News in Last 12 Months
May 2020: Fawkes Image Cloaking paper to appear at USENIX SecurityCongrats to Shawn and Emily (co-first authors), Jiayun and Huiying!
Apr 2020: Kevin joins ByteDance Labsas a researcher on adversarial machine learning! Congrats Kevin!!
Apr 2020: SIGCOMM 2021 TPC
Apr 2020: CCS paper on DNN protection via TrapdoorsCongrats to Shawn, Emily, Bolun, and Bo for our paper on honeypots used to protect deep learning models
Mar 2020: CHI 2020 Honorable MentionCongrats to Jenna, Shiliang et al for Best Paper Honorable Mention Award at CHI 2020 for our paper on Detecting Gender Stereotypes
Mar 2020: CHI 2020 Honorable MentionCongrats to Yuxin, Huiying, Shan-Yuan et al for Best Paper Honorable Mention Award at CHI 2020 for our paper on Wearable Microphone Jammers
Feb 2020: IEEE S&P 2021 TPC
Feb 2020: NYTimes: Bracelets of SilenceAwesome New York Times article by Kash Hill on our ultrasonic, wearable microphone jammer! Project Page.
Feb 2020: Talks at EdConSpeaking to 900+ IL judges on AI/ML and the law
Jan 2020: IMC 2020 TPC
Jan 2020: Huiying wins Facebook Fellowship!Congrats to Huiying Li!
Jan 2020: SciTechDaily articleon our NDSS paper on adversarial location via WiFi reflection
Dec 2019: CHI paper on Wearable Ultrasonic JammersCongrats Huiying, Yuxin, Shan-Yuan!
Dec 2019: CHI paper on Gender BiasCongrats Jenna, Shiliang & Xinyi!
Nov 2019: Distinguished lecture at KAUST
Oct 2019: Huiying gives first talk @CCS!
Oct 2019: Huiying & Emily roadtripw/ talk @ Stanford & visit to Berkeley!
Sept 2019: Distinguished lecture at EPFL
Aug 2019: NDSS paper on adversarial sensingCongrats to Yanzi, Zhujun, Yuxin, Zhijing and Max!
Aug 2019: DARPA grant on evaluating adversarial ML attacks
Aug 2019: NSF grant on spectrum anomaly detectionNew project led by Heather
July 2019: Congrats to Dr. Yanzi ZhuOff to join the AR/VR team at Google. Good luck!
July 2019: Latent backdoor paper at CCSCongrats Kevin and Huiying!
July 2019: interview for CNBCArticle on AI/ML and fake news
June 2019: Senior TPC, WSDM 2019
June 2019: Congrats to our new PhDsXinyi Zhang, Shiliang Tang, and Zhijing Li! Good luck at Facebook!
June 2019: Gave fun talk to Chicago Bar Associationon advances in ML & implications on the law
Lab: 377 Crerar, Office: 369 Crerar
5730 S. Ellis Ave, University of Chicago
Chicago, IL 60637
Travel/Deadlines (UChicago Calendar)
CFP: June 11, USENIX Security 2021
CFP: Sept 3, Oakland 2021
CFP: October 15, USENIX Security 2021
CFP: December 3, Oakland 2021
CFP: February 4, 2021, USENIX Security 2021
I am a Neubauer Professor of Computer Science at University of Chicago.
Over the years, I've followed my own interests in pursuing research
problems that I find intellectually interesting and meaningful. That's led me to
work on a sequence of areas from P2P networks, online social networks, SDR/open spectrum systems, graph mining
and modeling, user behavior analysis, to adversarial machine learning. Since 2016,
I've mostly worked on security and privacy problems in machine learning and mobile systems.
My meandering interests have led me to publish at a range of top
conferences, including Usenix Security/Oakland/CCS, IMC/WWW, CHI/CSCW, and Mobicom/SIGCOMM/NSDI. Here's a wordle of my
paper abstracts from 2017-2019.
Together with Prof. Heather Zheng, I co-direct the SAND Lab (Systems, Algorithms, Networking and Data) at University of Chicago. I received my PhD in Computer Science from UC Berkeley in 2004, where I was advised by John Kubiatowicz and Anthony Joseph, and created the Tapestry distributed hash table (dissertation). I received my MS from Berkeley in 2000, and my BS in computer science from Yale in 1997. I am an ACM Distinguished Scientist, a recipient of the NSF CAREER award (2005), MIT Tech Review's TR-35 Award (Young Innovators Under 35) (2006), IEEE Internet Technical Committee's Early Career Award (2014), and one of ComputerWorld's Top 40 Technology Innovators under 40. My papers have somewhere around 28,000 citations and an H-index of 66 (for whatever that's worth). In some of my "free time," I write about research and PhD life on Quora.
Spring 2020: Tu/Th 12:30-1:50PM, Zoom, CS35401-2: Topics Seminar - Adversarial Machine Learning
Reading seminar on adversarial machine learning, primarily designed for PhD and MS students interested on research in this space. We will meet twice a week, and students will lead discussions on papers ranging from adversarial examples to poison, black-box, surrogate model attacks. We can cover both empirical papers from the security community as well as those from core ML conferences.
Press/Media: A collection of recent news and media coverage of our research.
Awesome New York Times article (by the great Kashmir Hill) on our Bracelets of Silence, an ultrasonic, wearable microphone jammer for personal privacy! Project Page.
I'm always looking for bright PhD students!!
I'm always interested in self-driven/passionate students who want to work on high impact projects and have fun doing it. UChicago is a fantastic place to do a PhD, and we're constantly making improvements to the lab and the department. To find out a bit more about me as an advisor, and my views on everything from students to research and the meaning of life, you can read some of my posts on Quora, where I've been "Top Writer" since 2014. To get on a short list of names Heather and I will look for when reviewing applications, please fill out a basic form. This is better than email. I read all my emails. But due to the volume of emails, I am often unable to reply to individual emails.
If you are looking for a summer undergraduate internship, please do not email me directly. UChicago CS has organized a summer undergraduate internship program with more info here. If you are a high school student or undergraduate looking for a summer internship related to data, you might be interested in the CDAC Data and Computing Summer Lab. SAND Lab is involved in both programs, although the number of interns we take each summer can vary depending on the applicant pool.
UChicago Undergraduates interested in research?
We generally advise 3-5 undergraduates in my lab in active research (we're now quite full for 2020). If you're interested in working in my lab as an undergrad, drop me an email. Generally speaking, the best way to join my lab as an undergrad is to take and do well in my courses in networking or applied ML.