World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
62
Citations
14446
World Ranking
2919
National Ranking
1435

Research.com Recognitions

  • 2018 - ACM Fellow For contributions to research and education in the fields of computational and proof complexity

Overview

Toniann Pitassi is affiliated with Columbia University in the United States and focuses primarily on computer science research. Their work spans several subfields, including artificial intelligence, computational theory and mathematics, computer networks and communications, statistics and probability, and control and systems engineering.

The scientist's research topics are diverse, encompassing complexity and algorithms in graphs, logic, reasoning, and knowledge, machine learning and algorithms, formal methods in verification, cryptography and data security, constraint satisfaction and optimization, and advanced graph theory research.

Toniann Pitassi has an extensive record of publications. Among recent papers are:

  • "Size and Depth Separation in Approximating Benign Functions with Neural Networks," 2021, arXiv (Cornell University)
  • "Random \( \Theta (\log n) \) -CNFs are Hard for Cutting Planes," 2022, Journal of the ACM
  • "On the Power and Limitations of Branch and Cut," 2021, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • "On the Pseudo-Deterministic Query Complexity of NP Search Problems," 2021, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • "Theoretical bounds on estimation error for meta-learning," 2020, arXiv (Cornell University)

The publication venues where Toniann Pitassi frequently appears include:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Computational Complexity
  • Journal of the ACM
  • SIAM Journal on Computing

Collaborative work is a significant aspect of Toniann Pitassi's research, with frequent coauthors including:

  • Noah Fleming
  • Robert Robere
  • Richard S. Zemel
  • Or Meir
  • Russell Impagliazzo

In 2018, Toniann Pitassi was recognized as an ACM Fellow for contributions to research and education in the fields of computational and proof complexity.

Best Publications

  • Fairness through awareness

    Cynthia Dwork;Moritz Hardt;Toniann Pitassi;Omer Reingold

  • Differential privacy under continual observation

    Cynthia Dwork;Moni Naor;Toniann Pitassi;Guy N. Rothblum

  • Learning Adversarially Fair and Transferable Representations

    David Madras;Elliot Creager;Toniann Pitassi;Richard S. Zemel

  • The reusable holdout: Preserving validity in adaptive data analysis

    Cynthia Dwork;Vitaly Feldman;Moritz Hardt;Toniann Pitassi

  • Lower bounds for cutting planes proofs with small coefficients

    Maria Luisa Bonet;Toniann Pitassi;Ran Raz

  • Preserving Statistical Validity in Adaptive Data Analysis

    Cynthia Dwork;Vitaly Feldman;Moritz Hardt;Toniann Pitassi

  • Combining Component Caching and Clause Learning for Effective Model Counting.

    Tian Sang;Fahiem Bacchus;Paul Beame;Henry A. Kautz

  • The Limits of Two-Party Differential Privacy.

    Andrew McGregor;Ilya Mironov;Toniann Pitassi;Omer Reingold

  • Deterministic Communication vs. Partition Number

    Mika Göös;Toniann Pitassi;Thomas Watson

  • Simplified and improved resolution lower bounds

    P. Beame;T. Pitassi

  • Propositional proof complexity: past, present, and future

    Paul Beame;Toniann Pitassi

  • Exponential lower bounds for the pigeonhole principle

    Toniann Pitassi;Paul Beame;Russell Impagliazzo

  • The Relative Complexity of NP Search Problems

    Paul Beame;Stephen Cook;Jeff Edmonds;Russell Impagliazzo

  • Flexibly Fair Representation Learning by Disentanglement

    Elliot Creager;David Madras;Jörn-Henrik Jacobsen;Marissa A. Weis

  • Pan-Private Streaming Algorithms

    Cynthia Dwork;Moni Naor;Toniann Pitassi;Guy N. Rothblum

  • Stochastic Boolean Satisfiability

    Michael L. Littman;Stephen M. Majercik;Toniann Pitassi

  • Generalization in adaptive data analysis and holdout reuse

    Cynthia Dwork;Vitaly Feldman;Moritz Hardt;Toniann Pitassi

  • Algorithms and complexity results for #SAT and Bayesian inference

    F. Bacchus;S. Dalmao;T. Pitassi

  • Rank Bounds and Integrality Gaps for Cutting Planes Procedures

    Joshua Buresh-Oppenheim;Nicola Galesi;Shlomo Hoory;Avner Magen

  • Lower Bounds on Hilbert's Nullstellensatz and Propositional Proofs

    Paul Beame;Russell Impagliazzo;Jan Krajíček;Toniann Pitassi

  • Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer

    David Madras;Toniann Pitassi;Richard S. Zemel

  • An exponential separation between the parity principle and the pigeonhole principle

    Paul Beame;Toniann Pitassi

Frequent Co-Authors

Paul Beame
Paul Beame University of Washington
Russell Impagliazzo
Russell Impagliazzo University of California, San Diego
Richard S. Zemel
Richard S. Zemel University of Toronto
Stephen A. Cook
Stephen A. Cook University of Toronto
Samuel R. Buss
Samuel R. Buss University of California, San Diego
Cynthia Dwork
Cynthia Dwork Harvard University
Omer Reingold
Omer Reingold Stanford University
Vitaly Feldman
Vitaly Feldman Apple (United States)
Moritz Hardt
Moritz Hardt Max Planck Institute for Intelligent Systems
Ran Raz
Ran Raz Princeton University

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