ 05:30 PM - 07:00 PM

    Viterbi School of Engineering Career Connections

    University Calendar


    Hear from Viterbi ISE alumnus Justin Newton about his career path, how he landed a job working at the ultimate dream company, and what it takes to be a Disney Imagineer!

    Justin Newton is an executive at Walt Disney Imagineering. He is responsible for process improvement, risk management, talent development and supporting Walt Disney Imagineering projects.

    Location: Seeley G. Mudd Building (SGM) - 101

    Audiences: Everyone Is Invited

    Posted By: RTH 218 Viterbi Career Connections

    OutlookiCal
  • Intro to Deep Learning with AAAI and GRIDS

    Wed, Mar 06, 2019 @ 07:30 PM - 09:00 PM

    Viterbi School of Engineering Student Organizations

    University Calendar


    Join AAAI as we collaborate with USC's GRIDS (Graduates Rising in Informatics and Data Science) to bring you a presentation on Intro to Deep Learning.

    Deep learning has been the focus of much attention (and hype) in recent years: it has not only revolutionized consumer technologies ranging from image understanding to language processing to speech recognition, but has also found its way into domains like genomics, robotics, and particle physics. In this talk, we take a grounded look at what deep learning really is, what it is good for, how it is being used all around you, what you need to know to get started with it, and how you can do so on a budget.

    RSVP Here

    Location: Seeley G. Mudd Building (SGM) - 124

    Audiences: Everyone Is Invited

    Posted By: USC AAAI

    OutlookiCal
  • CS Colloquium: Eunsol Choi (University of Washington) - Learning to Understand Entities In Text

    Thu, Mar 07, 2019 @ 09:30 AM - 10:30 AM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Eunsol Choi, University of Washington

    Talk Title: Learning to Understand Entities In Text

    Series: CS Colloquium

    Abstract: Real world entities such as people, organizations and countries play a critical role in text. Reading offers rich explicit and implicit information about these entities, such as the categories they belong to, relationships they have with other entities, and events they participate in. In this talk, we introduce approaches to infer implied information about entities, and to automatically query such information in an interactive setting. We expand the scope of information that can be learned from text for a range of tasks, including sentiment extraction, entity typing and question answering. To this end, we introduce new ideas for how to find effective training data, including crowdsourcing and large-scale naturally occurring weak supervision data. We also describe new computational models, that represent rich social and conversation contexts to tackle these tasks. Together, these advances significantly expand the scope of information that can be incorporated into the next generation of machine reading systems.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.

    Biography: Eunsol Choi is a Ph.D candidate at the Paul G. Allen School of Computer Science at the University of Washington. Her research focuses on natural language processing, specifically applying machine learning to recover semantics from text. She completed a B.A. in Computer Science and Mathematics at Cornell University, and is a recipient of the Facebook fellowship.

    Host: Xiang Ren

    Location: Ronald Tutor Hall of Engineering (RTH) - 109

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

    OutlookiCal
  • CS Colloquium: Chi Jin (UC Berkeley) Machine Learning: Why Do Simple Algorithms Work So Well?

    Thu, Mar 07, 2019 @ 11:00 AM - 12:00 PM

    Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Chi Jin, UC Berkely

    Talk Title: Machine Learning: Why Do Simple Algorithms Work So Well?

    Series: CS Colloquium

    Abstract: While state-of-the-art machine learning models are deep, large-scale, sequential and highly nonconvex, the backbone of modern learning algorithms are simple algorithms such as stochastic gradient descent, or Q-learning (in the case of reinforcement learning tasks). A basic question endures---why do simple algorithms work so well even in these challenging settings?

    This talk focuses on two fundamental problems: (1) in nonconvex optimization, can gradient descent escape saddle points efficiently? (2) in reinforcement learning, is Q-learning sample efficient? We will provide the first line of provably positive answers to both questions. In particular, we will show that simple modifications to these classical algorithms guarantee significantly better properties, which explains the underlying mechanisms behind their favorable performance in practice.

    This lecture satisfies requirements for CSCI 591: Research Colloquium

    Biography: Chi Jin is a Ph.D. candidate in Computer Science at UC Berkeley, advised by Michael I. Jordan. He received a B.S. in Physics from Peking University. His research interests lie in machine learning, statistics, and optimization, with his PhD work primarily focused on nonconvex optimization and reinforcement learning.

