World's Best Scientists 2026 revealed!
Venkatesh Saligrama

Venkatesh Saligrama

D-Index & Metrics

Computer Science

D-Index
45
Citations
11395
World Ranking
7069
National Ranking
3103

Overview

Venkatesh Saligrama is a researcher affiliated with Boston University in the United States. Their academic work primarily focuses on the field of Computer Science, with a concentration on Artificial Intelligence, Computer Vision and Pattern Recognition, and Management Science and Operations Research. Additional interests include Electrical and Electronic Engineering as well as Radiology, Nuclear Medicine, and Imaging.

The researcher's main topics of investigation encompass Domain Adaptation and Few-Shot Learning, Machine Learning and Algorithms, Advanced Neural Network Applications, and Advanced Bandit Algorithms Research. Other notable areas include Generative Adversarial Networks and Image Synthesis, Human Pose and Action Recognition, and Adversarial Robustness in Machine Learning.

Venkatesh Saligrama has several frequent co-authors who have collaborated on multiple publications. These include:

  • Aditya Gangrade
  • Samarth Mishra
  • Kate Saenko
  • Pengkai Zhu
  • Ruizhao Zhu

The researcher has published notably in venues such as:

  • arXiv (Cornell University)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Nuclear Engineering and Technology
  • European Radiology
  • IEEE Transactions on Pattern Analysis and Machine Intelligence

Some of the recent published papers include:

  • "Federated Learning Based on Dynamic Regularization" (2021) - arXiv (Cornell University)
  • "Advances in gamma radiation detection systems for emergency radiation monitoring" (2020) - Nuclear Engineering and Technology
  • "Machine learning combining CT findings and clinical parameters improves prediction of length of stay and ICU admission in torso trauma" (2021) - European Radiology
  • "Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data" (2022) - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Interpretable Compositional Representations for Robust Few-Shot Generalization" (2022) - IEEE Transactions on Pattern Analysis and Machine Intelligence

Best Publications

  • Man is to computer programmer as woman is to homemaker? debiasing word embeddings

    Tolga Bolukbasi;Kai-Wei Chang;James Zou;Venkatesh Saligrama

  • Zero-Shot Learning via Semantic Similarity Embedding

    Ziming Zhang;Venkatesh Saligrama

  • Zero-Shot Learning via Joint Latent Similarity Embedding

    Ziming Zhang;Venkatesh Saligrama

  • Video anomaly detection based on local statistical aggregates

    Venkatesh Saligrama;Zhu Chen

  • Boolean Compressed Sensing and Noisy Group Testing

    G. K. Atia;V. Saligrama

  • Abnormal events detection based on spatio-temporal co-occurences

    Unknown

  • Abnormal events detection based on spatio-temporal co-occurences

    Y Benezeth;P.-M Jodoin;V Saligrama;C Rosenberger

  • Federated Learning Based on Dynamic Regularization

    Durmus Alp Emre Acar;Yue Zhao;Ramon Matas Navarro;Matthew Mattina

  • Foreground-Adaptive Background Subtraction

    J.M. McHugh;J. Konrad;V. Saligrama;P.-M. Jodoin

  • Adaptive neural networks for efficient inference

    Tolga Bolukbasi;Joseph Wang;Ofer Dekel;Venkatesh Saligrama

  • Information Theoretic Bounds for Compressed Sensing

    S Aeron;V Saligrama;Manqi Zhao

  • Distributed Detection in Sensor Networks With Packet Losses and Finite Capacity Links

    V. Saligrama;M. Alanyali;O. Savas

  • Video Anomaly Identification

    V Saligrama;J Konrad;P Jodoin

  • Prediction of hospitalization due to heart diseases by supervised learning methods.

    Wuyang Dai;Theodora S. Brisimi;William G. Adams;Theofanie Mela

  • Non-adaptive probabilistic group testing with noisy measurements: Near-optimal bounds with efficient algorithms

    Chun Lam Chan;Pak Hou Che;Sidharth Jaggi;Venkatesh Saligrama

  • Non-Adaptive Group Testing: Explicit Bounds and Novel Algorithms

    Chun Lam Chan;Sidharth Jaggi;Venkatesh Saligrama;Samar Agnihotri

  • Anomaly Detection with Score functions based on Nearest Neighbor Graphs

    Manqi Zhao;Venkatesh Saligrama

  • Efficient Training of Very Deep Neural Networks for Supervised Hashing

    Ziming Zhang;Yuting Chen;Venkatesh Saligrama

  • Unique contributions of parvalbumin and cholinergic interneurons in organizing striatal networks during movement

    Howard J. Gritton;William M. Howe;William M. Howe;Michael F. Romano;Alexandra G. DiFeliceantonio;Alexandra G. DiFeliceantonio

  • Supervised Sequential Classification Under Budget Constraints

    Kirill Trapeznikov;Venkatesh Saligrama

  • Zero-Shot Recognition via Structured Prediction

    Ziming Zhang;Venkatesh Saligrama

Frequent Co-Authors

Prakash Ishwar
Prakash Ishwar Boston University
Pierre-Marc Jodoin
Pierre-Marc Jodoin Université de Sherbrooke
David A. Castanon
David A. Castanon Boston University
Janusz Konrad
Janusz Konrad Boston University
Csaba Szepesvári
Csaba Szepesvári University of Alberta
Alex Olshevsky
Alex Olshevsky Boston University
Kai-Wei Chang
Kai-Wei Chang University of California, Los Angeles
Brian Kulis
Brian Kulis Boston University
Julien M. Hendrickx
Julien M. Hendrickx Université Catholique de Louvain
Amir Leshem
Amir Leshem Bar-Ilan 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

Exploring Computer Science in the USA opens diverse pathways for further education and professional growth. Many students begin with an associate degree, often searching for community colleges near me to find flexible, local, or online programs that match their budget and schedule.

For those looking to deepen their expertise, pursuing inexpensive masters degrees in computer science or related fields is a cost-effective option. Affordable online master's programs help students advance their skills without the burden of high tuition costs.

Ambitious professionals may consider doctoral pathways. A doctorate in leadership can be valuable for those aiming for executive or academic roles, emphasizing strategic thinking and organizational advancement. Alternatively, affordable edd programs online offer specialized education for leadership in educational settings.

No matter your current educational level or career goals, a wide range of online degree options can help you affordably reach your aspirations in technology, leadership, or beyond.

Best Scientists Citing Venkatesh Saligrama

Trending Scientists

Recently Published Articles