Keith Winstein's homepage (original) (raw)
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Keith WinsteinAssociate Professor of Computer ScienceAssociate Professor of Electrical Engineering (by courtesy)Stanford UniversityComputing and Data Science, room W342389 Jane Stanford WayStanford, CA 94305-9025 |
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Bio: Keith Winstein is an associate professor of computer science and, by courtesy, of electrical engineering at Stanford University. His research group creates new kinds of networked systems by rethinking abstractions around communication, compression, and computing. Some of his group's research has found broader use, including the Mosh tool, the Puffer video-streaming site, the Leptoncompression tool, the Mahimahinetwork emulators, and the gg lambda-computing framework. He has received the SIGCOMM Rising Star Award, the Sloan Research Fellowship, the NSF CAREER Award, the Usenix NSDI Community Award (2024, 2020, 2017), the Usenix NSDI Outstanding Paper Award, the Usenix ATC Best Paper Award, the Applied Networking Research Prize, the SIGCOMM Doctoral Dissertation Award, and a Sprowls award for best doctoral thesis in computer science at MIT. Winstein previously served as a staff reporter at The Wall Street Journal and worked at Ksplice, a startup company (now part of Oracle) where he was the vice president of product management and business development and also cleaned the bathroom. He did his undergraduate and graduate work at MIT.
CV: Here is my CV.
Students
Current
- Doctoral
- Yuhan Deng
- Akshay Srivatsan (with Dawson Engler)
- Gina Yuan (with David Mazières and Matei Zaharia)
- Master's and undergraduate
- Francis Chua
- Sebastian Ingino Former
- Doctoral
- Francis Yan (2020, with Philip Levis), Microsoft Research & Azure for Operators
- Colleen Josephson (2020, with Sachin Katti), assistant professor, UC Santa Cruz
- Luke Hsiao (2021, with Philip Levis), Numbers Station
- Riad S. Wahby (2021, with Dan Boneh), assistant professor, Carnegie Mellon University
- Sadjad Fouladi (2021), Microsoft Research
- John Emmons (with Silvio Savarese), Tesla
- Greg Hill, Bot Lab
- Master's, undergraduate, and HS
- Angela Montemayor (now PhD. student, U. Washington)
- Yasmine Mitchell (now Netflix)
- Pratyush Muthukumar
- Sneha Shah
- Neha Kunjal
- Emily Marx (now Berkeley Ph.D. student)
- Dan Iter (now
Stanford Ph.D. studentMicrosoft Research) - Jestin Ma (now IXL Learning)
- Henri Stern (now Privy)
- Emre Orbay (now Nvidia)
- Brennan Shacklett (now Stanford Ph.D. student)
- William Zeng (now Google)
- Katie Wu (now Scale AI)
- Charles Sheelam
- Kevin Song
Teaching
In the Winter 2023 term, I taught a section of Stanford's newfirst-year class on "Citizenship in the 21st Century."I have also taught CS 144: Introduction to Computer Networking, CS 181/181W: Computers, Ethics, and Public Policy, a first-year seminar (CS 81N: Hackers and Heroes), a graduate networking seminar (CS 344G: Network Application Studio), CS 244: Advanced Topics in Networking, and CS 349T / EE 192T: Video and Audio Technology for Live Theater in the Age of COVID.
Writing
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“What advice would you give to a young woman in high school considering computer science?” Advice on the CS faculty interview, February 2017. Things other people told me that proved helpful.Stock advice for undergraduates interested in doing a Ph.D. in computer science The N=2 Interview about Ph.D.s in Computer Science, August 2015. Discussion with Phil Guo (UC San Diego) and Eugene Wu (Columbia).Introducing the ‘right to eavesdrop on your things’, Politico The Agenda, June 29, 2015. Proposing that owners of electronic devices be able to listen in on what their own things are saying about them. (Later an academic paper.)How does an investigative reporter get started?, Oct. 16, 2011.What is the difference between Bayesian and frequentist statistics?, June 13, 2010.... 3G and Me, Aug. 19, 2010.A Simple Health-Care Fix Fizzles Out, The Wall Street Journal, page A1, Feb. 11, 2010. About the muted effect of comparative-effectiveness trials on U.S. clinical practice. Medicine's Dangerous Guessing Game: The Wall Street Journal, Sept. 9, 2009. A biotechnology company used a statistical method to describe the rate of side effects of a drug that was likely to underestimate the true rate. (Later said better in an academic paper by Julian Borchardt.)Boston Scientific Stent Study Flawed, The Wall Street Journal, page B1, August 14, 2008, with the accompanying statistical notes. A medical-device manufacturer used an inaccurate, but favorable, approximation in the primary endpoint analysis of a pivotal medical trial for a billion-dollar coronary stent. The error in the approximation was enough to alter the result of the trial across the prespecified p<0.05 threshold. Coverage by Knight Science Journalism Tracker and theheart.org. Why the U.S. Wants To End the Link Between Time and Sun; Astronomers Say Wait a Sec, Sundials Would Be Passé; Mean Blow to Greenwich, The Wall Street Journal, page A1, July 29, 2005. The story that blew the lid off the secret U.S. government plot to make all minutes last the same amount of time. In the fall of 2004, we did one of the first day-by-day electoral odds models in the MIT student newspaper, The Tech. A April 2004 interview with Jack Valenti, then head of the Motion Picture Association of America. He swears. A November 2002 article revealing intrigue and lucre in MIT's participation on the HDTV Grand Alliance. Answers from Quora. |
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Research
