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D-Index & Metrics

Computer Science

D-Index
46
Citations
9830
World Ranking
6788
National Ranking
108

Overview

Guy N. Rothblum is affiliated with the Weizmann Institute of Science in Israel and has contributed extensively to the field of computer science with a focus on artificial intelligence, computational theory, and related disciplines.

Their recent research includes several papers published between 2020 and 2023, covering topics such as risk prediction models, fairness in machine learning, and privacy-preserving data analysis. Notable publications include:

  • Developing a COVID-19 mortality risk prediction model when individual-level data are not available, 2020, Nature Communications
  • Addressing bias in prediction models by improving subpopulation calibration, 2020, Journal of the American Medical Informatics Association
  • Performing risk stratification for COVID-19 when individual level data is not available - the experience of a large healthcare organization, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • Samplable Anonymous Aggregation for Private Federated Data Analysis, 2023, arXiv (Cornell University)
  • Abstracting Fairness: Oracles, Metrics, and Interpretability, 2020, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Frequently collaborating with other researchers, Rothblum's coauthors include Gal Yona, Shafi Goldwasser, Noga Amit, Noam Barda, and Eitan Bachmat. These collaborations have contributed to a range of studies across diverse topics within computer science.

Their research has appeared regularly in publication venues such as:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Lecture Notes in Computer Science
  • Nature Communications
  • Journal of the American Medical Informatics Association

Guy N. Rothblum's main field of study is computer science, with particular emphasis on the subfields of artificial intelligence, computational theory and mathematics, safety research, management science and operations research, and radiology, nuclear medicine, and imaging.

Their work encompasses several key topics, including:

  • Cryptography and Data Security
  • Explainable Artificial Intelligence (XAI)
  • Adversarial Robustness in Machine Learning
  • Machine Learning in Healthcare
  • Ethics and Social Impacts of AI
  • Complexity and Algorithms in Graphs
  • Privacy-Preserving Technologies in Data

Rothblum's scientific output reflects a broad interconnection between theoretical foundations and applied research, addressing both the development of novel algorithms and practical challenges related to data privacy, fairness, and robustness.

Best Publications

  • Boosting and Differential Privacy

    Cynthia Dwork;Guy N. Rothblum;Salil Vadhan

  • Differential privacy under continual observation

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

  • Delegating Computation: Interactive Proofs for Muggles

    Shafi Goldwasser;Yael Tauman Kalai;Guy N. Rothblum

  • Delegating computation: interactive proofs for muggles

    Shafi Goldwasser;Yael Tauman Kalai;Guy N. Rothblum

  • On the complexity of differentially private data release: efficient algorithms and hardness results

    Cynthia Dwork;Moni Naor;Omer Reingold;Guy N. Rothblum

  • A Multiplicative Weights Mechanism for Privacy-Preserving Data Analysis

    Moritz Hardt;Guy N. Rothblum

  • Concentrated Differential Privacy

    Cynthia Dwork;Guy N. Rothblum

  • On Best-Possible Obfuscation

    Shafi Goldwasser;Guy N. Rothblum

  • One-Time Programs

    Shafi Goldwasser;Yael Tauman Kalai;Guy N. Rothblum

  • Virtual Black-Box Obfuscation for All Circuits via Generic Graded Encoding

    Zvika Brakerski;Guy N. Rothblum

  • The complexity of online memory checking

    Moni Naor;Guy N. Rothblum

  • Securely obfuscating re-encryption

    Susan Hohenberger;Guy N. Rothblum;Abhi Shelat;Vinod Vaikuntanathan

  • Constant-Round Interactive Proofs for Delegating Computation

    Omer Reingold;Guy N. Rothblum;Ron D. Rothblum

  • Multicalibration: Calibration for the (Computationally-Identifiable) Masses

    Úrsula Hébert-Johnson;Michael P. Kim;Omer Reingold;Guy N. Rothblum

  • Fiat-Shamir: from practice to theory

    Ran Canetti;Yilei Chen;Justin Holmgren;Alex Lombardi

  • Pan-Private Streaming Algorithms

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

  • Leakage-resilient signatures

    Sebastian Faust;Eike Kiltz;Krzysztof Pietrzak;Guy N. Rothblum

  • Practical delegation of computation using multiple servers

    Ran Canetti;Ben Riva;Guy N. Rothblum

  • The complexity of online memory checking

    M. Naor;G.N. Rothblum

  • Composable and versatile privacy via truncated CDP

    Mark Bun;Cynthia Dwork;Guy N. Rothblum;Thomas Steinke

  • Securely Obfuscating Re-Encryption

    Susan Hohenberger;Guy N. Rothblum;Abhi Shelat;Vinod Vaikuntanathan

  • Delegating Computation: Interactive Proofs for Muggles.

    Shafi Goldwasser;Guy N. Rothblum;Yael Tauman Kalai

  • Constant-Round Interactive Proofs for Delegating Computation.

    Omer Reingold;Ron Rothblum;Guy N. Rothblum

Frequent Co-Authors

Shafi Goldwasser
Shafi Goldwasser University of California, Berkeley
Moni Naor
Moni Naor Weizmann Institute of Science
Omer Reingold
Omer Reingold Stanford University
Cynthia Dwork
Cynthia Dwork Harvard University
Ran Canetti
Ran Canetti Boston University
Oded Goldreich
Oded Goldreich Weizmann Institute of Science
Salil P. Vadhan
Salil P. Vadhan Harvard University
Krzysztof Pietrzak
Krzysztof Pietrzak Institute of Science and Technology Austria
Zvika Brakerski
Zvika Brakerski Weizmann Institute of Science

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