Ben Y. Zhao

     
portrait

ravenben+www at cs dot uchicago dot edu
Twitter, Facebook, Quora, Linkedin.

News in Last 12 Months

May 2019: Article in UChicago Magazine

on online privacy & our research

May 2019: UChicago news about our backdoor work

May 2019: Congrats to Xinyi

for her SIGCOMM paper on network management!

Apr 2019: Congrats to Gang Wang

SAND Lab alumnus who just joined UIUC CS as Assistant Professor!

Mar 2019: Congrats to Zhijing, Zhujun

on their MobiHoc paper

Feb 2019: Congrats to SAND Lab alumnus Prof. Christo Wilson, Sloan Fellow 2019!!

Feb 2019: Recorded episode on UChicago Big Brains Podcast

Feb 2019: IMC 2019 TPC

Jan 2019: USENIX Security & AI Networking Conference (ScAINet) TPC

Dec 2018: SAND Lab gets new logo!

Finally!

Dec 2018: Bolun defends his PhD!

We'll miss you, good luck!

Nov 2018: Oakland 2019 paper

on detecting/reverse engineering and cleaning backdoors in DNNs

Nov 2018: NSDI 2020 TPC (heavy)

Oct 2018: SIGCOMM 2019 TPC (heavy)

Sept 2018: APNet 2019 TPC

Sept 2018: ICWSM 2018 Senior PC/Editor

Sept 2018: UChicago Magazine on Data Mind

August 2018: CSCW paper

on zero-incentive location check-ins

July 2018: Congrats to Zhijing for IMC paper

on fault analysis in NFV

June 2018: WWW 2019 Senior TPC

May 2018: WSDM 2019 Senior TPC

May 2018: joint project w/ UCB, Stanford & UIUC funded by DARPA!

on defending social engineering attacks

May 2018: Congrats to Prof. Viswanath!

Bimal accepted offer to join Virginia Tech as Assistant Professor!

May 2018: Congrats to Bolun, Yuanshun and Bimal for USENIX Security paper

on attacks against transfer learning

CODE

Clickstream modeling code here
Measurement-calibrated graphs here
Embedding graph coordinate systems here

Contact info

Lab: 377 Crerar
Office: 369 Crerar
5730 S. Ellis Ave,
University of Chicago
Chicago, IL 60637


Travel/Deadlines (UChicago Calendar)


CFP: May 13, IMC 2019
CFP: May 15, CCS 2019
CFP: May 23, NeurIPS 2019
1st of Every month, IEEE S&P
May 20-22, SF, CA, IEEE S&P (air, reg, hotel)
June 4, Chicago bar association
June 7-8, SOFC, Rosemont IL
June 10-12, Long Beach CA, ICML (reg)
June 14, UCSB Commencement/Hooding
July 2-5, Catania Italy, Mobihoc
July 18, Boston, IMC TPC Meeting
August 12, 14-16, Santa Clara, USENIX Security & ScAINet
August 19-24, Beijing China, SIGCOMM & NetAI
Oct 21-24, Amsterdam, IMC
Oct 27-29, SaTC PI meeting, Alexandria VA
CFP: Oakland, 1st of every month

Other Stuff

Google Scholar (~26,000), H-index: 63
Erdos # = 3 (Erdos-M. Saks-K. Hildrum-B. Y. Zhao)
This page, circa 2011

I am Neubauer Professor of Computer Science at University of Chicago. My research covers a range of topics from large-distributed networks and systems, HCI, security and privacy, and wireless / mobile systems, mostly from a data-driven perspective. My current projects are focused on three areas: adversarial machine learning, data-driven models of user behavior, and privacy-preserving mobile and wireless systems. My work targets a range of top conferences, including UsenixSecurity/Oakland/CCS, IMC/WWW, CHI/CSCW, and Mobicom/SIGCOMM/NSDI. Here's a wordle of my paper abstracts from 2017-2018.

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 National Science Foundation's 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 26,000 citations and an H-index of 63 (for whatever that's worth).

Teaching
Winter 2019: M/W 2:00-3:20PM, Saieh (SHFE) 021, CS 23280/Econ 23040 (Cryptocurrencies), a new course co-taught with David Cash (CS) and Harald Uhlig (Economics). This course will cover both the computer science aspects and economic aspects of cryptocurrencies. Topics to be discussed will include network and system building blocks, consensus protocols, cryptographic algorithms, security and privacy issues, pricing of cryptocurrencies, bubbles, monetary policy issues and regulatory concerns.
Winter 2019: Tu/Th 11AM-12:20AM, Hinds (HGS) 180, CS 35401 (Special Topics/Seminar: Applied Machine Learning). We will cover recent research in applied machine learning and systems, particularly with respect to questions of robustness and resilience against attacks on deep learning systems. Students will present papers, lead discussion, and run open ended projects related to the topic.

Press/Media
A collection of recent news and media coverage of our research is here.

Active data mining/OSN project pages: Clickstream behavior models, Graph Coordinate Systems, Graph Modeling/Generation, Social Network Measurement/Analysis, Detection of Social Spam and Fake Users (Sybils)

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 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. Email me to get on my radar, and mention me (or Heather) in your application. I read all my emails. But due to the volume of these requests, I might not be able to reply to your email.

UChicago Undergraduates interested in research?
I generally advise 1-3 undergraduates in my lab in active research (we have 6 already in 2017-8). If you're interested in working in my lab as an undergrad, drop by my lab at 377 Crerar and we'll talk! 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,