November 2024: | Reducing WebAssembly's RAM overheads to (close to) the bare minimum. Joint work with Dominik Tacke and our wasm2c/WABT co-contributors. | ||||
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June 2023: | "Four Steps to the Apocalypse": A talk at the 60th anniversary of MIT's Project MAC and 20th of the creation of MIT CSAIL---focusing on alternative "existential" threats from AI (sociological, disciplinary, and "consolidationalist"). | ||||
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August 2022: | Sadjad Fouladi, Brennan Shacklett, Fait Poms, Arjun Arora, Alex Ozdemir, Deepti Raghavan, Pat Hanrahan, Kayvon Fatahalian, and KW,R2E2: Low-latency Path Tracing of Terabyte-scale Scenes Using Thousands of Cloud CPUs, SIGGRAPH 2022.Sadjad, Brennan, and co-authors created a gigantic ray-tracing engine using swarms of thousands of cloud CPUs fired up in a few seconds, in order to render truly gigantic film-scale scenes (with a terabyte of geometry and texture data) interactively on demand. | ||||
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March 2021: | Working with my student Sadjad Fouladi, and our collaborators Michael Rau (Theater and Performance Studies), Tsachy Weissman (EE), and Dustin Schroeder (Geophysics), we operationalized Sadjad's earlier “Salsify” research into "Stagecast," an effort to produce the best possible videoconferencing system for live theater and music during the pandemic.In the fall of 2020, we co-taught a class for undergraduates and master's students:CS 349T / EE 192T: Video and Audio Technology for Live Theater in the Age of COVID where our students developed out the system into a usable tool. Then in the winter of 2021, we rehearsed and eventually heldthree live performances in March 2021, including four new plays performed by a cast of five student actors, plus three musical numbers performed by members of the Wet Ink Ensemble from New York City. The performances were enabled by a backstage crew of seven student technicians who used our software to adjust camera focus/framing/brightness, audio levels, and shot selection in real time, advised by the instructional staff from the TAPS department.One innovation in the Stagecast system is a new media transport protocol that allows multiple reconstructions of the same incoming stream of packets. Each musician sends out their audio (ideally) once over a reliable transport protocol. The priority of original vs. retransmitted packets is sensitive to the low-latency needs of the stream. At the receiver side, the stream is reconstructed multiple times with different latency thresholds: once to produce a low-latency (but low-tolerance-for-jitter) feed, and again 100 ms later to produce a higher-latency, higher-quality version of the same incoming packets. The first feed goes to the other musicians; the second feed is used by the backstage mixers and eventually for the audience. | ||||
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February 2020: | Francis Y. Yan, Hudson Ayers, Chenzhi Zhu, Sadjad Fouladi, James Hong, Keyi Zhang, Philip Levis, and KW,Learning in situ: a randomized experiment in video streaming, Usenix NSDI 2020, Santa Clara, Calif., 2020 (won Community Award and Applied Networking Research Prize).Francis and our co-authors set up a website that streamed 38+ years of video to 63,500+ users over the course of a year; we found that variability, and therefore statistical uncertainty, is bigger than had been documented (calling into question the reliability of some past research in this area), and that "dumb" ABR schemes may be able to outperform some more-sophisticated schemes. We describe a way of learning in place (in situ) that appears to alleviate, at least partly, some of the pitfalls that have afflicted other ML approaches. The website is still live, and we welcome contributions from researchers who would like to evaluate or develop new algorithms for ABR selection, throughput prediction, or congestion control. We also welcome contributions from viewers who would like to contribute to the experiments by watching TV. | ||||
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July 2019: | Sadjad Fouladi, Francisco Romero, Dan Iter, Qian Li, Shuvo Chatterjee, Christos Kozyrakis, Matei Zaharia, and KW,From Laptop to Lambda: Outsourcing Everyday Jobs to Thousands of Transient Functional Containers, USENIX ATC, Renton, Wash., 2019.Framework to "functionalize" everyday tasks (e.g., software compilation, unit tests, video encoding, object recognition, ...) and, with their data-dependencies well-described, offload them efficiently to quick bursts of 5,000+ lambda functions executing in parallel. Imagine expressing workflows in, auto-converting existing workflows into, a sort of Parallel-Haskell-like representation. This paper tries to bust the myths that S3 is slow for small files (it depends on the client implementation), lambdas are slow to start en masse (it depends on the client implementation) and that AWS Lambda forbids direct network communication between workers (NAT-traversal techniques can connect them). More practical info is in the followup paper in Usenix ;login: magazine. | ||||
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April 2018: | Sadjad Fouladi, John Emmons, Emre Orbay, Catherine Wu, Riad S. Wahby, and KW, Salsify: low-latency network video through tighter integration between a video codec and a transport protocol, in USENIX NSDI ’18, Renton, Wash., April 2018 (won Applied Networking Research Prize). Salsify is a new design for real-time Internet video that jointly controls a video codec and a network transport protocol. Current systems (Skype, Facetime, WebRTC) run these components independently, which produces more glitches and stalls when the network is unpredictable. In testing, Salsify consistently outperformed today’s real-time video systems in both quality and delay. | ||||
