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Distinguished Colloquium Series Speaker

Theoretical Reflections on Quantum Supremacy

Date and Time
Wednesday, May 19, 2021 - 12:30pm to 1:30pm
Location
Zoom Webinar (off campus)
Type
Distinguished Colloquium Series Speaker
Host
Sanjeev Arora & Andrew Houck

Recording available here


Umesh Vazirani
The recent demonstration of quantum supremacy by Google is a first step towards the era of small to medium scale quantum computers. In this talk I will explain what the experiment accomplished and the theoretical work it is based on, as well as what it did not accomplish and the many theoretical and practical challenges that remain. I will also describe recent breakthroughs in the design of protocols for the testing and benchmarking of quantum computers, a task that has deep computational and philosophical implications. Specifically, this leads to protocols for scalable and verifiable quantum supremacy, certifiable quantum random generation and verification of quantum computation.

Bio:
Umesh Vazirani is Strauch Distinguished Professor of Computer Science at UC Berkeley, and Director of the Berkeley Quantum Computing Center (BQIC). His 1993 paper with Ethan Bernstein laid the foundations of quantum complexity theory, and his research has touched on many facets of quantum computation, including Quantum Algorithms, Quantum Hamiltonian Complexity and Interactive classical testing of quantum devices. Vazirani is co-inventor of the Bid Scaling algorithm for the AdWords auction which is widely used by Internet search companies, and co-winner of the Fulkerson Prize for the ARV graph partitioning algorithm. He is member of the NAS, and co-author of two books: An Introduction to Computational Learning Theory (MIT Press) and Algorithms (McGraw-Hill).

To request accommodations for a disability please contact Emily Lawrence, emilyl@cs.princeton.edu, at least one week prior to the event.

Monoculture and Simplicity in an Ecosystem of Algorithmic Decision-Making

Date and Time
Thursday, April 29, 2021 - 4:30pm to 5:30pm
Location
Zoom Webinar (off campus)
Type
Distinguished Colloquium Series Speaker
Host
Sanjeev Arora

Click here for recording 


Jon Kleinberg
Algorithms are increasingly used to aid decision-making in high-stakes settings including employment, lending, healthcare, and the legal system. This development has led to an ecosystem of growing complexity in which algorithms and people interact around consequential decisions, often mediated by organizations and firms that may be in competition with one another.

We consider two related sets of issues that arise in this setting. First, concerns have been raised about the effects of algorithmic monoculture, in which multiple decision-makers all rely on the same algorithm. In a set of models drawing on minimal assumptions, we show that when competing decision-makers converge on the use of the same algorithm as part of a decision pipeline, the result can potentially be harmful for social welfare even when the algorithm is more accurate than any decision-maker acting on their own. Second, we consider some of the canonical ways in which data is simplified over the course of these decision-making pipelines, showing how this process of simplification can introduce sources of bias in ways that connect to principles from the psychology of stereotype formation.

The talk will be based on joint work with Sendhil Mullainathan and Manish Raghavan.

Bio:
Jon Kleinberg is the Tisch University Professor in the Departments of Computer Science and Information Science at Cornell University. His research focuses on the interaction of algorithms and networks, the roles they play in large-scale social and information systems, and their broader societal implications. He is a member of the National Academy of Sciences and the National Academy of Engineering, and the recipient of MacArthur, Packard, Simons, Sloan, and Vannevar Bush research fellowships, as well awards including the Harvey Prize, the Nevanlinna Prize, and the ACM Prize in Computing.


To request accommodations for a disability please contact Emily Lawrence, emilyl@cs.princeton.edu, at least one week prior to the event.

Language, Brain, and Computation

Date and Time
Friday, February 19, 2021 - 12:30pm to 1:30pm
Location
Zoom Webinar (off campus)
Type
Distinguished Colloquium Series Speaker
Host
Sanjeev Arora

Watch the recording here


Christos Papadimitriou
How does the brain beget the mind?  How do molecules, cells and synapses effect reasoning, intelligence, language?   Despite dazzling progress in experimental neuroscience, as well as in cognitive science at the other extreme of scale, we do not seem to be making progress in the overarching question -- the gap is huge and a completely new approach seems to be required.  As Richard Axel recently put it:  "We don't have a logic for the transformation of neural activity into thought [...]."  

