Machine Learning Research in Top 10 US Universities

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This article represents information related with machine learning departments & related research projects in top 10 US universities (as per USNews Ranking). I have put it together for my quick reference and thought to share with you for the same purpose. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos.

Following are top 10 universities covered later in this article:

  • Princeton University
  • Harvard University
  • Yale University
  • Columbia University
  • Stanford University
  • University of Chicago
  • MIT
  • Duke University
  • University of Pennsylvania
  • California Institue of Technology

 

Machine Learning @ Top 10 US Universities
  1. Princeton University: Machine Learning Department at Princeton University is using some of the following ML techniques to continue their work on areas such as theoretical foundations of machine learning, the experimental study of machine learning algorithms, and the interdisciplinary application of machine learning to other domains, such as biology and information retrieval:
    • Non-parametric Bayesian techniques
    • Probabilistic graphical models
    • Support-vector Machines

    Following are some of the projects that they are currently working upon:

  2. Harvard University – Artificial Intelligence Research Group (AIRG): Following are areas of reasearch focused upon by AIRG:
    • Natural Language Processing
      • Computational Linguistics
      • Statistical Language Processing
      • Discourse
    • Reasoning under Uncertainty
      • Probabilistic Reasoning for Complex Systems
      • Learning Rich Probabilistic Models
      • Effective Algorithms for Game-Theoretic Problems
  3. Yale University – Machine Learning
  4. Columbia University – Machine Learning Lab: Following is the list of areas of research:
    • Learning with Matchings and Perfect Graphs
      • Learning with Generalized Matchings
      • Matching, MAP Estimation and Message Passing
      • Matchings, Trees and Perfect Graphs
    • Discriminative and Generative Learning

    Their past work have been focused upon machine-learning inspired computer vision systems that that achieved top-performing face recognition performance and obtained an honorable mention from the Pattern Recognition Society. Their collections of research papers could be found on this page.

  5. Stanford University – SAIL: Stanford Artificial Intelligence Laboratory (SAIL) has been a center of excellence for Artificial Intelligence research, teaching, theory, and practice for over fifty years. This page provides details of all ML related courses including CS229 by Andrew NG which is one of the most popular ML course of current times. Another related popular course is Statistical Learning Theory.
  6. University of Chicago – Artificial Intelligence Lab: Following are some of the current research areas:
    • Data mining for manufacturing and design processes
    • Text summarization
    • Modeling network routing as partially observable markov decision processes
  7. MIT – BigData@CSAIL: MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) is focused on sole objective of identifying and developing new technologies needed to solve next generation data challenges that will require the ability to scale well beyond what today’s computing platforms, algorithms, and methods can provide. Their current research projects could be found on this page. Following are some of the machine-learning related projects:
  8. Duke University – Machine Learning: Following are some of the research projects happening at Machine learning department in Duke Univ:
    • Nonparametric Bayesian methods for analysis of high-dimensional data
    • Bayesian prediction and variable selection for complex data
    • Bayesian statistical methodology for complex data
    • Machine learning for Systems Biology
    • Statistical methods for genomics
    • Statistical methods for Cognitive Science
    • Bayesian modeling
  9. University of Pennsylvania – Machine Learning: Following some of the research projects happening currently at UPenn:
  10. California Institue of Technology– Machine Lab: Machine Learning at Caltech is driven mostly by Prof. Yaser S. Abu-Mustafa. His lectures on different machine learning topics could be found on this lectures page. Alternatively, there is a great collection of videos on machine learning available on videos library page.
Ajitesh Kumar

Ajitesh Kumar

Ajitesh has been recently working in the area of AI and machine learning. Currently, his research area includes Safe & Quality AI. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc.

He has also authored the book, Building Web Apps with Spring 5 and Angular.
Ajitesh Kumar

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