Haoqi Zhang


Assistant Professor
Ford 2.320, 2.325

Delta Lab
Segal Design Institute 
Technology & Social Behavior

Current and Recent Works


Pair Research: Matching People for Collaboration, Learning, and Productivity. [PDFnew!
Robert C. Miller, Haoqi Zhang, Eric Gilbert, and Elizabeth Gerber.
To appear in CSCW '14, Baltimore, 2014.

Community clustering: Leveraging an academic crowd to form coherent conference sessions. [PDFDemonew!
Paul Andre, Haoqi Zhang, Juho Kim, Lydia B. Chilton, Steven P. Dow, and Robert C. Miller.
In HCOMP '13, Palm Springs, 2013.
notable paper award

Cobi: A Community-Informed Conference Scheduling Tool [PDFProject Overview & Demonew!
Juho Kim, Haoqi Zhang, Paul André, Lydia Chilton, Wendy MacKay, Michel Beaudouin-Lafon, Robert C. Miller, Steven P. Dow.
In UIST '13, St Andrews, 2013.

Automated Workflow Synthesis [PDFnew!
Haoqi Zhang, Eric Horvitz, and David Parkes.
In AAAI '13, Bellevue, 2013.

Cobi: Communitysourcing Large-Scale Conference Scheduling [PDFProject Overview & Demo
Haoqi Zhang, Paul André, Lydia Chilton, Juho Kim, Steven P. Dow, Robert C. Miller, Wendy MacKay, and Michel Beaudouin-Lafon.
Demo at CHI Interactivity, 2013.

Computational Environment Design
Haoqi Zhang
Dissertation, Harvard University, 2012.


Other Publications

Hallucination: a Mixed-Initiative Approach for Efficient Document Reconstruction [PDFslidesvideo
Haoqi Zhang, John Lai, and Moritz Baecher.
In HCOMP '12, Toronto, 2012.

Human Computation Tasks with Global Constraints[PDFslidesvideo
Haoqi Zhang, Edith Law, Krzysztof Gajos, Eric Horvitz, Rob Miller, and David Parkes.
In CHI '12, Austin, 2012. 
honorable mention for best paper 

Task Routing for Prediction Tasks [PDFslides
Haoqi Zhang, Eric Horvitz, Yiling Chen, and David Parkes.
In AAMAS '12, Valencia, Spain, 2012. 
Earlier version [PDFslides] appeared at the ACM EC Workshop on social computing & user-generated content, 2011.

TurkServer: Enabling Synchronous and Longitudinal Online Experiments [PDF
Andrew Mao, Yiling Chen, Krzysztof Gajos, David Parkes, Ariel Procaccia, and Haoqi Zhang
In HCOMP '12, Toronto, 2012. 

Economics of BitTorrent Communities [PDFslides,interview
Ian Kash, John Lai, Haoqi Zhang, and Aviv Zohar.
In WWW '12, Lyon, France, 2012. 
Earlier version [PDFslides] appeared at the ACM EC workshop on NetEcon, 2011.

PlateMate: Crowdsourcing Nutrition Analysis from Food Photographs.[PDFslides
Jon Noronha, Eric Hysen, Haoqi Zhang, and Krzysztof Z. Gajos.
In UIST '11, Santa Barbara, 2011.

Towards Large-Scale Collaborative Planning: Answering High-Level Search Queries Using Human Computation [PDFslides
Edith Law and Haoqi Zhang.
In AAAI '11, San Francisco, 2011.

An Iterative Dual Pathway Structure for Speech-to-Text Transcription[PDFslides
Beatrice Liem, Haoqi Zhang, and Yiling Chen.
In HCOMP '11 (held at AAAI), San Francisco, 2011.

Crowdsourcing General Computation [PDF
Haoqi Zhang, Eric Horvitz, Rob Miller, and David C. Parkes.
In the CHI 2011 workshop on crowdsourcing and human computation, 2011.
Also available as MSR technical report MSR-TR-2011-6.

Incentive Design for Adaptive Agents [PDFslides
Yiling Chen, Jerry Kung, David Parkes, Ariel Procaccia, and Haoqi Zhang.
In AAMAS '11, Taipei, Taiwan, 2011.

Toward Automatic Task Design: A Progress Report [PDFslides
Eric Huang, Haoqi Zhang, David Parkes, Krzysztof Gajos, and Yiling Chen.
In KDD-HCOMP'10, Washington, DC, 2010.

Policy Teaching Through Reward Function Learning [PDFslides]
Haoqi Zhang, David C. Parkes, and Yiling Chen.
In the 10th ACM Electronic Commerce Conference (EC'09), Stanford, CA, 2009.

