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Events for March 11, 2020
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ECE Seminar: Compiler and Runtime Systems for Homomorphic Encryption and Graph Analytics
Wed, Mar 11, 2020 @ 10:45 AM - 11:45 AM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Roshan Dathathri, PhD candidate, Dept of CS, University of Texas at Austin
Talk Title: Compiler and Runtime Systems for Homomorphic Encryption and Graph Analytics
Abstract: Distributed and heterogeneous architectures are tedious to program because devices such as CPUs, GPUs, FPGAs, and TPUs provide different programming abstractions and may have disjoint memories, even if they are on the same machine. In this talk, I present compiler and runtime systems that make it easier to develop efficient programs for privacy-preserving computation and graph analytics applications on such architectures.
Fully Homomorphic Encryption (FHE) refers to a set of encryption schemes that allow computations on encrypted data without requiring a secret key. Recent cryptographic advances have pushed FHE into the realm of practical applications. However, programming these applications remains a huge challenge, as it requires cryptographic domain expertise to ensure correctness, security, and performance. I present CHET, a domain-specific optimizing compiler, that is designed to make the task of programming neural network inference applications using FHE easier. CHET automates many laborious and error prone programming tasks including encryption parameter selection to guarantee security and accuracy of the computation, determining efficient data layouts, and performing scheme-specific optimizations. Our evaluation of CHET on a collection of popular neural networks shows that CHET-generated programs outperform expert-tuned ones by an order of magnitude.
Applications in several areas like machine learning, bioinformatics, and security need to process and analyze very large graphs. Distributed clusters are essential in processing such graphs in reasonable time. I present a novel approach to building distributed graph analytics systems that exploits heterogeneity in processor types, partitioning policies, and programming models. The key to this approach is Gluon, a domain-specific communication-optimizing substrate. Programmers write applications in a shared-memory programming system of their choice and interface these applications with Gluon using a lightweight API. Gluon enables these programs to run on heterogeneous clusters and optimizes communication in a novel way by exploiting structural and temporal invariants of graph partitioning policies. Systems built using Gluon outperform previous state-of-the-art systems and scale well up to 256 CPUs and 64 GPUs.
Biography: Roshan is a Ph.D. candidate advised by Prof. Keshav Pingali in the University of Texas at Austin. He works on domain-specific programming languages, compilers, and runtime systems that make it easy to develop efficient sparse computation and privacy-preserving computation on large-scale distributed clusters, while utilizing heterogeneous architectures. He has built programming systems for distributed and heterogeneous graph analytics and privacy-preserving neural network inferencing. He received his masters from Indian Institute of Science advised by Prof. Uday Bondhugula, where he worked on automatic parallelization of affine loop nests for distributed and heterogeneous architectures.
Host: Professor Massoud Pedram
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Mayumi Thrasher
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CS Colloquium: Jesse Thomason (University of Washington) - Language Grounding with Robots
Wed, Mar 11, 2020 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Jesse Thomason, University of Washington
Talk Title: Language Grounding with Robots
Series: CS Colloquium
Abstract: We use language to refer to objects like "toast", "plate", and "table" and to communicate requests such as "Could you make breakfast?" In this talk, I will present work on computational methods to tie language to physical, grounded meaning. Robots are an ideal platform for such work because they can perceive and interact with the world. I will discuss dialog and learning strategies I have developed to enable robots to learn from their human partners, similar to how people learn from one another through interaction. I will present methods enabling robots to understand language referring expressions like "the heavy, metallic mug", the first work showing that it is possible to learn to connect words to their perceptual properties in the visual, tactile, and auditory senses of a physical robot. I will also present benchmarks and models for translating high-level human language like "put the toast on the table" that imply latent, intermediate goals into executable sequences of agent actions with the help of low-level, step-by-step language instructions. Finally, I will discuss how my work in grounded language contributes to NLP, robotics, and the broader goals of the AI community.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Jesse Thomason is a postdoctoral researcher at the University of Washington working with Luke Zettlemoyer. He received his PhD from the University of Texas at Austin with Raymond Mooney. His research focuses on language grounding and natural language processing applications for robotics (RoboNLP). Key to this work is using dialog with humans to facilitate both robot task execution and learning to enable lifelong improvement of robots' language understanding capabilities. He has worked to encourage and promote work in RoboNLP through workshop organization at both NLP and robotics conference venues.