    Host: Haipeng Luo

    Location: Olin Hall of Engineering (OHE) - 132

    Audiences: Everyone Is Invited

    Posted By: Assistant to CS chair

    OutlookiCal
  • Individual Grammar Tutorials

    Thu, Mar 07, 2019 @ 11:00 AM - 12:00 PM

    Viterbi School of Engineering Student Affairs

    Workshops & Infosessions


    Viterbi graduate and undergraduate students are invited to sign up for individual grammar assistance from professors at the Engineering Writing Program. Sign up for one-on-one individual sessions here: http://bit.ly/grammaratUSC

    Questions? Email helenhch@usc.edu

    Location: Olin Hall of Engineering (OHE) - 106

    Audiences: Graduate and Undergraduate Students

    Posted By: Helen Choi

    OutlookiCal
  • NL Seminar: Separating the Sheep from the Goats: On Recognizing the Literal and Figurative Usages of Idioms

    Thu, Mar 07, 2019 @ 11:00 AM - 12:00 PM

    Information Sciences Institute

    Conferences, Lectures, & Seminars


    Speaker: Rebecca Hwa, University of Pitt

    Talk Title: Separating the Sheep from the Goats: On Recognizing the Literal and Figurative Usages of Idioms

    Series: Natural Language Seminar

    Abstract: Typically, we think of idioms as colorful expressions whose literal interpretations don't match their underlying meaning. However, many idiomatic expressions can be used either figuratively or literally, depending on their contexts. In this talk, we survey both supervised and unsupervised methods for training a classifier to automatically distinguish usages of idiomatic expressions. We will conclude with a discussion about some potential applications.

    Biography: Rebecca Hwa is an Associate Professor in the Department of Computer Science at the University of Pittsburgh. Her recent research focuses on understanding persuasion from a computational linguistics perspective. Some of her recent projects include: modeling student behaviors in revising argumentative essays, identifying symbolisms in visual rhetorics, and understanding idiomatic expressions. Dr Hwa is a recipient of the NSF CAREER Award. Her work has also been supported by NIH and DARPA.

    Host: Xusen Yin

    More Info: https://nlg.isi.edu/nl-seminar/

    Location: Information Science Institute (ISI) - Conf Room #689

    Audiences: Everyone Is Invited

    Posted By: Peter Zamar

    OutlookiCal
  • ECE Seminar: Information and Incentives in Learning and Decision Making on Networks

    Thu, Mar 07, 2019 @ 11:15 AM - 12:15 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Parinaz Naghizadeh, Postdoctoral Research Associate/ Purdue University and Princeton University Edge Lab

    Talk Title: Information and Incentives in Learning and Decision Making on Networks

    Abstract: Networks play a central role in determining the outcomes of a variety of socio-technological and economic interactions. Examples include investing in security, sharing of congestible resources, and learning by teams of agents, in network environments. In this talk, I aim to analyze the role of information and incentives in distributed learning and decision making in such problems.

    I will first discuss the role of information sharing in a multi-agent (reinforcement) learning problem. We study learning and decision making by agents who have heterogeneous information about their unknown, partially observable environment. We identify two benefits of information sharing between such agents: it facilitates coordination among them, and further enhances the learning rate of both better informed and less informed agents. We show however that these benefits will depend on the communication timing, in that delayed information sharing may be preferred in certain scenarios.

    I will then present a framework for characterizing the effects of the network topology on strategic decision making over networks. Specifically, we establish a connection between the equilibrium outcomes of network games with non-linear (resp. linear) best-response functions, and variational inequality (resp. linear complementarity) problems. Through these connections, we outline conditions for existence, uniqueness, and stability of equilibria in these games, extending several existing results in the literature. We further discuss the effects of the network topology on the design of incentive mechanisms in such settings, with applications in improving cybersecurity.