A General Approach to Environment Design with One Agent [PDF,slides]
Haoqi Zhang, Yiling Chen, and David C. Parkes.
In the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), Pasadena, CA, 2009.

Strong Activity Rules for Iterative Combinatorial Auctions [PDF]
Pavithra Harsha, Cynthia Barnhart, David C. Parkes, and Haoqi Zhang.
In Computers & Operations Research, 2009.

Value-based Policy Teaching with Active Indirect Elicitation [PDF,slides]
Haoqi Zhang and David C. Parkes.
In the 23rd AAAI Conference on Artificial Intelligence (AAAI'08), Chicago, IL, 2008 
accepted for oral & poster presentation

Enabling Environment Design via Active Indirect Elicitation [PDFslides]
Haoqi Zhang and David C. Parkes.
In the 4th Multidisciplinary Workshop on Advances in Preference Handling, Chicago, IL, 2008.

Policy Teaching through Reward Function Learning [PDF]
Haoqi Zhang
Undergraduate thesis, Computer Science and Economics, Harvard College, 2007 (Hoopes Prize Winner).

HaoqiI am a foodie. Contact me about restaurant recommendations. 





CS 101: An Introduction to Computer Science for Everyone

From US National Library of Medicine (CS 101 poster: small/large)








Instructor: Haoqi Zhang
Lectures: Monday and Wednesday, 3-3:50, Pancoe Building, Abbot Auditorium.

Office Hours:

  • Haoqi: Monday, 4-5pm, Ford 2-325 (or by appointment).
  • Darrell: Monday 10-11am, Ford 3-333 (or by appointment).
  • Chandra: Tuesday, 2-3pm, Ford 3-211 (or by appointment).

Teaching Assistants:

  • Chandra Sekhar Bhagavatula. email
  • Darrell Hoy. email

Sections: on Friday at

  • 1PM, Tech LG62 (Chandra)
  • 2PM, Tech LG62 (Chandra)
  • 3PM, Tech LG68 (Chandra)
  • 1PM, Tech L168 (Darrell)
  • 2PM, Tech L170 (Darrell)
  • 3PM, Tech L170 (Darrell)

Online Discussion: on piazza

Course Description

Computation is ubiquitous: DNA contains biological programs and is a part of all lifeforms, the human brain is a powerful computer, and the digital computer has revolutionized most aspects of our society. The primary goal of this course is to explore the whats, whys, and hows of computer science.

CS 101, a conversation (video, click to watch)

The topics covered include the theory of computation (what computers can compute), algorithms for efficient computation (what to tell a computer to compute), programming languages (how to tell a computer what to compute), artificial intelligence (how your computer can do things your brain does), computational biology (how DNA-based biological systems are like programs), computer systems (e.g., how computers work together in networks like the Internet), computer vision and graphics (how computers can gather and convey useful visual information) and human computer interaction (easy, natural ways to get what you need and want from computers).

In this course, students will learn what the computer science major is all about. Coursework will be reading and writing about computer science topics and their impact in the world. There will be no computer programming in this course.

This course is a Core course in the Computer Science Curriculum and also satisfies the Weinberg Area III (Social and Behavioral Sciences) Distribution. The target audience of this course is freshmen and sophomores; advanced students can satisfy the computer science major's 101 requirement by instead taking an additional breadth course.

CS 101 Instructors

Guest Instructors

This course surveys many topics in computer science and lectures will be given by Northwestern professors who research and teach advanced courses in these topics. Instructors include Prof. Haoqi Zhang, Prof. Jason Hartline, Prof. Fabian Bustamante, Prof. Bryan Pardo, Prof. Nicole Immorlica, Prof. Mike Horn, Prof. Ronen Gradwohl, Prof. Robby Findler, Prof. Ollie Cossairt, and Prof. Ian Horswill.

Reading and Media

Reading and media viewing assignments (see: weekly schedule) will be taken from popular press and computer science journals. Sources include: The Atlantic, The Economist, WIRED, Communications of the ACM (CACM), TED Talks, XRDS: the ACM student magazine, The Huffington Post, The New York Times, and Scientific American. Reading materials can be downloaded individually from their respective sources.

Attendance, Participation, and Grading

Attendance of and participation in lectures and discussion sections is mandatory.

  • Students should complete reading assignments and submit their answers to the discussion question before each class.
  • Students should contribute to classroom discussions by asking and answering questions and (when asked) providing discussion of lecture topics and reading assignments.
  • Students should participate in discussion sections by being involved in activities during the discussion section and in out-of-section followup work.
  • Students should participate in online discussion on piazza. Possible online contributions include relating assigned reading and lecture material to current events, culture, and articles in popular media and discussion thereof.

Grades will be weighted as follows: 40% assignments, 20% participation, 20% Midterm, and 20% final (subject to change). 

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