World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
13006
World Ranking
6698
National Ranking
2956

Research.com Recognitions

  • 2015 - Fellow of the Indian National Academy of Engineering (INAE)

Overview

May D. Wang is affiliated with the Georgia Institute of Technology in the United States and has contributed extensively to the field of medicine, with a primary focus on the intersection of artificial intelligence and healthcare. Their work spans multiple subfields including molecular biology, artificial intelligence, radiology, nuclear medicine and imaging, cognitive neuroscience, and public health, environmental and occupational health.

The scientist's recent papers cover a range of topics related to medical AI applications and public health challenges. These include:

  • "Multimodal deep learning models for early detection of Alzheimer's disease stage" (2021, Scientific Reports)
  • "Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis" (2020, BMC Medical Informatics and Decision Making)
  • "Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review" (2022, IEEE Reviews in Biomedical Engineering)
  • "Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?" (2020, IEEE Open Journal of Engineering in Medicine and Biology)
  • "COVID-19 Automatic Diagnosis With Radiographic Imaging: Explainable Attention Transfer Deep Neural Networks" (2021, IEEE Journal of Biomedical and Health Informatics)

Their frequent coauthors include Wenqi Shi, Yuanda Zhu, Tong Li, Felipe Giuste, and Gilbert C. Gee. This pattern of collaboration reflects a multidisciplinary approach encompassing data science, biomedical engineering, and public health.

May D. Wang has published extensively in widely recognized venues, with multiple works appearing in:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • SSRN Electronic Journal
  • Scientific Reports
  • IEEE Journal of Biomedical and Health Informatics

The main topics addressed across their body of work include machine learning applications in healthcare, artificial intelligence approaches to COVID-19 diagnosis, EEG and brain-computer interface technologies, gene expression and cancer classification, AI in healthcare and education, issues related to obesity, physical activity, and diet, as well as biomedical text mining and ontologies.

Among subfields, molecular biology, artificial intelligence, and cognitive neuroscience feature prominently, indicating an integration of computational techniques with complex biological systems.

May D. Wang was awarded the title of Fellow of the Indian National Academy of Engineering (INAE) in 2015.

Best Publications

  • GoMiner: a resource for biological interpretation of genomic and proteomic data

    Barry R Zeeberg;Weimin Feng;Geoffrey Wang;May D Wang

  • The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

    Leming Shi;Gregory Campbell;Wendell D. Jones;Fabien Campagne

  • A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

    Zhenqiang Su;Paweł P. Łabaj;Sheng Li;Jean Thierry-Mieg

  • Bioconjugated quantum dots for multiplexed and quantitative immunohistochemistry

    Yun Xing;Qaiser Chaudry;Christopher Shen;Koon Yin Kong

  • Multimodal deep learning models for early detection of Alzheimer's disease stage.

    Janani Venugopalan;Li Tong;Hamid Reza Hassanzadeh;May D. Wang

  • Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

    Wenqian Zhang;Ying Yu;Falk Hertwig;Falk Hertwig;Jean Thierry-Mieg

  • Detecting and correcting systematic variation in large-scale RNA sequencing data

    Sheng Li;Paweł P Łabaj;Paul Zumbo;Peter Sykacek

  • Omic and Electronic Health Record Big Data Analytics for Precision Medicine

    Po-Yen Wu;Chih-Wen Cheng;Chanchala D. Kaddi;Janani Venugopalan

  • Pathology imaging informatics for quantitative analysis of whole-slide images.

    Sonal Kothari;John H Phan;Todd H Stokes;May D Wang

  • Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study

    Sheng Li;Scott W Tighe;Charles M Nicolet;Deborah Grove

  • Hand-held Spectroscopic Device for In Vivo and Intraoperative Tumor Detection: Contrast Enhancement, Detection Sensitivity, and Tissue Penetration

    Aaron M. Mohs;Michael C. Mancini;Sunil Singhal;James M. Provenzale;James M. Provenzale

  • Automated cell counting and cluster segmentation using concavity detection and ellipse fitting techniques

    Sonal Kothari;Qaiser Chaudry;May D. Wang

  • LncADeep: an ab initio lncRNA identification and functional annotation tool based on deep learning

    Cheng Yang;Cheng Yang;Longshu Yang;Man Zhou;Haoling Xie

  • (Glyco)sphingolipidology: an amazing challenge and opportunity for systems biology

    Alfred H. Merrill;May Dongmei Wang;Meeyoung Park;M. Cameron Sullards

  • DeeperBind: Enhancing prediction of sequence specificities of DNA binding proteins

    Hamid Reza Hassanzadeh;May D. Wang

  • Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis

    Li Tong;Jonathan Mitchel;Kevin Chatlin;May D. Wang

  • Sphingolipidomics: a valuable tool for understanding the roles of sphingolipids in biology and disease.

    Alfred H. Merrill;Todd H. Stokes;Amin Momin;Hyejung Park

  • k-Nearest neighbor models for microarray gene expression analysis and clinical outcome prediction

    R. M. Parry;W. Jones;T. H. Stokes;J. H. Phan

  • Effect of low-expression gene filtering on detection of differentially expressed genes in RNA-seq data

    Ying Sha;John H. Phan;May D. Wang

  • Combining Two-Dimensional Diffusion-Ordered Nuclear Magnetic Resonance Spectroscopy, Imaging Desorption Electrospray Ionization Mass Spectrometry, and Direct Analysis in Real-Time Mass Spectrometry for the Integral Investigation of Counterfeit Pharmaceuticals

    Leonard Nyadong;Glenn A. Harris;Stéphane Balayssac;Asiri S. Galhena

  • A Review of Emerging Technologies for the Management of Diabetes Mellitus

    Konstantia Zarkogianni;Eleni Litsa;Konstantinos Mitsis;Po-Yen Wu

  • DeeperBind: Enhancing Prediction of Sequence Specificities of DNA Binding Proteins

    May D Wang;Hamid Reza Hassanzadeh

Frequent Co-Authors

Shuming Nie
Shuming Nie University of Illinois at Urbana-Champaign
Leming Shi
Leming Shi Fudan University
Weida Tong
Weida Tong National Center for Toxicological Research
Matthias Fischer
Matthias Fischer University of Cologne
Alfred H. Merrill
Alfred H. Merrill Georgia Institute of Technology
Christopher E. Mason
Christopher E. Mason Cornell University
Hong Fang
Hong Fang National Center for Toxicological Research
Huixiao Hong
Huixiao Hong United States Food and Drug Administration
Cesare Furlanello
Cesare Furlanello Fondazione Bruno Kessler
Benedikt Brors
Benedikt Brors German Cancer Research Center

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 can open up numerous related fields and interdisciplinary career pathways. Many students interested in this area consider combining their studies with specialized degrees in fields like environmental engineering, mechanical engineering, and data science. Online options make these degrees more accessible and budget-friendly for international and working students.

For example, you may explore the cheapest online environmental science degree programs to blend sustainable practices with technology. If you’re drawn to engineering, understanding mechanical engineering degree cost can help you plan for an affordable, industry-focused education.

Physics is another foundational discipline in tech, and finding the cheapest online physics degree can allow you to expand your analytical skills. As data-driven industries grow, a data science degree can position you at the forefront of technology and innovation.

These online degree pathways provide flexibility, cost savings, and diverse career opportunities in today’s competitive tech landscape.

Best Scientists Citing May D. Wang

Trending Scientists