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Engineering and Technology

D-Index
33
Citations
26497
World Ranking
9304
National Ranking
2599

Overview

Sumit Chopra is affiliated with New York University in the United States. Their research primarily spans the field of Medicine, with a concentrated focus on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Biomedical Engineering, and Computer Vision and Pattern Recognition.

The scientist's recent publications cover a range of topics related to medical imaging and machine learning applications in healthcare. Notable papers include:

  • Assessment of a deep-learning system for fracture detection in musculoskeletal radiographs, 2020, npj Digital Medicine
  • FastMRI Prostate: A public, biparametric MRI dataset to advance machine learning for prostate cancer imaging, 2024, Scientific Data
  • Virtualization In Cloud Computing: A Review, 2020, International Journal of Scientific Research in Computer Science Engineering and Information Technology
  • Prostate Cancer Risk Stratification and Scan Tailoring Using Deep Learning on Abbreviated Prostate MRI, 2025, Journal of Magnetic Resonance Imaging
  • Pancreatic Cystic Lesions, 2023, Gastrointestinal Endoscopy Clinics of North America

Their research topics predominantly involve radiomics and machine learning in medical imaging, medical imaging techniques and applications, prostate cancer diagnosis and treatment, advanced MRI techniques and applications, advanced X-ray and CT imaging, MRI in cancer diagnosis, and artificial intelligence in healthcare and education.

Frequent co-authors collaborating with Sumit Chopra include:

  • Daniel K. Sodickson
  • Hersh Chandarana
  • Angela Tong
  • Tarun Dutt
  • Luke Ginocchio

Common publication venues for their work include:

  • arXiv (Cornell University)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • International Journal of Security and Networks
  • npj Digital Medicine
  • Scientific Data

Best Publications

  • Dimensionality Reduction by Learning an Invariant Mapping

    R. Hadsell;S. Chopra;Y. LeCun

  • Learning a similarity metric discriminatively, with application to face verification

    S. Chopra;R. Hadsell;Y. LeCun

  • A Neural Attention Model for Abstractive Sentence Summarization

    Alexander M. Rush;Sumit Chopra;Jason Weston

  • Efficient Learning of Sparse Representations with an Energy-Based Model

    Marc'aurelio Ranzato;Christopher Poultney;Sumit Chopra;Yann L. Cun

  • Memory Networks

    Jason Weston;Sumit Chopra;Antoine Bordes

  • Sequence Level Training with Recurrent Neural Networks

    Marc'Aurelio Ranzato;Sumit Chopra;Michael Auli;Wojciech Zaremba

  • A Tutorial on Energy-Based Learning

    Yann LeCun;Sumit Chopra;Raia Hadsell;Aurelio Ranzato

  • Abstractive Sentence Summarization with Attentive Recurrent Neural Networks

    Sumit Chopra;Michael Auli;Alexander M. Rush

  • Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

    Jason Weston;Antoine Bordes;Sumit Chopra;Alexander M. Rush

  • Question Answering with Subgraph Embeddings

    Antoine Bordes;Sumit Chopra;Jason Weston

  • Large-scale Simple Question Answering with Memory Networks

    Antoine Bordes;Nicolas Usunier;Sumit Chopra;Jason Weston

  • Deep neural network improves fracture detection by clinicians.

    Robert V. Lindsey;Aaron Daluiski;Sumit Chopra;Alexander Lachapelle

  • The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations

    Felix Hill;Antoine Bordes;Sumit Chopra;Jason Weston

  • Video (language) modeling: a baseline for generative models of natural videos.

    Marc'Aurelio Ranzato;Arthur Szlam;Joan Bruna;Michaël Mathieu

  • StarSpace: Embed All The Things!

    Ledell Yu Wu;Adam Fisch;Sumit Chopra;Keith Adams

  • Learning Longer Memory in Recurrent Neural Networks

    Tomas Mikolov;Armand Joulin;Sumit Chopra;Michael Mathieu

  • DLID: Deep Learning for Domain Adaptation by Interpolating between Domains

    Sumit Chopra;Suhrid Balakrishnan;Raghuraman Gopalan

  • #TagSpace: Semantic Embeddings from Hashtags

    Jason Weston;Sumit Chopra;Keith Adams

  • Collaborative ranking

    Suhrid Balakrishnan;Sumit Chopra

  • Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems

    Jesse Dodge;Andreea Gane;Xiang Zhang;Antoine Bordes

Frequent Co-Authors

Jason Weston
Jason Weston Facebook (United States)
Marc'Aurelio Ranzato
Marc'Aurelio Ranzato DeepMind (United Kingdom)
Antoine Bordes
Antoine Bordes Facebook (United States)
Yann LeCun
Yann LeCun Facebook (United States)
Alexander M. Rush
Alexander M. Rush Cornell University
John Leahy
John Leahy New York University
Andrew Caplin
Andrew Caplin New York University
Jiwei Li
Jiwei Li Zhejiang University
Srinivas Bangalore
Srinivas Bangalore Interactions LLC
Tomas Mikolov
Tomas Mikolov Czech Technical University in Prague

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