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Events for March 22, 2022
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CS Colloquium: Rachee Singh (Microsoft Azure for Operators) - Leveraging over-provisioned cloud networks for next-generation services
Tue, Mar 22, 2022 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Rachee Singh , Microsoft Azure for Operators
Talk Title: Leveraging over-provisioned cloud networks for next-generation services
Series: CS Colloquium
Abstract: The last decade has seen a large-scale commercialization of cloud computing and the emergence of global cloud providers. Cloud providers are expanding their datacenter deployments and backbone capacity, preparing their infrastructure to meet the challenges of rapidly evolving workloads in the cloud. In this talk, I will re-examine the design and operation choices made by cloud providers during this phase of exponential growth using a cross-layer empirical analysis of the wide-area network (WAN) of a large commercial cloud provider. Despite their crucial role in enabling high performance cloud applications and expensive infrastructure, there are several inefficiencies in both the design and operation of cloud WANs. In this talk, I will focus on improving the performance and cost efficiency of the fiber optical network underpinning cloud WANs. First, I will demonstrate how rate-adaptive physical links can harness 75% more capacity from 80% of the optical wavelengths in a cloud WAN, leading to a gain of over 100 terabits of network capacity with 25% fewer link failures. Second, I will show how to achieve a 40% reduction in the hardware costs of provisioning long-haul WAN capacity by optically bypassing network hops where conversion of light signals from optical to electrical domain is unnecessary and uneconomical. I will show that identifying and fixing these inefficiencies in today's cloud networks is crucial for enabling next-generation cloud services.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Rachee Singh is a senior researcher in the office of the CTO of Microsoft Azure for Operators. Before this, she was a researcher in the Mobility and Networking group of Microsoft Research, Redmond. Her research interests are in computer networking with a focus on wide area network performance and monitoring. Her PhD dissertation was supported by a Google PhD Fellowship in Systems and Networking and it received the CICS Outstanding dissertation award at the University of Massachusetts, Amherst. Recently, she was named a rising star in computer networking by N2Women and a rising star in EECS by UC Berkeley. In a previous life, she developed routing protocol features for Ethernet switches at Arista Networks.
Host: Ramesh Govindan
Location: Olin Hall of Engineering (OHE) - 132
Audiences: By invitation only.
Contact: Assistant to CS chair
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Virtual First-Year Admission Information SessionTue, Mar 22, 2022 @ 11:00 AM - 12:00 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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Webinar for U.S. Active Duty Military & Veteran Prospective Graduate Engineering Students
Tue, Mar 22, 2022 @ 12:00 PM - 01:00 PM
DEN@Viterbi, Viterbi School of Engineering Graduate Admission
Workshops & Infosessions
Join USC Viterbi to learn about the funding and support provided to U.S. active duty military and veterans who are interested in pursuing a graduate degree in engineering or computer science. This virtual information session via WebEx will discuss how USC Viterbi's flexible online DEN@Viterbi delivery enables active duty military and veterans to pursue their degree from anywhere in the world.
The session will discuss military funding and scholarships available, student support, enrollment options, FAQs, and more! Attendees will have the opportunity to connect directly with USC Viterbi representatives.
Register Now!WebCast Link: https://uscviterbi.webex.com/uscviterbi/onstage/g.php?MTID=edfce0fcb3165cdfc609cc79bf92919ab
Audiences: Everyone Is Invited
Contact: Corporate & Professional Programs
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CS Colloquium: Ariel Barel (Technion, Israeli Institute of Technology) - Applied Deep-Learning methods for Expediting Path Selection in Real-Time MAP
Tue, Mar 22, 2022 @ 01:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ariel Barel, Technion, Israeli Institute of Technology
Talk Title: Applied Deep-Learning methods for Expediting Path Selection in Real-Time MAP
Series: Computer Science Colloquium
Abstract: Multi-Agent Path Finding (MAPF) is an NP-hard problem that plays a key role in numerous domains ranging from warehouse automation to computer games. In this research we are given a large pre-calculated set of legal paths from all possible sources to all possible destinations. The aim is to select paths from this set such that they do not collide with static obstacles nor with each other and minimize the maximal execution time of all tasks (Makespan). This selection should be calculated in near real-time, i.e., extremely fast compared to classic MAPF algorithms.
We investigate how Deep-Learning methods may speed up the search process, as trained Neural Networks have potential to make computations extremely fast. Training dataset may be generated by solving the "online" problem offline. The idea is to train the network to recognize patterns in the training examples and apply them to new, previously unseen, settings of the problem, i.e., new pairs of sources and destinations. The main challenges are definition of NN architecture and input representation.
