Center for Research on Computation and Society
School of Engineering and Applied Sciences
110 Maxwell-Dworking Laboratory
Initial of first name plus full last name AT seas DOT harvard DOT edu
I'm a postdoctoral fellow at the Center for Research on Computation and Society at
the School for Engineering and Applied Sciences at Harvard University,
under the supervision of the brilliant prof. Salil Vadhan.
Before joining Harvard, I was a Research Fellow at the Theoretical Foundations of Big Data program at
Simons Institute for the Theory of Computing.
I completed my PhD in computer science from Carnegie Mellon University,
advised by the ingenious-as-a-gross-understatement prof. Avrim Blum.
I got my M.Sc in computer science from the Weizmann Institute of Science,
where I had the honor of being advised by prof. Oded Goldreich.
I have a B.Sc Hebrew University in Jerusalem,
Israel, where I was fortunate to work with prof. Nati Linial as part of the
sgh Amirim honors program.
My research interests lie in broad theoretical computer science.
My work includes projects in approximation algorithms, machine learning in general and clustering in particular,
algorithmic game theory and privacy. Differential privacy has been the focus of my research in last years. I am a proud
member of the Privacy Tools for Sharing Research Data project.
In Fall 2014, together with prof. Kobbi Nissim, I am teaching a course on differential privacy.
This is a graduate-level course, open to undergraduate students as well.
Or Sheffet and
Salil Vadhan, WINE 2014.
Learning Mixture of Ranking Models,
Or Sheffet and
Aravindan Vijayaraghavan, NIPS 2014.
Based on “Learning Mixture of Mallows Models”, in Workship on Spectral Learning, NIPS 2013.
Optimizing Password Composition Policies, Jeremiah Blocki, Saranga Komanduri, Ariel Procaccia and Or Sheffet, EC 2013.
Differentially Private Analysis of Social Networks via Restricted Sensitivity, Jeremiah Blocki, Avrim Blum, Anupam Datta and Or Sheffet, ITCS 2013.
The Johnson-Lindenstrauss Transform Itself Preserves Differential Privacy, Jeremiah Blocki, Avrim Blum, Anupam Datta and Or Sheffet, FOCS 2012.
Additive Approximation for Near-Perfect Phylogeny Construction, Pranjal Awasthi, Avrim Blum, Jamie Morgenstern and Or Sheffet, APPROX-RANDOM 2012.
Paper. (Full version.)
Improved Spectral Norm Bounds for Clustering, Pranjal Awasthi and Or Sheffet, APPROX-RANDOM 2012.
Paper. (Full version.)
Predicting Preference Flips in Commerce Search, Samuel Ieong, Nina Mishra and Or Sheffet, ICML 2012.
Optimal Choice Functions: A Utilitarian View, Craig Boutilier, Ioannis Caragiannis, Simi Haber, Tyler Lu, Ariel Procaccia and Or Sheffet, EC 2012.
Send Mixed Signals – Earn More, Work Less, Peter Bro Miltersen and Or Sheffet, EC 2012.
Center-based Clustering under Perturbation Stability, Pranjal Awasthi, Avrim Blum and Or Sheffet, Information Processing Letters, 112(1-2).
Stability Yields a PTAS for k-Median and k-Means, Pranjal Awasthi, Avrim Blum and Or
Sheffet, FOCS 2010.
On Nash-Eqilibria of Approximation-Stable Games, Pranjal Awasthi, Nina Balcan, Avrim
Blum, Or Sheffet and Santosh Vempala. SAGT 2010.
Paper. Journal Version (for general audience).
Improved Guarantees for Agnostic Learning of Disjunctions, Pranjal Awasthi, Avrim Blum and Or Sheffet, COLT 2010.
On the Randomness Complexity of Property Testing, Oded Goldreich and Or Sheffet,
Journal of Computational Complexity 19 (2), 2010. Originally appeared in Approx/Random 2007.
(Based on my M.Sc. thesis: “Reducing the Randomness Complexity of Property Testing, with an Emphasis on Testing Bipartiteness”.)
Graph Coloring with No Large Monochromatic Components, Nathan Linial, Jiri Matousek, Or Sheffet and Gabor Tardos, Journal of Combinatorial Theory Series B 17 (4), 2008.
Originally appeared in Eurocomb 2007.
(Based on my “Amirim” Honors program final project: “On Ramsey Type Problems in Graphs, and the Largest Monochromatic Connected Component in a 2-Edge-Coloring of a Graph.”)
In case you are interested...
You can read my thesis, or a few of my all time favorite quotes.