Curriculum vitae

Iman YeckehZaare

Postdoctoral Associate, MIT Center for Collective Intelligence · Head of Research, Honor Education · Volunteer Founder, 1Cademy

Office: 1 Main Street, 9th Floor, Cambridge, MA 02142

Updated

Research profile

I study how people build and use knowledge together, how writing and learning systems support that work, and how AI assistance should be evaluated. My research combines system design, field and laboratory experiments, and qualitative analysis, with projects on shared educational notes, practice incentives, expert contribution, and AI-assisted revision. I am a Postdoctoral Associate at MIT's Center for Collective Intelligence, Head of Research at Honor Education, and founder of 1Cademy, which I maintain on an entirely voluntary basis.

Current appointments

  • Postdoctoral Associate

    Massachusetts Institute of Technology, Center for Collective Intelligence

    Cambridge, MA · Sep 2024 - present

    • Develop ontology-review, data, and evaluation workflows for the Work Activity Ontology and related studies of AI and work.
    • Coordinate implementation with two software developers and contribute to human–AI evaluation tools and the Where can AI be used? research team.

  • Head of Research

    Honor Education

    Remote · May 2022 - present

    • Set research priorities for graph-based learning, AI-assisted research tools, and human–AI evaluation.
    • Supervise two software developers and work with product and design colleagues to translate research prototypes into testable learner-facing systems.

  • Volunteer Founder

    1Cademy Research Communities

    Winter 2020 - present

    • Maintain and study 1Cademy's shared notes, prerequisite links, and learning pathways in an entirely voluntary founder role.
    • The community has included 2,011 contributors from 267 institutions and produced 72,268 nodes connected by 374,166 prerequisite links.

Education

  • Ph.D. in Information

    University of Michigan School of Information

    Ann Arbor, MI · Sep 2015 - Dec 2023

    • Dissertation: Harnessing Micro-Topics Arranged in Learning Pathways for Spaced Retrieval, Reading, and Collaborative Note-taking. Advisor: Paul Resnick. Committee: Paul Resnick (chair), Eytan Adar, Priti Shah, Christopher Brooks.

  • M.S. in Information

    University of Michigan School of Information

    Ann Arbor, MI · Sep 2012 - Dec 2014

    • Specializations: Human-Computer Interaction and Information Economics for Management.

  • B.E. in Information Technology, First-Class Honors

    Iran University of Science and Technology

    2011

  • B.E. in Computer Engineering, First-Class Honors

    Iran University of Science and Culture

    2010

Peer-reviewed journal articles and conference papers

  1. YeckehZaare, I.; Resnick, P. (2025). Counting days is a spacing incentive that unlocks the potential of low GPA students. npj Science of Learning, 10, Article 35.

  2. Chen, Y.; Farzan, R.; Kraut, R.; YeckehZaare, I.; Zhang, A. F. (2023). Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia. Management Science, 70(5), 3264-3280 (2024 issue; published online 2023).

  3. YeckehZaare, I.; Chen, S.; Barghi, T. (2023). Reducing Procrastination Without Sacrificing Students' Autonomy Through Optional Weekly Presentations of Student-Generated Content. SIGCSE.

  4. YeckehZaare, I.; Mulligan, V.; Ramstad, G. V.; Resnick, P. (2022). Semester-level Spacing but Not Procrastination Affected Student Exam Performance. LAK.

  5. YeckehZaare, I.; Aronoff, C.; Grot, G. (2022). Retrieval-based Teaching Incentivizes Spacing and Improves Grades in Computer Science Education. SIGCSE.

  6. YeckehZaare, I.; Grot, G.; Dimovski, I.; Pollock, K.; Fox, E. (2022). Another Victim of COVID-19: Computer Science Education. SIGCSE, 913-919.

  7. YeckehZaare, I.; Fox, E.; Grot, G.; Chen, S.; Walkosak, C.; Kwon, K.; Hofmann, A.; Steir, J.; McGeough, O.; Silverstein, N. (2021). Incentivized Spacing and Gender in Computer Science Education. ICER, 18-28.

  8. YeckehZaare, I.; Barghi, T.; Resnick, P. (2020). QMaps: Engaging Students in Voluntary Question Generation and Linking. CHI.

  9. YeckehZaare, I.; Resnick, P.; Ericson, B. (2019). A Spaced, Interleaved Retrieval Practice Tool that is Motivating and Effective. ICER.

  10. YeckehZaare, I.; Resnick, P. (2019). Speed and Studying: Gendered Pathways to Success. SIGCSE, 693-698.

  11. Chen, Y.; YeckehZaare, I.; Zhang, A. F. (2018). Real or bogus: Predicting susceptibility to phishing with economic experiments. PLOS ONE, 13(6), e0198213.