    Biography: Parinaz Naghizadeh is a postdoctoral research associate in the Department of Electrical and Computer Engineering at Purdue University and Princeton University Edge Lab. She received her Ph.D. in electrical engineering from the University of Michigan in 2016, M.Sc. degrees in electrical engineering and mathematics, both from the University of Michigan, in 2013 and 2014, respectively, and her B.Sc. in electrical engineering from Sharif University of Technology, Iran, in 2010. Her research interests are in network economics, learning theory, game theory, reinforcement learning, and data analytics. She was a recipient of the Barbour Scholarship in 2014, a finalist for the ProQuest Dissertation Award in 2016, and a Rising Stars in EECS in 2017.

    Host: Professor Richard Leahy, leahy@sipi.usc.edu

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132

    Audiences: Everyone Is Invited

    Posted By: Mayumi Thrasher

    OutlookiCal
  • Internship/Job Search Open Forum

    Thu, Mar 07, 2019 @ 04:00 PM - 05:00 PM

    Viterbi School of Engineering Career Connections

    Workshops & Infosessions


    Increase your career and internship knowledge on the job/internship search by attending this professional development Q&A moderated by Viterbi Career Connections staff or Viterbi employer partners.

    For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.

    Location: Ronald Tutor Hall of Engineering (RTH) - 211

    Audiences: All Viterbi Students

    Posted By: RTH 218 Viterbi Career Connections

    OutlookiCal
  • Repeating EventMeet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Fri, Mar 08, 2019

    Viterbi School of Engineering Undergraduate Admission

    Workshops & Infosessions


    This half day program is designed for prospective freshmen (HS juniors and younger) and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.

    Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m.

    Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!

    RSVP

    Location: Ronald Tutor Campus Center (TCC) - USC Admission Office

    Audiences: Everyone Is Invited

    View All Dates

    Posted By: Viterbi Admission

    OutlookiCal
  • Center for Cyber-Physical Systems and Internet of Things and Ming Hsieh Institute Seminar Series

    Fri, Mar 08, 2019 @ 10:00 AM - 11:00 AM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Ziv Bar-Joseph, Carnegie Mellon University

    Talk Title: Distributed Information Processing in Biological and Computational Systems

    Series: Center for Cyber-Physical Systems and Internet of Things

    Abstract: Computer science and biology have enjoyed a long and fruitful relationship for decades. Computational methods are widely used to analyze and integrate large biological data sets, while several algorithms were inspired by the high-level design principles of biological systems. In this talk I will discuss similarities and differences between assumptions, requirements and goals of distributed biological and computational systems. To illustrate the mutual benefits I will present examples from two recent studies. The first models bacterial food search as an application of probabilistic belief propagation while the second looks at epigenetics as a process implementing a shared memory communication model.

    Biography: Ziv Bar-Joseph is the FORE Systems Professor of Computational Biology and Machine Learning at the School of Computer Science at Carnegie Mellon University. His work focuses on the analysis, integration and modeling of high throughput biological data and on improving algorithms for distributed computational networks by relying on our increased understanding of how biological systems operate. Dr. Bar-Joseph received his Ph.D. from MIT in 2003. He is the director of the joint CMU-Pitt PhD program in Computational Biology and the PI of a number of large, multi-university centers including the HuBMAP Computational Tools Center. He was the recipient of the DIMACS-Celera Genomics Graduate Student Award in Computational Biology, the NSF CAREER award and Overton prize in computational biology.

    Host: Paul Bogdan

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - EEB 132

    Audiences: Everyone Is Invited

    Posted By: Talyia White

    OutlookiCal
  • Individual Grammar Tutorials

    Fri, Mar 08, 2019 @ 10:30 AM - 12:00 PM

    Viterbi School of Engineering Student Affairs

    Workshops & Infosessions


    Viterbi graduate and undergraduate students are invited to sign up for individual grammar assistance from professors at the Engineering Writing Program. Sign up for one-on-one individual sessions here: http://bit.ly/grammaratUSC

    Questions? Email helenhch@usc.edu

    Location: Olin Hall of Engineering (OHE) - 106

    Audiences: Graduate and Undergraduate Students

    Posted By: Helen Choi

    OutlookiCal
  • W.V.T. RUSCH ENGINEERING HONORS COLLOQUIUM

    Fri, Mar 08, 2019 @ 01:00 PM - 01:50 PM

    USC Viterbi School of Engineering

    Conferences, Lectures, & Seminars


    Speaker: Dr. Nathan Smith, Associate Curator, The Dinosaur Institute, Natural History Museum

