Vijay Kumar

Assistant Professor

Ph.D., Clarkson University

Campus Image

Education

  • Postdoctoral Researcher, Data Science & Environmental Health, Columbia University (2023–2025)
  • PhD, Mathematics, Clarkson University, USA (2018–2023)
  • MS, Applied Data Science, Clarkson University, USA (2022–2023)
  • MS, Mathematics, Clarkson University, USA (2018–2020)
  • MS, Applied Mathematics, NED University of Engineering and Technology, Karachi (2013–2015)
  • BS, Mathematics, University of Sindh, Jamshoro (2009–2012)

Awards & Honors

  • Principal Investigator, US National Science Foundation (NSF) ACCESS Computing Resources Allocation (2024–2026)
  • Travel Grant, Institute for Mathematical and Statistical Innovation (IMSI), University of Chicago (2025)
  • Travel Grant, Centre de Recherches Mathématiques (CRM), University of Montreal (2025)
  • Travel Grant, Institute for Computational and Experimental Research in Mathematics (ICERM), Brown University (2024, 2025, 2026)
  • Travel Grant, National Center for Atmospheric Research (NCAR), Boulder, CO (2024)
  • Travel Grant, Data Science Institute, University of Chicago (2024)
  • Clarkson University Diversity, Equity and Inclusion Distinguished Award (2024)
  • Clarkson University Phalanx Leadership Award (2023)
  • Clarkson University Phalanx Inducted Fellow (2023)
  • Clarkson University Graduate Teaching Assistantship (2018–2022)
  • US-Pak Knowledge Corridor HEC PhD Scholarship (2018–2023)
  • Postgraduate Fellowship, SISSA, Trieste, Italy (2016)

Service & Outreach

  • Panelist, Balancing Act: Climate Mitigation and Adaptation, Conference on Climate Crisis in Pakistan, Pakistani Student Association (PSA), Columbia University (2024)
  • Judge, Undergraduate Statistics Project Competition (USPROC), American Statistical Association (2024, 2025)
  • Founding President, Pakistani Student Association (PSA), Clarkson University (2022–2023)
  • Judge, Science Fair, State University of New York, Potsdam (2018)

Teaching & Research Experience

  • New Jersey City University: Assistant Professor of Data Science (2025–Present)
  • Brown University: Research Investigator / Research Assistant Professor, Data Science and Epidemiology (2025–Present)
  • Columbia University, Mailman School of Public Health: Postdoctoral Research Scientist (2023–2025)
  • Clarkson University: Adjunct Instructor & NSF REU Coordinator, Department of Mathematics (2022–2023)
  • Clarkson University: Graduate Teaching Assistant, Department of Mathematics (2018–2022)
  • SMI University, Karachi: Lecturer, Mathematics and Statistics (2016–2018)
  • NED University of Engineering and Technology, Karachi: Lecturer, Department of Mathematics (2013–2016)

Biography

Dr. Vijay Kumar is a data scientist and applied mathematician whose research applies Bayesian statistics, machine learning, and spatiotemporal modeling to challenges in environmental and health sciences. His work includes the development of the Bayesian Nonparametric Ensemble (BNE) algorithm in collaboration with researchers at MIT and Harvard University, deployed on US National Science Foundation (NSF) funded high performance computing infrastructure for nationwide air pollution prediction. He also developed the open source BNER R package, now widely used by the environmental health research community, and studies the impact of environmental exposures on vulnerable populations through epidemiological modeling.

Dr. Kumar earned his PhD in Mathematics from Clarkson University alongside an MS in Applied Data Science and an MS in Mathematics, following an MS in Applied Mathematics from NED University of Engineering and Technology and a BS in Mathematics from the University of Sindh, Pakistan. He subsequently completed a postdoctoral appointment at Columbia University’s Mailman School of Public Health before joining Brown University as Research Assistant Professor and New Jersey City University as Assistant Professor of Data Science. He serves as Principal Investigator on an NSF ACCESS Accelerate Allocation and has authored more than 15 peer reviewed publications while actively mentoring graduate and undergraduate researchers.

His interdisciplinary collaborations span institutions including MIT, Harvard University, Columbia University, Brown University, Washington University in St. Louis, The Ohio State University, Baylor University, Smith College, Oberlin College, and Clarkson University. He has presented research at leading universities and scientific forums including MIT, the University of Chicago, Columbia University, NASA HAQAST, and the New York Academy of Medicine. Since 2013, he has taught undergraduate and graduate courses in mathematics, statistics, data science, and machine learning, with a strong focus on applying mathematical methods to real world data driven research.


Research Interests

  • Bayesian Statistics
  • Machine Learning
  • Data Science
  • Environmental Health
  • Air Quality Modeling
  • Spatiotemporal Modeling
  • Statistical Learning
  • Epidemiology
  • Environmental Exposure Assessment
  • High Performance Computing
  • Low Cost Air Quality Sensors
  • Applied Mathematics

Selected Publications

  • Yaqoob, I., Nepal, S., Kumar, V., & Chaudhry, S. “Multi-city Bi-pollutant Calibration of Low-cost PM Sensors Using Machine Learning,” IEEE Access (2026)
  • Kumar, V., Benavides, J., Carrillo-Gallegos, C., Speyer, G., & Kioumourtzoglou, M.-A. “Scalable Bayesian Nonparametric Ensemble (BNE) for Spatio-temporal Air Pollution Predictions Using High-performance Computing,” 29th Annual IEEE HPEC Conference (2025)
  • Kumar, V., Senarathna, D., Gurajala, S., Dhaniyala, S., Sur, S., & Mondal, S. “Effect of Distance and Number of PM2.5 Low-cost Sensors on Correction Models,” International Journal of Data Science and Analytics (2025)
  • Benavides, J., Carrillo-Gallegos, C., Kumar, V., Chillrud, L. G., Paisley, J., Coull, B., Fiore, A., & Kioumourtzoglou, M.-A. “BNER: A Collaborative Workflow for Air Quality Modeling and Uncertainty Characterization Using the Bayesian Nonparametric Ensemble,” Journal of Environmental Management (2025)
  • Yaqoob, I., Kumar, V., & Chaudhry, S. A. “Machine Learning Calibration of Low-cost Sensor PM2.5 Data,” 2024 IEEE International Symposium on Systems Engineering (ISSE) (2024)
  • Kumar, V., Sur, S., Senarathna, D., Gurajala, S., Dhaniyala, S., & Mondal, S. “Quantifying Impact of Correlated Predictors on Low-cost Sensor PM2.5 Data Using KZ Filter,” Frontiers in Applied Mathematics and Statistics (2024)
  • Kumar, V., Senarathna, D., Gurajala, S., Olsen, W., Sur, S., Mondal, S., & Dhaniyala, S. “Spectral Analysis Approach for Assessing Accuracy of a Low-cost Air Quality Sensor Network,” Atmospheric Measurement Techniques, 16(21) (2023): 5415–5427
  • Mondal, S., Chaipitakporn, C., Kumar, V., Wangler, B., Gurajala, S., Dhaniyala, S., & Sur, S. “COVID-19 in New York State: Effects of Demographics and Air Quality on Infection and Fatality,” Science of the Total Environment (2022)
  • Kumar, V., Athavale, P., Clark, J., Mondal, S., & Sur, S. “Differential Impact of COVID-19 Risk Factors on Ethnicities in the United States,” Frontiers in Public Health, 9 (2021): 743003

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