World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
6068
World Ranking
10246
National Ranking
4300

Research.com Recognitions

  • 2021 - IEEE Claude E. Shannon Award

Overview

Alon Orlitsky is affiliated with the University of California, San Diego in the United States. Their research focuses primarily on the field of Computer Science with a notable emphasis on Artificial Intelligence. Contributions also span into related subfields including Mechanical Engineering, Molecular Biology, Control and Systems Engineering, and Mathematical Physics.

Orlitsky's work covers a range of topics, with significant publications in Machine Learning and Algorithms, Algorithms and Data Compression, Domain Adaptation and Few-Shot Learning, as well as Mineral Processing and Grinding. Additional topics of research include Diffusion and Search Dynamics, Control Systems and Identification, and Mathematical Dynamics and Fractals.

Recent published papers authored or coauthored by Orlitsky include:

  • A General Method for Robust Learning from Batches, 2020, arXiv (Cornell University)
  • Profile Entropy: A Fundamental Measure for the Learnability and Compressibility of Discrete Distributions, 2020, arXiv (Cornell University)
  • SURF: A Simple, Universal, Robust, Fast Distribution Learning Algorithm, 2020, arXiv (Cornell University)
  • Linear-Sample Learning of Low-Rank Distributions, 2020, arXiv (Cornell University)
  • Robust estimation algorithms don't need to know the corruption level, 2022, arXiv (Cornell University)

Frequent coauthors collaborating with Orlitsky include:

  • Ayush Jain
  • Vaishakh Ravindrakumar
  • Hao Yi
  • Yi Hao

Orlitsky has contributed primarily to publications in arXiv (Cornell University), with multiple articles published in this venue. Their sustained research output in this repository reflects engagement with emerging and exploratory studies in their fields of interest.

In recognition of their contributions, Orlitsky was awarded the IEEE Claude E. Shannon Award in 2021.

Best Publications

  • Coding for computing

    A. Orlitsky;J.R. Roche

  • Stopping set distribution of LDPC code ensembles

    A. Orlitsky;Krishnamurthy Viswanathan;J. Zhang

  • Always Good Turing: asymptotically optimal probability estimation

    A. Orlitsky;N.P. Santhanam;J. Zhang

  • Zero-error information theory

    J. Korner;A. Orlitsky

  • Source coding and graph entropies

    N. Alon;A. Orlitsky

  • Universal compression of memoryless sources over unknown alphabets

    A. Orlitsky;N.P. Santhanam;Junan Zhang

  • Worst-case interactive communication. I. Two messages are almost optimal

    A. Orlitsky

  • Optimal prediction of the number of unseen species

    Alon Orlitsky;Ananda Theertha Suresh;Yihong Wu

  • Monte Carlo generation of self-avoiding walks with fixed endpoints and fixed length

    N. Madras;A. Orlitsky;L. A. Shepp

  • Stopping sets and the girth of Tanner graphs

    A. Orlitsky;R. Urbanke;K. Viswanathan;J. Zhang

  • On Learning Distributions from their Samples

    Sudeep Kamath;Alon Orlitsky;Dheeraj Pichapati;Ananda Theertha Suresh

  • Repeated communication and Ramsey graphs

    N. Alon;A. Orlitsky

  • On codes that avoid specified differences

    B.E. Moision;A. Orlitsky;P.H. Siegel

  • Interactive communication of balanced distributions and of correlated files

    Alon Orlitsky

  • Worst-case interactive communication. II. Two messages are not optimal

    A. Orlitsky

  • A lower bound on the expected length of one-to-one codes

    N. Alon;A. Orlitsky

  • Competitive distribution estimation: why is Good-Turing good

    Alon Orlitsky;Ananda Theertha Suresh

  • Estimating Renyi Entropy of Discrete Distributions

    Jayadev Acharya;Alon Orlitsky;Ananda Theertha Suresh;Himanshu Tyagi

  • Privacy, additional information and communication

    R. Bar-Yehuda;B. Chor;E. Kushilevitz;A. Orlitsky

  • On modeling profiles instead of values

    Alon Orlitsky;Narayana P. Santhanam;Krishnamurthy Viswanathan;Junan Zhang

  • Near-optimal-sample estimators for spherical Gaussian mixtures

    Jayadev Acharya;Ashkan Jafarpour;Alon Orlitsky;Ananda Theertha Suresh

Frequent Co-Authors

Yihong Wu
Yihong Wu Yale University
Olgica Milenkovic
Olgica Milenkovic University of Illinois at Urbana-Champaign
Christina Fragouli
Christina Fragouli University of California, Los Angeles
Vwani P. Roychowdhury
Vwani P. Roychowdhury University of California, Los Angeles
Thomas Kailath
Thomas Kailath Stanford University
Noga Alon
Noga Alon Tel Aviv University
Paul H. Siegel
Paul H. Siegel University of California, San Diego
Eyal Kushilevitz
Eyal Kushilevitz Technion – Israel Institute of Technology
Moni Naor
Moni Naor Weizmann Institute of Science
Abbas El Gamal
Abbas El Gamal Stanford University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Expanding your computer science education can open doors to diverse career pathways, both inside and outside traditional tech roles. Many students explore graduate studies to build expertise while balancing work and personal commitments. Today, online degree options provide flexibility and affordability for continued learning.

For those interested in leadership, the best online emba programs offer advanced business skills, preparing graduates to lead tech projects or startups. Another alternative is the cheapest online doctorate in organizational leadership, suitable for those seeking research or executive roles in large organizations.

If you’re looking for specialized paths, a master in library science can help you leverage technology in information management, digital archives, or data curation. Those seeking more affordable routes should explore the cheapest online masters degree programs for customizable and budget-friendly advancement.

By pursuing related online degrees, you can tailor your expertise and enhance your career mobility in today’s evolving job market.

Best Scientists Citing Alon Orlitsky

Trending Scientists

Recently Published Articles