What kind of formal system would qualify as this "logic"? 

I will introduce the Assembly Calculus, a computational system whose basic data structure is the assembly -- assemblies are large populations of neurons representing concepts, words, ideas, episodes, etc.,

The Assembly Calculus is biologically plausible in the following two orthogonal senses: Its primitives are properties of assemblies observed in experiments or useful for explaining experiments, and can be provably (through both mathematical proof and simulations) "compiled down" to the activity of neurons and synapses.  I will also explain why the Assembly Calculus is especially powerful in exploring how language happens in the brain.

Bio: Christos Harilaos Papadimitriou is the Donovan Family Professor of Computer Science at Columbia University.  Before joining Columbia in 2017, he was a professor at UC Berkeley for the previous 22 years, and before that he taught at Harvard, MIT, NTU Athens, Stanford, and UCSD.  He has written five textbooks and many articles on algorithms and complexity, and their applications to optimization, databases, control, AI, robotics, economics and game theory, the Internet, evolution, and the brain.  He holds a PhD from Princeton (1976), and eight honorary doctorates, including from ETH, University of Athens, EPFL, and Univ. de Paris Dauphine.  He is a member of the National Academy of Sciences of the US, the American Academy of Arts and Sciences, and the National Academy of Engineering, and he has received the Knuth prize, the Go"del prize, the von Neumann medal, as well as the 2018 Harvey Prize by Technion.  In 2015 the president of the Hellenic republic named him commander of the order of the Phoenix.  He has also written three novels: “Turing ,” “Logicomix”  and his latest “Independence.”


This talk will be recorded.  To request accommodations for a disability please contact Emily Lawrence, emilyl@cs.princeton.edu, at least one week prior to the event.

Collaboration as a Lens for Inclusive Technical Innovation

Date and Time
Monday, November 9, 2020 - 4:30pm to 5:30pm
Location
Zoom Webinar (off campus)
Type
Distinguished Colloquium Series Speaker
Host
Szymon Rusinkiewicz

Meredith Ringel Morris
*This talk is open only to Princeton University faculty, staff, and students. 
Please register for this webinar here.


In this lecture, I show how considering the intersection of collaborative and social scenarios with other domains of computing can reveal end-user needs and result in innovative technical systems. I give examples of this approach from my work in gesture interaction, information retrieval, and accessibility, focusing particularly on the topics of creating more efficient and expressive augmentative and alternative communication technologies and of making social media more accessible to screen reader users. I close by identifying future opportunities for creating inclusive collaborative and social technologies.

Bio:
Meredith Ringel Morris is a Sr. Principal Researcher at Microsoft Research and Research Area Manager for Interaction, Accessibility, and Mixed Reality. She founded Microsoft Research’s Ability research group and is a member of the lab’s Leadership Team. She is also an Affiliate Professor at the University of Washington in the Allen School of Computer Science & Engineering and in The Information School. Dr. Morris is an expert in Human-Computer Interaction; in 2020, she was inducted into the ACM SIGCHI Academy in recognition of her research in collaborative and social computing. Her research on collaboration and social technologies has contributed new systems, methods, and insights to diverse areas of computing including gesture interaction, information retrieval, and accessibility. Dr. Morris earned her Sc.B. in Computer Science from Brown University and her M.S. and Ph.D. in Computer Science from Stanford University.


To request accommodations for a disability please contact Emily Lawrence, emilyl@cs.princeton.edu at least one week prior to the event.

A New Abstraction for Software Design

Date and Time
Monday, March 2, 2020 - 12:30pm to 1:30pm
Location
Computer Science Small Auditorium (Room 105)
Type
Distinguished Colloquium Series Speaker
Host
Jennifer Rexford

Daniel Jackson
The internal design of software—how the code is structured—is powered by familiar abstractions (such as abstract types, classes and modules). But the external design—how the software actually behaves—is usually viewed informally, without the guidance of robust abstractions.

For the last few years, I have been exploring a new abstraction that can shape how we think about software applications and systems, and that provides a way to organize behaviors, encapsulate reusable ideas, and evaluate designs.

In this talk, I’ll define this abstraction and show how it can be used to explain a variety of flaws in familiar applications. I’ll also present some general principles that attempt to capture some key aspects of good software design.