Dissertation

  1. YeckehZaare, I. (2024). Harnessing Micro-Topics Arranged in Learning Pathways for Spaced Retrieval, Reading, and Collaborative Note-taking. Ph.D. dissertation, University of Michigan.

Workshop papers and extended abstracts

  1. YeckehZaare, I.; Fox, E.; Wood, S.; Grot, G. (2021). Improving Collaborative Notetaking Through Finding and Visualizing Prerequisite Knowledge Links. ACM Collective Intelligence Conference (CI 2021). Nonarchival extended abstract.

  2. Ericson, B.; YeckehZaare, I.; Guzdial, M. (2019). Runestone Interactive Ebooks: A Research Platform for On-line Computer Science Learning. SPLICE Workshop at ICER. Workshop paper.

Accepted manuscripts

  1. Iman YeckehZaare (2026). Measuring Proof Burden in Public Bounty Listings: A RentAHuman Case Study. Accepted at ACM HCOMP 2026.

Submitted manuscripts

  1. Iman YeckehZaare (2026). Making Small Explanations Useful Together: What Shared Notes Support in 1Cademy. Submitted to CHI 2027.

  2. Iman YeckehZaare (2026). Suggest, Guide, Rewrite: Comparing Forms of AI Writing Assistance. Submitted to CHI 2027.

  3. Iman YeckehZaare; Benjamin S Brown; Louwis Truong; Tirdad Barghi; Sit Wai (Jeffery) Phonn; Abdessamad Ouhra Ali (2026). Keeping the Reason Behind the Label: What Self-Coded Presentation Feedback Supports. Submitted to CHI 2027.

  4. YeckehZaare, I. (2026). Topic-Mixing as an Algorithmic Practice Scheduler: Behavioral Evidence from a Randomized Field Experiment. Submitted to Journal of Learning Analytics.

Preprints

  1. Cai, A.; YeckehZaare, I.; Sun, S.; Charisi, V.; Wang, X.; Imran, A.; Laubacher, R.; Prakash, A.; Malone, T. (2026). Where can AI be used? Insights from a deep ontology of work activities. arXiv:2603.20619. Preprint.

Working manuscripts and work in preparation

  1. YeckehZaare, I. (2026). StrictParity-GraphAudit: When Graph Retrieval Gains Do Not Become RAG Context Gains. Working manuscript.

  2. YeckehZaare, I. (2026). Placing Before Posting: Contribution-Time Structural Placement in Collaborative Knowledge Production. Working manuscript.

  3. YeckehZaare, I. (2026). ConceptualGrader: Interactive Provenance and Eligibility Techniques for Auditing Large Language Models in Grading. Working manuscript.

  4. Chen, Y.; Mostagir, M.; YeckehZaare, I. Strategic Experimentation and Information Design in Dynamic Contests: An Experimental Study. Working manuscript.

  5. YeckehZaare, I.; Barghi, T.; Cai, J.; Brown, B.; Truong, L.; Resnick, P. Fragmenting Study Materials into Multi-Page Concept Maps Impairs Delayed Recognition. In preparation.

  6. Scalable expert oversight of ontology revision without objective ground truth. Study design and deployed review workflow in progress.

  7. YeckehZaare, I. (2026). The Epistemic Triad: Auditing Participant-Endorsed Selections in Hybrid Human-LLM Coding. Working draft.

Teaching experience

  • Graduate Student Instructor

    University of Michigan School of Information

    2017-2021

    • Courses included Machine Learning and Deep Learning, Advanced Web Development, Programs, Information, and People, and Data Exploration.

Awards and honors

  • CI 2026 Outstanding Reviewer, ACM Collective Intelligence Conference, 2026.
  • Wikimedia Foundation Research Award of the Year, 2025, for "Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia."
  • Outstanding Graduate Student Instructor of the Year, University of Michigan School of Information, 2018-2019.
  • Learning Levers, 2019, 3rd Prize; Innovation in Action, 2018, 2nd Prize; Michigan Collegiate Innovation Prize, 2013.

Professional service and peer review

  • Reviewed multiple papers for ACM Collective Intelligence (CI) and HCOMP; additional conference reviewing includes CHI Papers (2024-2026), LAK 2025, CSCW 2026, DIS, IDC, IMX, and IUI.
  • Journal reviewer for Computers & Education and Studies in Educational Evaluation.
  • Recognized for an outstanding review for CHI 2024 Papers.

Methods and technical work

  • Field and lab experiments, mixed methods, human-AI evaluation, knowledge graphs, Python, R, JavaScript/React, PostgreSQL, Firebase, and LLM workflow orchestration.