World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
16832
World Ranking
9941
National Ranking
4178

Overview

Moises Goldszmidt is affiliated with Apple in the United States, contributing to research primarily within the field of Computer Science. Their work predominantly addresses topics related to Artificial Intelligence, with a specialized focus on subfields such as Machine Learning and Algorithms, Machine Learning and Data Classification, as well as Gaussian Processes and Bayesian Inference.

The recent scholarly output from Goldszmidt includes a publication titled Active Learning with Expected Error Reduction, released in 2022 through the arXiv repository hosted by Cornell University. This paper has accumulated a modest number of citations, indicating engagement from the research community.

Collaboration appears as a notable aspect of Goldszmidt's research activity. Frequent coauthors include:

  • Stephen Mussmann
  • Julia Reisler
  • Daniel Tsai
  • Ehsan Mousavi Khaneghah
  • Shayne O'Brien

Goldszmidt's publication venues are currently concentrated in preprint archives, with arXiv (Cornell University) being the principal outlet for disseminating their latest contributions. This choice may reflect an emphasis on accessibility and early-stage research communication.

The main topics of research covered by Goldszmidt's works are identified as:

  • Machine Learning and Algorithms
  • Machine Learning and Data Classification
  • Gaussian Processes and Bayesian Inference

This profile demonstrates a consistent engagement with methodologies and theoretical frameworks that intersect at the core of artificial intelligence and computational learning theories. The combination of fields and topics highlights an integrative approach to advancing machine learning capabilities and probabilistic modeling.

Best Publications

  • Bayesian Network Classifiers

    Nir Friedman;Dan Geiger;Moises Goldszmidt

  • Context-specific independence in Bayesian networks

    Craig Boutilier;Nir Friedman;Moises Goldszmidt;Daphne Koller

  • Learning Bayesian networks with local structure

    Nir Friedman;Moises Goldszmidt

  • Correlating instrumentation data to system states: a building block for automated diagnosis and control

    Ira Cohen;Moises Goldszmidt;Terence Kelly;Julie Symons

  • Stochastic dynamic programming with factored representations

    Craig Boutilier;Richard Dearden;Moisés Goldszmidt

  • Exploiting Structure in Policy Construction

    Craig Boutilier;Richard Dearden;Moises Goldszmidt

  • Qualitative probabilities for default reasoning, belief revision, and causal modeling

    Moisés Goldszmidt;Judea Pearl

  • Capturing, indexing, clustering, and retrieving system history

    Ira Cohen;Steve Zhang;Moises Goldszmidt;Julie Symons

  • Building classifiers using Bayesian networks

    Nir Friedman;Moises Goldszmidt

  • Discretizing continuous attributes while learning Bayesian networks

    Nir Friedman;Moisés Goldszmidt

  • Fingerprinting the datacenter: automated classification of performance crises

    Peter Bodik;Moises Goldszmidt;Armando Fox;Dawn B. Woodard

  • Data analysis with bayesian networks: a bootstrap approach

    Nir Friedman;Moises Goldszmidt;Abraham Wyner

  • A maximum entropy approach to nonmonotonic reasoning

    M. Goldszmidt;P. Morris;J. Pearl

  • Rank-based Systems: A Simple Approach to Belief Revision, Belief Update, and Reasoning about Evidence and Actions.

    Moisés Goldszmidt;Judea Pearl

  • How dynamic are IP addresses

    Yinglian Xie;Fang Yu;Kannan Achan;Eliot Gillum

  • Sequential auctions for the allocation of resources with complementarities

    Craig Boutilier;Moisés Goldszmidt;Bikash Sabata

  • Ensembles of models for automated diagnosis of system performance problems

    S. Zhang;I. Cohen;M. Goldszmidt;J. Symons

  • Predicting travel time reliability using mobile phone GPS data

    Dawn Woodard;Galina Nogin;Paul Koch;David Racz

  • Sequential update of Bayesian network structure

    Nir Friedman;Moises Goldszmidt

  • Bayesian Network Classifiers

    Moises Goldszmidt

  • Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence

    Craig Boutilier;Moisés Goldszmidt

Frequent Co-Authors

Nir Friedman
Nir Friedman Weizmann Institute of Science
Ira Cohen
Ira Cohen Hewlett-Packard (United States)
Craig Boutilier
Craig Boutilier Google (United States)
Judea Pearl
Judea Pearl University of California, Los Angeles
Paul Barham
Paul Barham Google (United States)
Adnan Darwiche
Adnan Darwiche University of California, Los Angeles
Richard Mortier
Richard Mortier University of Cambridge
Armando Fox
Armando Fox University of California, Berkeley
Daniel Delling
Daniel Delling Apple (United States)
Andrew V. Goldberg
Andrew V. Goldberg Amazon (United States)

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

Exploring online education can be a smart way to start or advance your computer science career in the USA. There are 2 year online degrees that provide a fast-track option to gain foundational skills and potentially land entry-level tech jobs.

For those seeking a quicker route to higher-level roles, fastest masters degree online programs offer an accelerated path to advanced credentials. These programs are designed for flexibility and speed, helping students upskill without interrupting their careers.

When selecting a program, consider the impact on your long-term goals. Choosing graduate degrees that are worth it ensures your investment pays off, with degrees focused on in-demand areas like data science, cybersecurity, and artificial intelligence.

Additionally, targeted certificates can quickly boost your employability. Check out easy licenses and certifications to get if you want a cost-effective way to enter the workforce or specialize in a niche area.

Best Scientists Citing Moises Goldszmidt

Trending Scientists

Recently Published Articles