Bio: Daniel Jackson is a professor of computer science and MacVicar teaching fellow at MIT, and associate director of the Computer Science and Artificial Intelligence Laboratory. His research has focused primarily on software modeling and design, most notably the Alloy modeling language. He is also a photographer whose most recent project brings to light the experiences of those with depression and other mental health issues (http://portraitsofresilience.com).

Lunch for talk attendees will be available at 12:00pm. 
To request accommodations for a disability, please contact Emily Lawrence, emilyl@cs.princeton.edu, 609-258-4624 at least one week prior to the event.

Self-Driving Networks: Is it a good idea to mix AI and computer networks?

Date and Time
Wednesday, November 13, 2019 - 12:30pm to 1:30pm
Location
Computer Science Small Auditorium (Room 105)
Type
Distinguished Colloquium Series Speaker
Speaker
Host
Kyle Jamieson

Jeff Mogul
Just as you wouldn't want to be in a car without seat belts, even if it's a self-driving car, you probably don't want your Self-Driving Network (SelfDN) to rely completely on control-theory or ML, no matter how sophisticated or formally verified.   While autonomous systems promise to solve many problems that afflict networks, just as they promise to solve many problems that afflict our roadways, they are not immune from a multitude of practical problems and unexpected consequences. At Google, we have been moving towards highly-automated networking, and along the way we have learned a lot about the risks involved, and how to build robust networks in spite of the wonders of automation.  I will talk about some of the problems that are likely to afflict SelfDNs as they enter the real world.

Bio:
Jeff Mogul works on fast, cheap, reliable, and flexible networking infrastructure for Google. Until 2013, he was a Fellow at HP Labs, doing research primarily on computer networks and operating systems issues for enterprise and cloud computer systems; previously, he worked at the DEC/Compaq Western Research Lab. He received his PhD from Stanford in 1986, an MS from Stanford in 1980, and an SB from MIT in 1979. He is an ACM Fellow. Jeff is the author or co-author of several Internet Standards; he contributed extensively to the HTTP/1.1 specification. He was an associate editor of Internetworking: Research and Experience, and has been the chair or co-chair of a variety of conferences and workshops, including SIGCOMM, OSDI, NSDI, USENIX, HotOS, and ANCS.

Lunch for talk attendees will be available at 12:00pm. 
To request accommodations for a disability, please contact Emily Lawrence, emilyl@cs.princeton.edu, 609-258-4624 at least one week prior to the event.

Can learning theory resist deep learning?

Date and Time
Friday, November 15, 2019 - 12:30pm to 1:30pm
Location
Computer Science Small Auditorium (Room 105)
Type
Distinguished Colloquium Series Speaker
Speaker
Host
Barbara Engelhardt, Sanjeev Arora, Peter Ramadge

Francis Bach
Machine learning algorithms are ubiquitous in most scientific, industrial and personal domains, with many successful applications. As a scientific field, machine learning has always been characterized by the constant exchanges between theory and practice, with a stream of algorithms that exhibit both good empirical performance on real-world problems and some form of theoretical guarantees. Many of the recent and well publicized applications come from deep learning, where these exchanges are harder to make, in part because the objective functions used to train neural networks are not convex. In this talk, I will present recent results on the global convergence of gradient descent for some specific non-convex optimization problems, illustrating these difficulties and the associated pitfalls (joint work with Lénaïc Chizat and Edouard Oyallon).

Bio:
Francis Bach is a researcher at INRIA, leading since 2011 the SIERRA project-team, which is part of the Computer Science Department at Ecole Normale Supérieure, and a joint team between CNRS, ENS and INRIA. Since 2016, he is an adjunct Professor at Ecole Normale Supérieure. He completed his Ph.D. in Computer Science at U.C. Berkeley, working with Professor Michael Jordan, and spent two years in the Mathematical Morphology group at Ecole des Mines de Paris, he then joined the WILLOW project-team at INRIA/Ecole Normale Superieure/CNRS from 2007 to 2010. He obtained in 2009 a Starting Grant and in 2016 a Consolidator Grant from the European Research Council, and received the Inria young researcher prize in 2012, the ICML test-of-time award in 2014, as well as the Lagrange prize in continuous optimization in 2018. In 2015, he was program co-chair of the International Conference in Machine learning (ICML), and general chair in 2018; he is now co-editor-inchief of the Journal of Machine Learning Research. Francis Bach is primarily interested in machine learning, and especially in graphical models, sparse methods, kernel-based learning, large-scale convex optimization, computer vision and signal processing.