    Talk Title: The Assembly of Avian Anatomy -“from Early Dinosaurs to Diving Waterbirds

    Host: EHP and Dr. Prata

    Location: Henry Salvatori Computer Science Center (SAL) - 101

    Audiences: Everyone Is Invited

    Posted By: Amanda McCraven

    OutlookiCal
  • Mingu Kang Seminar, Friday, March 8th at 2PM in EEB 132

    Fri, Mar 08, 2019 @ 02:00 PM - 03:30 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Mingu Kang, IBM Thomas J. Watson Research Center

    Talk Title: Energy-efficient machine learning in resource-constrained edge-computing platforms

    Abstract: There is much interest in embedding data analytics into sensor-rich platforms such as wearables, biomedical devices, autonomous vehicles, robots, and Internet-of-Things (IoT) to provide these with decision-making capabilities. Such platforms need to implement machine learning algorithms under severe resource-constraints in embedded battery-powered platforms. However, traditional von Neumann architectures suffer from explicit separation between memory and computation (the "Memory Wall"), which imposes bottlenecks on energy efficiency and throughput for big data processing.

    In this talk, I will present deep in-memory computing architecture (DIMA), where analog computation is deeply embedded into a standard memory array to overcome the memory wall. First, the data flow of machine learning algorithms is analyzed to show how it naturally leads to the DIMA. Next, the design of a multi-functional DIMA IC prototype will be presented to validate the concept of DIMA and demonstrate its versatility. An in-memory instruction set architecture with LLVM-based compiler is demonstrated to provide user-friendly programming interface, and optimal resource allocation for target application accuracy. DIMA lends itself to a communication-inspired system analysis that helps to understand the fundamental trade-off between its energy and accuracy in the low-SNR regime. Finally, I will present future research directions spanning device, architecture, and system to build large-scale system-on-chip by leveraging non-conventional computing including in-memory, in-sensor, and neuromorphic computing.


    Biography: Mingu Kang is a research staff member of the IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA, where he designs machine learning accelerator architecture. He received the Ph.D. degree in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, Champaign, IL, USA, in 2017, and the B.S. and M.S. degrees in Electrical and Electronic Engineering from Yonsei University, Seoul, South Korea, in 2007 and 2009, respectively. From 2009 to 2012, he was with the Memory Division, Samsung Electronics, Hwaseong, South Korea, where he was involved in the circuit and architecture design of phase change memory (PRAM). His current research interests include low-power integrated circuits, architecture, and system for machine learning and signal processing by leveraging emerging computing paradigms. He is a recipient of UIUC Coordinated Science Lab (CSL) best thesis award in 2018, MICRO TOP Pick Honorable Mention 2019, IEEE International Symposium on Circuits and Systems (ISCAS) "Neural System and Application" Best Paper Awards in 2016 and 2018, and Kwanjeong Scholarship from 2012 to 2017.

    Host: ECE-Electrophysics

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Posted By: Marilyn Poplawski

    OutlookiCal
  • Civil and Environmental Engineering

    Fri, Mar 08, 2019 @ 03:00 PM - 04:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars


    Speaker: Xu Huang, University of Toronto

    Talk Title: Large-Scale Computational/Experimental Distributed Simulation Framework

    Host: Civil and Environmental Engineering

    Location: Ray R. Irani Hall (RRI) - 101

    Audiences: Everyone Is Invited

    Posted By: Salina Palacios

    OutlookiCal
  • Repeating EventSatellite Propulsion Systems

    Sat, Mar 09, 2019 @ 09:00 AM - 05:00 PM

    Executive Education

    Conferences, Lectures, & Seminars


    Abstract: The Satellite Propulsion Systems program provides an understanding of the basic principles and figures of merit of Rocket Propulsion. Upon completion of the 4-day program, participants will be able to apply these principles to spacecraft propulsion system and components Analysis-&-Design, Testing, Ground Operations, Flight Operations, and End-of-life (EOL) De-orbit.

    More Info: https://viterbiexeced.usc.edu/engineering-program-areas/astronautical-engineering/satellite-propulsion-systems/

    Audiences: Registered Attendees

    View All Dates

    Posted By: Corporate & Professional Programs

    OutlookiCal