This work addresses well-formed environments where agents may wait indefinitely at their sources but must follow a wait-free path once deployed. Moreover, our framework allows assignment of multiple agents per source and requires that all calculations complete before the first deployment, making scheduling a key component of the solution.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Join Zoom Meeting
https://usc.zoom.us/j/98857434920
Meeting ID: 988 5743 4920
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Biography: Dr. Ariel Barel is an academic visitor at the Technion, Israeli Institute of Technology. He received the PhD degrees in Computer Science from the Technion in the field of Distributed Control of Multi-Agent Systems. His current interest also includes Machine Learning implementations to expedite traditional planning algorithms. For more info and publications visit his personal web page https://arielba.cswp.cs.technion.ac.il/
Host: Christopher Leet (cjleet@usc.edu), Sven Koenig (skoenig@usc.edu)
Webcast: https://usc.zoom.us/j/98857434920Location: Online - Zoom
WebCast Link: https://usc.zoom.us/j/98857434920
Audiences: Everyone Is Invited
Contact: Computer Science Department
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CS Colloquium: Natasha Jacques (Google Brain / UC Berkeley) - Social Reinforcement Learning
Tue, Mar 22, 2022 @ 02:00 PM - 03:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Natasha Jacques, Google Brain / UC Berkeley
Talk Title: Social Reinforcement Learning
Series: CS Colloquium
Abstract: Social learning helps humans and animals rapidly adapt to new circumstances, coordinate with others, and drives the emergence of complex learned behaviors. What if it could do the same for AI? This talk describes how Social Reinforcement Learning in multi-agent and human-AI interactions can address fundamental issues in AI such as learning and generalization, while improving social abilities like coordination. I propose a unified method for improving coordination and communication based on causal social influence. I then demonstrate that multi-agent training can be a useful tool for improving learning and generalization. I present PAIRED, in which an adversary learns to construct training environments to maximize regret between a pair of learners, leading to the generation of a complex curriculum of environments. Agents trained with PAIRED generalize more than 20x better to unknown test environments. Ultimately, the goal of my research is to create intelligent agents that can assist humans with everyday tasks; this means leveraging social learning to interact effectively with humans. I show that learning from human social and affective cues scales more effectively than learning from manual feedback. However, it depends on accurate recognition of such cues. Therefore I discuss how to dramatically enhance the accuracy of affect detection models using personalized multi-task learning to account for inter-individual variability. Together, this work argues that Social RL is a valuable approach for developing more general, sophisticated, and cooperative AI, which is ultimately better able to serve human needs.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Natasha Jaques holds a joint position as a Senior Research Scientist at Google Brain and Postdoctoral Fellow at UC Berkeley. Her research focuses on Social Reinforcement Learning in multi-agent and human-AI interactions. Natasha completed her PhD at MIT, where her thesis received the Outstanding PhD Dissertation Award from the Association for the Advancement of Affective Computing. Her work has also received Best Demo at NeurIPS, an honourable mention for Best Paper at ICML, Best of Collection in the IEEE Transactions on Affective Computing, and Best Paper at the NeurIPS workshops on ML for Healthcare and Cooperative AI. She has interned at DeepMind, Google Brain, and was an OpenAI Scholars mentor. Her work has been featured in Science Magazine, Quartz, MIT Technology Review, Boston Magazine, and on CBC radio. Natasha earned her Masters degree from the University of British Columbia, and undergraduate degrees in Computer Science and Psychology from the University of Regina.
Host: Jesse Thomason
Location: Ronald Tutor Hall of Engineering (RTH) - 105
Audiences: By invitation only.
Contact: Assistant to CS chair
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ISE 651 Epstein Seminar
Tue, Mar 22, 2022 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Alain Rossier, Visiting guest/3rd year PhD student, Oxford University
Talk Title: Asymptotic Analysis of Deep Residual Networks
Host: Dr. Renyuan Xu
More Information: March 22, 2022.pdf
Location: Online/Zoom
Audiences: Everyone Is Invited
Contact: Grace Owh
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Mork Family Department Seminar - Aditya Sood
Tue, Mar 22, 2022 @ 04:00 PM - 05:20 PM
Mork Family Department of Chemical Engineering and Materials Science
Conferences, Lectures, & Seminars
Speaker: Aditya Sood, Stanford University
Talk Title: Engineering functionality through dynamic visualization and control of atomic motions
Host: Professor A.Hodge
Location: Social Sciences Building (SOS) - B46
Audiences: Everyone Is Invited
Contact: Heather Alexander
