World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
4123
World Ranking
14065
National Ranking
5580

Overview

Vikas Singh is affiliated with the University of Wisconsin-Madison in the United States. Their scholarly work spans primarily the fields of Medicine and Computer Science, with a significant focus on Artificial Intelligence, Genetics, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, and Surgery.

The scientist's research covers various specialized topics including:

  • Glioma Diagnosis and Treatment
  • Domain Adaptation and Few-Shot Learning
  • Adversarial Robustness in Machine Learning
  • Gaussian Processes and Bayesian Inference
  • Advanced Neuroimaging Techniques and Applications
  • Explainable Artificial Intelligence (XAI)
  • Anomaly Detection Techniques and Applications

Several of their recent publications include:

  • "Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia," 2020, Computers and Electronics in Agriculture
  • "Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention," 2021, arXiv (Cornell University)
  • "On the Versatile Uses of Partial Distance Correlation in Deep Learning," 2022, Lecture notes in computer science
  • "Alzheimer's disease genetic risk and cognitive reserve in relationship to long-term cognitive trajectories among cognitively normal individuals," 2023, Alzheimer s Research & Therapy

Vikas Singh frequently collaborates with a group of coauthors, including Rudrasis Chakraborty, Sathya N. Ravi, Aliasgar Moiyadi, Prakash Shetty, and Sridhar Epari, with multiple joint publications across their research areas.

The scientist has also contributed to published books, including one titled Computing Algorithms with Applications in Engineering, released in 2020 by Springer Nature.

Their publication record is distributed across various venues with notable contributions to:

  • arXiv (Cornell University)
  • Journal of the American College of Cardiology
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Neurology India
  • PubMed

Best Publications

  • Predictive Markers for AD in a Multi-Modality Framework: An Analysis of MCI Progression in the ADNI Population

    Chris Hinrichs;Vikas Singh;Guofan Xu;Sterling C. Johnson

  • An efficient algorithm for Co-segmentation

    Dorit S. Hochbaum;Vikas Singh

  • Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention

    Yunyang Xiong;Zhanpeng Zeng;Rudrasis Chakraborty;Mingxing Tan

  • Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset.

    Chris Hinrichs;Vikas Singh;Lopamudra Mukherjee;Guofan Xu

  • Half-integrality based algorithms for cosegmentation of images

    Lopamudra Mukherjee;Vikas Singh;Charles R Dyer

  • Gaze-enabled egocentric video summarization via constrained submodular maximization

    Jia Xu;Lopamudra Mukherjee;Yin Li;Jamieson Warner

  • Solving the multi-way matching problem by permutation synchronization

    Deepti Pachauri;Risi Kondor;Vikas Singh

  • Deep Learning image segmentation for extraction of fish body measurements and prediction of body weight and carcass traits in Nile tilapia

    Arthur F.A. Fernandes;Eduardo M. Turra;Érika R. de Alvarenga;Tiago L. Passafaro

  • Scale invariant cosegmentation for image groups

    Lopamudra Mukherjee;Vikas Singh;Jiming Peng

  • MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

    Yunyang Xiong;Hanxiao Liu;Suyog Gupta;Berkin Akin

  • Controlling UAVs with sensor input spoofing attacks

    Drew Davidson;Hao Wu;Robert Jellinek;Thomas Ristenpart

  • Random walks based multi-image segmentation: Quasiconvexity results and GPU-based solutions

    Maxwell D. Collins;Jia Xu;Leo Grady;Vikas Singh

  • GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity

    Jia Xu;Vamsi K. Ithapu;Lopamudra Mukherjee;James M. Rehg

  • Topology-Based Kernels With Application to Inference Problems in Alzheimer's Disease

    D. Pachauri;C. Hinrichs;M. K. Chung;S. C. Johnson

  • Extracting and summarizing white matter hyperintensities using supervised segmentation methods in Alzheimer's disease risk and aging studies.

    Vamsi Ithapu;Vikas Singh;Christopher Lindner;Benjamin P. Austin

  • Mixed Effects Neural Networks (MeNets) With Applications to Gaze Estimation

    Yunyang Xiong;Hyunwoo J. Kim;Vikas Singh

  • MKL for Robust Multi-modality AD Classification

    Chris Hinrichs;Vikas Singh;Guofan Xu;Sterling Johnson

  • Characterizing Functional Connectivity Differences in Aging Adults using Machine Learning on Resting State fMRI Data

    Svyatoslav Vergun;Alok Deshpande;Timothy B. Meier;Jie Song

  • Ensemble clustering using semidefinite programming with applications

    Vikas Singh;Lopamudra Mukherjee;Jiming Peng;Jinhui Xu

  • Imaging-based enrichment criteria using deep learning algorithms for efficient clinical trials in mild cognitive impairment

    Vamsi K. Ithapu;Vikas Singh;Ozioma C. Okonkwo;Richard J. Chappell

  • Tensorize, Factorize and Regularize: Robust Visual Relationship Learning

    Seong Jae Hwang;Hyunwoo J. Kim;Sathya N. Ravi;Maxwell D. Collins

  • 3D texture analysis for classification of second harmonic generation images of human ovarian cancer

    Bruce Wen;Bruce Wen;Kirby R. Campbell;Karissa Tilbury;Oleg Nadiarnykh

  • Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination

    Won H. Kim;Deepti Pachauri;Charles Hatt;Moo. K. Chung

  • Multivariate General Linear Models (MGLM) on Riemannian Manifolds with Applications to Statistical Analysis of Diffusion Weighted Images

    Hyunwoo J. Kim;Barbara B. Bendlin;Nagesh Adluru;Maxwell D. Collins

  • Texture analysis applied to second harmonic generation image data for ovarian cancer classification

    Bruce L. Wen;Molly A. Brewer;Oleg Nadiarnykh;James D. Hocker

  • Multi-resolution statistical analysis of brain connectivity graphs in preclinical Alzheimer's disease

    Won Hwa Kim;Nagesh Adluru;Moo K. Chung;Ozioma C. Okonkwo

  • MobileDets: Searching for Object Detection Architectures for Mobile Accelerators

    Yunyang Xiong;Hanxiao Liu;Suyog Gupta;Berkin Akin

Frequent Co-Authors

Moo K. Chung
Moo K. Chung University of Wisconsin–Madison
Baba C. Vemuri
Baba C. Vemuri University of Florida
Rebecca L. Koscik
Rebecca L. Koscik University of Wisconsin–Madison
Glenn Fung
Glenn Fung American Family Insurance
Ozioma C. Okonkwo
Ozioma C. Okonkwo University of Wisconsin–Madison
Andrew L. Alexander
Andrew L. Alexander University of Wisconsin–Madison
Sanjay Asthana
Sanjay Asthana University of Wisconsin–Madison
Anil K. Jain
Anil K. Jain Michigan State University
Henrik Zetterberg
Henrik Zetterberg University of Gothenburg
Ronald Berezney
Ronald Berezney University at Buffalo, State University of New York

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