Hi, I'm Shlomi.

shlomi <AT> bu <DOT> edu

(Anonymous) feedback welcome.

I’m looking for an intern position as Responsible AI researcher/data scientist (e.g., fairness, interpretability, privacy) for summer 2022. Please reach out!

Do you teach Responsible AI? Join to our workshop on Jan 10, 2022, at Tel-Aviv University [link]!

I’m a second-year CS Ph.D. student at Boston University, being supervised by Prof. Ran Canetti.

I’m interested in Responsible AI, particularly:

  1. Societal impact of algorithms and machine learning systems
  2. Interpretable machine learning
  3. Differentially private synthetic data for government data

I’m also an Associated Researcher at the Alexander von Humboldt Institute for Internet and Society (HIIG) in Berlin. In summer 2019, I did a research internship at the Center for Human-Compatible AI at UC Berkeley, working on neural network interpretability.

For the last two years, I teach courses in Responsible AI, Law, Ethics & Society in various institutes including Cornell Tech, Tel Aviv University and the Technion. Occasionally, I’m consulting for startups and companies with data science projects.

In my previous life, I was a social entrepreneur - co-founder of the Israeli Cyber Education Center. There I led the development of nationwide educational programs in computing for kids and teens. The center aims to increase the social mobility of underrepresented groups in tech, such as women, minorities, and individuals from the suburbs of Israel. I co-authored a Computer Network textbook in a tutorial approach (in Hebrew). I taught also a new academic course on Problem Solving using Python. Before that, I was an algorithmic research team leader in cybersecurity.


Shlomi Hod, Karni Chagal-Feferkorn, Niva Elkin-Koren and Avigdor Gal. “Data Science Meets Law: Learning Responsible AI Together”. To appeared in the Communications of the ACM (February 2022).

*Shlomi Hod, *Stephen Casper, *Daniel Filan, Cody Wild, Andrew Critch and Stuart Russell. “Detecting Modularity in Deep Neural Networks.” arXiv preprint arXiv:2110.08058 (2021).

*Daniel Filan, *Stephen Casper, *Shlomi Hod, Cody Wild, Andrew Critch, and Stuart Russell. “Clusterability in Neural Networks.” arXiv preprint arXiv:2103.03386 (2021).

*Gavin Brown, *Shlomi Hod, *Iden Kalemaj. “Performative Prediction in a Stateful World.” Appeared with a contributed talk at Workshop on Consequential Decision Making in Dynamic Environments (NeurIPS 2020).

*Daniel Filan, *Shlomi Hod, Cody Wild, Andrew Critch, and Stuart Russell. “Neural Networks are Surprisingly Modular.” arXiv preprint arXiv:2003.04881 (2020).