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November 2017: | Michael Schapira and KW, Congestion-Control Throwdown, ACM HotNets, Palo Alto, Calif., November 2017.Michael (as Hamilton) and I (Burr) were stuck on an airplane together and found ourselves at loggerheads about Internet congestion control. We put our disagreement to good use by collaborating on a throwdown-in-the-form-of-a-paper (and later an actual throwdown, at HotNets 2017). | ||||
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October 2016: | In 2007, an academic cardiologist downloaded 42 medical studies from the Web site of drug giant GlaxoSmithKline, combined them in a meta-analysis, and found that Avandia, the world's best-selling diabetes drug, caused heart attacks. GSK lost about $12 billion in sales and market value. But a different way to analyze the same data—a “Bayesian” way—finds that the drug actually reduces heart attacks. Or does it?We often hear of this conflict, between Bayesian and “frequentist” statistics. But much of the conflict is misguided. Viewed formally, on the same axes, the two schools of statistics turn out to share a tight symmetry. Criticisms of each can be transformed into a corresponding criticism of the other. Slides from talk given at University of Chicago (January 2009), U.T. Austin (April 2011), MIT CSAIL (October 2013), Boston Children's Hospital (October 2013), Harvard Medical School (February 2014), MongoDB Inc. (October 2016). Also written version of the main section of the talk. | ||||
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May 2014: | My doctoral dissertation: Transport Architectures for an Evolving Internet, advised by Hari Balakrishnan at the Massachusetts Institute of Technology, 2014. | ||||
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August 2013: | TCP ex Machina: Computer-Generated Congestion Control, in SIGCOMM 2013, Hong Kong, China, August 2013. Remy is a computer program that creates TCP congestion-control algorithms from first principles, given uncertain prior knowledge about the network and an objective to achieve. I used to say that these computer-generated schemes can outperform their human-generated forebears, even ones that benefit from running code inside the network—I should have been equally emphatic that it matters a lot how the designer specifies their assumption and how closely those assumptions are met by the real network. The real contribution here, I think, was in the idea that the design of a CC algorithm can be the product of reinforcement learning: a process where the emphasis is appropriately on the designer's assumptions and goals, and less-so on the mechanism. (Joint work with my advisor, Hari Balakrishnan.) | ||||
April 2013: | Sprout: Stochastic Forecasts Achieve High Throughput and Low Delay over Cellular Networks, in USENIX NSDI 2013, Lombard, Ill., April 2013 (won 2014 Applied Networking Research Prize). We showed that on today's cellular networks, with some simple inferential techniques it is possible to achieve 7–9× less delay than Skype, Facetime, and Google Hangout, while achieving 2–4× the throughput of these applications at the same time. We packaged the evaluation into one VM and held a contest for 40 students to try to find a better algorithm on the same conditions. We were able to match the performance of the in-network CoDel algorithm, while operating purely end-to-end. (Joint work with my colleague Anirudh Sivaraman and Hari Balakrishnan.) | ||||
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Interview 2 | Radio interview | ||
June 2012: | Mosh: An Interactive Remote Shell for Mobile Clients, in USENIX ATC 2012, Boston, Mass., June 2012. We built a novel datagram protocol that synchronizes the state of abstract objects over a challenged, mobile network. We used this to implement a replacement for the venerable SSH application that tolerates intermittent connectivity and roaming, and has a predictive local user interface. The program is in wide release with hundreds of thousands of downloads. Joint work with Hari Balakrishnan (research) and with Keegan McAllister, Anders Kaseorg, Quentin Smith, and Richard Tibbetts (software). | ||||
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January 2006: | MIT OpenCourseWare taped my 8-hour Introduction to Copyright Law course, which I taught for the EECS department in MIT's Independent Activities Period of 2006. | ||||
2005–6: | We were involved in some of the first “amateur” high-definition broadcasting, which required implementing anATSC-conforming scheduler for MPEG-2 transport streams. The project is probably most notable for producing this three-hour video of the 2006 MIT Integration Bee. Other videos of 2005–6 era MIT sports arealso available. | ||||
October 2004: | Created the Library Access to Music Project, which served as MIT's open-access electronic music library 2004 to 2016. (Joint work with Josh Mandel.) Engineering a Campus-Wide Accessible Music Library (MIT master's thesis, 2005). Coverage in NYT | USA Today | Boston Globe | NPR Morning Edition | Fark. | |
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March 2001: | Wired | The Tech | New Yorker | Wall Street Journal. | |
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December 1998: | The first automated linguistic steganography. |