Lunch for talk attendees will be available at 12:00pm. 
To request accommodations for a disability, please contact Emily Lawrence, emilyl@cs.princeton.edu, 609-258-4624 at least one week prior to the event.

Zanzibar: Google’s Consistent, Global Authorization System

Date and Time
Wednesday, October 16, 2019 - 1:30pm to 2:30pm
Location
Computer Science Small Auditorium (Room 105)
Type
Distinguished Colloquium Series Speaker
Speaker
Host
Margaret Martonosi

Ramon Caceres
Determining whether online users are authorized to access digital objects is central to preserving privacy. This talk presents the design, implementation, and deployment of Zanzibar, a global system for storing and evaluating access control lists. Zanzibar provides a uniform data model and configuration language for expressing a wide range of access control policies from hundreds of client services at Google, including Calendar, Cloud, Drive, Maps, Photos, and YouTube. Its authorization decisions respect causal ordering of user actions and thus provide external consistency amid changes to access control lists and object contents. Zanzibar scales to trillions of access control lists and millions of authorization requests per second to support services used by billions of people. It has maintained 95th-percentile latency of less than 10 milliseconds and availability of greater than 99.999% over 3 years of production use.
 

Bio: Ramón Cáceres is a software engineer at Google. He was previously a researcher at AT&T Labs and IBM Research. His areas of focus include computer systems and networks, mobile computing services and applications, and location data analysis and modeling. He holds a PhD in Computer Science from the University of California at Berkeley. He is an IEEE Fellow and an ACM Distinguished Scientist.


To request accommodations for a disability, please contact Emily Lawrence, emilyl@cs.princeton.edu, 609-258-4624 at least one week prior to the event.

Democratizing the Network Edge

Date and Time
Wednesday, January 23, 2019 - 2:00pm to 3:00pm
Location
Computer Science Small Auditorium (Room 105)
Type
Distinguished Colloquium Series Speaker
Host
Jennifer Rexford

Larry Peterson
The network edge—where the access networks that connect homes, businesses, and mobile users to the Internet are implemented—is in the midst of a transformation. Network operators (Telcos and CableCos) are transitioning from closed and proprietary hardware to disaggregated and virtualized software running on white-box servers, switches, and access devices. This transformation is partly motivated by the CAPEX savings that come from replacing purpose-built appliances with commodity hardware, but it is mostly driven by the need to increase feature velocity through the softwarization of the access network. The goal is to enable new classes of edge services—e.g., Autonomous Vehicles, Internet-of-Things (IoT), Immersive User Interfaces—that benefit from low latency connectivity. This is all part of the growing trend to move functionality to the network edge.

This transformation faces two technical challenges. The first is to disaggregate and virtualize existing hardware appliances. This is done, for example, by applying SDN principles (decoupling the network control and data planes) and by breaking monolithic applications into a set of micro-services. The second is to integrate the resulting disaggregated components back into a functioning system, packaged with sufficient configuration and life cycle management tools to make it deployable in a production environment. This talk describes CORD, a community-based open source effort to address these challenges. CORD is being deployed in Telco field trials, but more interestingly, it lowers the barrier for anyone (not just global carriers) to deploy edge solutions that incorporate the latest 5G (wireless) and XGS-PON (fiber) access technologies. The talk concludes with some remarks on the opportunity this democratization of the network edge opens for the research community.

Bio:
Larry Peterson is the Robert E. Kahn Professor of Computer Science, Emeritus at Princeton University, where he served as Chair from 2003-2009. He is a co-author of the best selling networking textbook Computer Networks: A Systems Approach (5e). His research focuses on the design, implementation, and deployment of Internet-scale distributed systems, including the widely used PlanetLab and MeasurementLab platforms. He is currently working on a new access edge cloud called CORD, an open source project of the Open Networking Foundation

Professor Peterson is a former Editor-in-Chief of the ACM Transactions on Computer Systems, and served as program chair for SOSP, NSDI, and HotNets. He is a member of the National Academy of Engineering, a Fellow of the ACM and the IEEE, the 2010 recipient of the IEEE Kobayashi Computer and Communication Award, and the 2013 recipient of the ACM SIGCOMM Award. He received his Ph.D. degree from Purdue University in 1985.