Host: Stefanos Nikolaidis
Location: Ronald Tutor Hall of Engineering (RTH) - 109
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Computer Science General Faculty Meeting
Wed, Mar 11, 2020 @ 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: Ronald Tutor Hall of Engineering (RTH) - 526
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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AME Laufer Lecture - CANCELLED
Wed, Mar 11, 2020 @ 12:00 PM - 02:00 PM
Aerospace and Mechanical Engineering
Conferences, Lectures, & Seminars
Speaker: Howard A. Stone, Princeton
Abstract: This event has been cancelled.
Host: AME Department
More Info: https://ame.usc.edu/seminars/
Audiences: Everyone Is Invited
Contact: Tessa Yao
Event Link: https://ame.usc.edu/seminars/
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POSTPONED- Internship/Job Search Open Forum
Wed, Mar 11, 2020 @ 01:00 PM - 02:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Will be rescheduled virtually at a later date.
For more information about Labs & Open Forums, please visit viterbicareers.usc.edu/workshops.
Location: Ronald Tutor Hall of Engineering (RTH) -
Audiences: All Viterbi
Contact: RTH 218 Viterbi Career Connections
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*CANCELLED* CAIS Seminar: Rediet Abebe (Harvard University) - Mechanism Design for Social Good
Wed, Mar 11, 2020 @ 04:15 PM - 05:15 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Rediet Abebe, Harvard University
Talk Title: Mechanism Design for Social Good
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: Algorithmic and artificial intelligence techniques show immense potential to deepen our understanding of socioeconomic inequality and inform interventions designed to improve access to opportunity. Interventions aimed at historically under-served communities are made particularly challenging by the fact that disadvantage and inequality are multifaceted, notoriously difficult to measure, and reinforced by feedback loops in underlying structures.
In this talk, we develop algorithmic and computational techniques to address these issues through two types of interventions: one in the form of allocating scarce societal resources and another in the form of improving access to information. We examine the ways in which techniques from algorithms, discrete optimization, and network and computational science can combat different forms of disadvantage, including susceptibility to income shocks, social segregation, and disparities in access to health information. We discuss current practice and policy informed by this work and close with a discussion of an emerging research area -- Mechanism Design for Social Good (MD4SG) -- around the use of algorithms, optimization, and mechanism design to address this category of problems.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Rediet Abebe is a Junior Fellow at the Harvard Society of Fellows and will be receiving her Ph.D. in computer science from Cornell University in 2019. Her research is broadly in the fields of algorithms and AI, with a focus on equity and social good concerns. As part of this research agenda, she co-founded Mechanism Design for Social Good (MD4SG), a multi-institutional, interdisciplinary research initiative working to improve access to opportunity for historically disadvantaged communities. This initiative has active participants from over 100 institutions in 20 countries and has been supported by Schmidt Futures, the MacArthur Foundation, and the Institute for New Economic Thinking.
Abebe currently serves on the NIH Advisory Committee to the Director Working Group on AI, tasked with developing a comprehensive report to the NIH leadership. She was recently named one of 35 Innovators Under 35 by the MIT Technology Review and honored in the 2019 Bloomberg 50 list as a "one to watch." Her work has been covered by outlets including Forbes, the Boston Globe, and the Washington Post. In addition to her research, she also co-founded Black in AI, a non-profit organization tackling diversity and inclusion issues in AI. Her research is deeply influenced by her upbringing in her hometown of Addis Ababa, Ethiopia.
Host: USC Center for Artificial Intelligence in Society (CAIS)
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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POSTPONED- Behavioral Interview Workshop with Veeva Systems
Wed, Mar 11, 2020 @ 06:30 PM - 08:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Learn more about what employers look for and how to best brand yourself so you stand out from the competition during the interview process! We will focus on one's personal brand, networking and how to ensure you are remembered when you leave the meeting or interview.
Veeva Systems is a leader in cloud-based software for the global life sciences industry. Veeva is dedicated to building careers of new university graduates. Generation Veeva is a program focused on your professional development, providing mentors, workshops, and career path planning.
Opportunities available for students majoring in: Computer Science, Computer Engineering, and any software development related major. Open to all Bachelors, Masters and PhD students.
To learn more about our Generation Veeva Program, visit our website at: https://www.veeva.com/generationveeva/Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
