World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
75
Citations
25837
World Ranking
1401
National Ranking
82

Overview

Anima Anandkumar is affiliated with Nvidia in the United Kingdom and has contributed extensively to research at the intersection of computer science and medicine. Their work encompasses various subfields, including artificial intelligence, computer vision and pattern recognition, surgery, biomedical engineering, and health informatics.

Their recent publications demonstrate a focus on AI-driven methods applied to medical and surgical contexts, as well as advances in machine learning models. Notable papers include:

  • "FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators" (2022, arXiv (Cornell University))
  • "A vision transformer for decoding surgeon activity from surgical videos" (2023, Nature Biomedical Engineering)
  • "Convolutional Tensor-Train LSTM for Spatio-temporal Learning" (2020, arXiv (Cornell University))
  • "A multi-institutional study using artificial intelligence to provide reliable and fair feedback to surgeons" (2023, Communications Medicine)
  • "Surgical gestures as a method to quantify surgical performance and predict patient outcomes" (2022, npj Digital Medicine)

Anandkumar has collaborated frequently with several researchers, including Andrew J. Hung, Daniel A. Donoho, Yuke Zhu, Dani Kiyasseh, and Dhiraj J. Pangal. These co-authors appear regularly in their research publications, indicating ongoing partnerships within related domains.

Their work has been disseminated primarily through specific venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • npj Digital Medicine
  • The Journal of Urology
  • Nature Biomedical Engineering

The main fields of study covered by Anandkumar include computer science with 45 publications and medicine with 40. Within these, their research targets several subfields:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Surgery
  • Biomedical Engineering
  • Health Informatics

Research topics across their portfolio concentrate on areas such as:

  • Surgical Simulation and Training
  • Artificial Intelligence in Healthcare and Education
  • Machine Learning in Materials Science
  • Anatomy and Medical Technology
  • History and Advancements in Chemistry
  • Cardiac, Anesthesia and Surgical Outcomes
  • Advanced Vision and Imaging

Best Publications

  • SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

    Enze Xie;Wenhai Wang;Zhiding Yu;Anima Anandkumar

  • Fourier Neural Operator for Parametric Partial Differential Equations

    Zongyi Li;Nikola Borislavov Kovachki;Kamyar Azizzadenesheli;Burigede liu

  • Tensor decompositions for learning latent variable models

    Animashree Anandkumar;Rong Ge;Daniel Hsu;Sham M. Kakade

  • Born Again Neural Networks

    Tommaso Furlanello;Zachary Chase Lipton;Michael Tschannen;Laurent Itti

  • Physics-informed machine learning: case studies for weather and climate modelling.

    K. Kashinath;M. Mustafa;A. Albert;J. L. Wu;J. L. Wu

  • Deep Active Learning for Named Entity Recognition.

    Yanyao Shen;Hyokun Yun;Zachary C. Lipton;Yakov Kronrod

  • signSGD: Compressed Optimisation for Non-Convex Problems

    Jeremy Bernstein;Yu-Xiang Wang;Kamyar Azizzadenesheli;Animashree Anandkumar

  • U-FNO - an enhanced Fourier neural operator based-deep learning model for multiphase flow.

    Gege Wen;Zongyi Li;Kamyar Azizzadenesheli;Anima Anandkumar

  • Neural Operator: Graph Kernel Network for Partial Differential Equations

    Zongyi Li;Nikola B. Kovachki;Kamyar Azizzadenesheli;Burigede Liu

  • Stochastic Activation Pruning for Robust Adversarial Defense

    Guneet S. Dhillon;Kamyar Azizzadenesheli;Zachary C. Lipton;Jeremy D. Bernstein

  • Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret

    A Anandkumar;N Michael;A K Tang;A Swami

  • A Method of Moments for Mixture Models and Hidden Markov Models

    Animashree Anandkumar;Daniel J. Hsu;Sham M. Kakade

  • TensorLy: tensor learning in python

    Jean Kossaifi;Yannis Panagakis;Anima Anandkumar;Maja Pantic

  • Neural Lander: Stable Drone Landing Control Using Learned Dynamics

    Guanya Shi;Xichen Shi;Michael O'Connell;Rose Yu

  • A Tensor Spectral Approach to Learning Mixed Membership Community Models

    Animashree Anandkumar;Rong Ge;Daniel J. Hsu;Sham M. Kakade

  • Learning Latent Tree Graphical Models

    Myung Jin Choi;Vincent Y. F. Tan;Animashree Anandkumar;Alan S. Willsky

  • A Spectral Algorithm for Latent Dirichlet Allocation

    Animashree Anandkumar;Dean P. Foster;Daniel Hsu;Sham M. Kakade

  • Beating the Perils of Non-Convexity: Guaranteed Training of Neural Networks using Tensor Methods

    Majid Janzamin;Hanie Sedghi;Anima Anandkumar

  • OrbNet: Deep learning for quantum chemistry using symmetry-adapted atomic-orbital features.

    Zhuoran Qiao;Matthew Welborn;Animashree Anandkumar;Frederick R. Manby

  • Opportunistic Spectrum Access with Multiple Users: Learning under Competition

    Animashree Anandkumar;Nithin Michael;Ao Tang

  • Non-convex Robust PCA

    Praneeth Netrapalli;Niranjan U N;Sujay Sanghavi;Animashree Anandkumar

  • Multipole Graph Neural Operator for Parametric Partial Differential Equations

    Zongyi Li;Nikola B. Kovachki;Kamyar Azizzadenesheli;Burigede Liu

Frequent Co-Authors

Vincent Y. F. Tan
Vincent Y. F. Tan National University of Singapore
Daniel Hsu
Daniel Hsu Columbia University
Sham M. Kakade
Sham M. Kakade Harvard University
Yisong Yue
Yisong Yue California Institute of Technology
Yuke Zhu
Yuke Zhu The University of Texas at Austin
Rong Ge
Rong Ge Duke University
Zachary C. Lipton
Zachary C. Lipton Carnegie Mellon University
Lang Tong
Lang Tong Cornell University
Animesh Garg
Animesh Garg University of Toronto

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 degree options can open new doors in the field of computer science and beyond. Today, many good online colleges offer flexible programs that cater to students with different goals, whether you’re looking to launch your career or upskill for advancement.

If you’re interested in creativity and technology, you might consider one of the video game design programs available online. These programs often blend technical skills with hands-on experience, preparing graduates for roles in the thriving gaming industry.

Cybersecurity is another rapidly-growing field. With an increasing demand for IT security professionals, earning an online cybersecurity degree can help you develop the expertise needed to protect data and systems in a digital world.

For those interested in the intersection of technology and project management, consider pursuing a master of construction management. This qualification can lead to leadership roles in various industries where technology integration is key.

Each pathway offers unique benefits and potential careers, making it important to research your options and choose a program that aligns with your interests and professional aspirations.

Best Scientists Citing Anima Anandkumar

Trending Scientists

Recently Published Articles