Georgia Tech's Online MOOC-based Master Program

Date and Time
Thursday, February 14, 2019 - 12:30pm to 1:30pm
Location
Computer Science Small Auditorium (Room 105)
Type
Distinguished Colloquium Series Speaker
Host
Nick Feamster

Zvi Galil
In May 2013, Georgia Tech together with its partners, Udacity and AT&T, announced a new online master’s degree in computer science delivered through the platform popularized by massively open online courses (MOOCs). This new online MS CS— or OMSCS for short — costs less than $7,000 total, compared with a price tag of $40,000 for an MS CS at comparable public universities and upwards of $70,000 at private universities.

The first-of-its-kind program was launched in January 2014 and has sparked a worldwide conversation about higher education in the 21st century. President Barack Obama praised OMS CS by name twice, and more than 1,200 news stories mentioned the program. It has been described as a potential "game changer" and "ground zero of the revolution in higher education”.  Harvard University researchers concluded that OMSCS is “the first rigorous evidence showing an online degree program can increase educational attainment” and predicted that OMSCS will single handedly raise the number of annual MS CS graduates in the United States by at least 7 percent.

OMSCS started in 2014 with an enrollment of 380; in this semester (spring 2019) enrollment is close to 9,000; OMSCS is apparently the biggest MS in CS program in the world. So far more than 2,000  students have graduated from OMSCS; more than 1,000 will graduate each year from now on. The program has also paved the way for at least 22 similar, MOOC-based online MS programs. According to the Bureau of Labor Statistics and the National Science Foundation, there is a shortage of 500,000 computer professionals in the US, a shortage that will reach one million by 2020. In other words, OMSCS is satisfying a great national need.
 
The talk will describe the OMSCS program, how it came about, its first five years, and what Georgia Tech has learned from the OMSCS experience. We will also discuss its potential effect on higher education.

Bio:
Dr. Zvi Galil, Dean of the College of Computing, Georgia Institute of Technology, was born in Tel Aviv, Israel. He earned BS and MS degrees in Applied Mathematics from Tel Aviv University, both summa cum laude. He then obtained a PhD in Computer Science from Cornell University. After a post-doctorate in IBM's Thomas J. Watson research center, he returned to Israel and joined the faculty of Tel-Aviv University. He served as the chair of the Computer Science department in 1979-1982.  In 1982 he joined the faculty of Columbia University. He served as the chair of the Computer Science Department in 1989-1994 and as dean of The Fu Foundation School of Engineering & Applied Science in 1995-2007. Galil was appointed Julian Clarence Levi Professor of Mathematical Methods and Computer Science in 1987, and Morris and Alma A. Schapiro Dean of Engineering in 1995. In 2007 Galil returned to Tel Aviv University and served as president. In 2009 he resigned as president and returned to the  faculty as a professor of Computer Science. In July 2010 he became The John P. Imlay, Jr. Dean of Computing at Georgia Tech.   

Dr. Galil's research areas have been the design and analysis of algorithms, complexity, cryptography and experimental design. In 1983-1987 he served as chairman of ACM SIGACT, the Special Interest Group of Algorithms and Computation Theory. He has written over 200 scientific papers, edited 5 books, and has given about 250 lectures in 25 countries (over 60 in 15 countries on OMSCS). Galil has served as editor in chief of two journals and as the chief computer science adviser in the United States to the Oxford University Press. He is a fellow of the ACM and the American Academy of Arts and Sciences and a member of the National Academy of Engineering. In 2008 Columbia University established the Zvi Galil Award for Improvement in Engineering Student Life. In 2009 the Columbia Society of Graduates awarded him the Great Teacher Award.  In 2012 the University of Waterloo awarded him an honorary doctorate in mathematics. 

Zvi Galil is married to Dr. Bella S. Galil, a marine biologist. They have one son, Yair, a corporate lawyer in New York City.

Lunch for talk attendees will be available at 12:00pm. 
To request accommodations for a disability, please contact Emily Lawrence, emilyl@cs.princeton.edu, 609-258-4624 at least one week prior to the event.

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