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CIS Seminar: “Advances in Machine Learning Systems Research”

October 27, 2020 at 3:00 PM - 4:00 PM

A long-standing grand challenge in computing is to enable machines to act autonomously and intelligently: to rapidly and repeatedly take appropriate actions based on information in the world around them. Driven by trends in the data economy, rapid progress in AI, and an increasingly programmable physical world we are at an inflection point that demands a new class of AI system. This new class of systems goes beyond training models at scale, to connecting models with the world, rendering predictions in real-time under heavy query load, adapting to new observations and contexts. These systems will need to be composable and elastically scalable to accommodate new technologies and variations in workloads. Operating in the physical world, observing intimate details of our lives, and making critical decisions, these systems must also be secure.

In this talk, I will present work in my group exploring advances in systems for prediction serving, autonomous driving, and how model design and system design interact.  In particular, I will discuss some of the key trade-offs between time, accuracy,  convergence, throughput, and security that govern how we design systems, train models, and make predictions that meet the demands of real-world applications.

Joseph Gonzalez

Sept. of Electrical engineering and Computer Science University of California, Berkeley

Joseph Gonzalez is a founding member of the Berkeley RISE Lab where he studies the design of Real-time, Intelligent, Secure, and Explainable systems.  He is also a member of the Berkeley AI Research Group.  Gonzalez’s research addresses problems in neural network design, efficient inference, computer vision, prediction serving, autonomous vehicles, graph analytics, and distributed systems.  Gonzalez also helped develop the Data Science program at UC Berkeley and co-created Data100 which is now taught to over a thousand students a semester.  Prior to joining Berkeley, Gonzalez co-founded Turi Inc (formerly GraphLab) based on his thesis work and created the GraphX project (now part of Apache Spark).  Gonzalez’s innovative work has earned him significant recognition, including the Okawa Research Grant, NSF Early Career Award, and the NSF Expedition Award.

Details

Date:
October 27, 2020
Time:
3:00 PM - 4:00 PM
Event Tags:
Website:
https://www.cis.upenn.edu/events/

Organizer

Computer and Information Science
Phone:
215-898-8560
Email:
cis-info@cis.upenn.edu
View Organizer Website

Venue

Zoom – Email CIS for link
cherylh@cis.upenn.edu
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