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Arkajyoti Saha

Arkajyoti Saha

Assistant Professor, Department of Statistics, University of California, Irvine

Biography

Arkajyoti Saha, Ph.D., is Assistant Professor in the Department of Statistics at the University of California, Irvine. His research focuses on developing statistical methods for spatially dependent data and high-dimensional inference, with applications in environmental science, genetics, and computational biogeochemistry. Saha received a Ph.D. in Biostatistics from Johns Hopkins Bloomberg School of Public Health, where his dissertation examined the analysis of large correlated data with applications in statistical genetics and spatial statistics.

Saha has developed widely-used statistical software for spatial data analysis, including the BRISC R package with over 47,000 CRAN downloads and the RandomForestsGLS package with over 24,000 downloads. His methodological work on random forests for spatially dependent data was published in the Journal of the American Statistical Association, and his research on nearest-neighbor Gaussian processes for identifying spatially variable genes appeared in Nature Communications. He received the Margaret Merrell Award for outstanding research by a doctoral student in biostatistics and the Joint Statistical Meetings Student Paper Award from the American Statistical Association.

Prior to joining UC Irvine, Saha was a Postdoctoral Fellow in the Department of Statistics at the University of Washington, where he also held appointments as a UW Data Science Postdoctoral Fellow at the eScience Institute and as a Postdoctoral Fellow with the Simons Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems. He completed his Master of Statistics and Bachelor of Statistics degrees at the Indian Statistical Institute in Kolkata, India.

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Education

  • Ph.D. in Biostatistics, Johns Hopkins Bloomberg School of Public Health, 2021
  • M.Stat. in Statistics, Indian Statistical Institute, 2016
  • B.Stat. in Statistics, Indian Statistical Institute, 2014
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Distinctions

  • Joint Statistical Meetings Student Paper Award, American Statistical Association, Section on Statistical Computing, 2018
  • Symposium on Data Science & Statistics Student Funding Award, American Statistical Association, 2018
  • UW Data Science Postdoctoral Fellowship, eScience Institute, University of Washington, 2022
  • The Margaret Merrell Award, Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 2020
  • Biostatistics first-year comprehensive examination Award, Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 2017
  • Academic Senate Council on Research, Computing and Libraries (CORCL) Award, School of ICS, University of California, Irvine, 2025
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Areas of Expertise

  • Spatial Statistics
  • Fuzzy Clustering Algorithms
  • Random Forests for Dependencies
  • Bootstrap Inference Methods
  • Gaussian Process Approximations
  • Correlation Thresholding Independence Tests
  • Marine Ecosystem Biogeochemical Modeling

Recent Publications

  • Arkajyoti Saha, Daniela Witten, Jacob Bien, “Inferring independent sets of Gaussian variables after thresholding correlations”, Journal of the American Statistical Association: Theory and Methods, vol. 120, no. 549, pp. 370-381, 2025.
  • Arkajyoti Saha, Sumanta Basu, Abhirup Datta, “Random forests for spatially dependent data.”, Journal of the American Statistical Association: Theory and Methods, vol. 118.541, pp. 665-683, 2023.
  • Lukas M. Weber, Arkajyoti Saha, Abhirup Datta, Kasper D. Hansen, Stephanie C. Hicks, “nnSVG: scalable identification of spatially variable genes using nearest-neighbor Gaussian processes”, Nature Communications, vol. 14, no. 1, pp. 4059, 2023.
  • Arkajyoti Saha, Sumanta Basu, Abhirup Datta, “RandomForestsGLS: An R package for Random Forests for dependent data.”, Journal of Open Source Software, vol. 7, no. 70, pp. 3780, 2022.
  • Arkajyoti Saha, Abhirup Datta, Sudipto Banerjee, “Scalable Predictions for Spatial Probit Linear Mixed Models Using Nearest Neighbor Gaussian Processes.”, Journal of Data Science, vol. 20, no. 4, 2022.
  • Abhirup Datta, Arkajyoti Saha, Misti Levy Zamora, Colby Buehler, Lei Hao, Fulizi Xiong, Drew R. Gentner, Kirsten Koehler, “Statistical field calibration of a low-cost PM2.5 monitoring network in Baltimore.”, Atmospheric Environment, vol. 242, pp. 117761, 2020.
  • Arkajyoti Saha, Abhirup Datta, “BRISC: bootstrap for rapid inference on spatial covariances.”, Stat, vol. 7, no. 1, pp. e184, 2018.
  • Arkajyoti Saha, Swagatam Das, “Clustering of fuzzy data and simultaneous feature selection: A model selection approach.”, Fuzzy Sets and Systems, vol. 340, pp. 1-37, 2018.
  • Arkajyoti Saha, Swagatam Das, “On the unification of possibilistic fuzzy clustering: Axiomatic development and convergence analysis.”, Fuzzy Sets and Systems, vol. 340, pp. 73-90, 2018.
  • Arkajyoti Saha, Swagatam Das, “Stronger convergence results for the center-based fuzzy clustering with convex divergence measure.”, IEEE transactions on cybernetics, vol. 49, no. 12, pp. 4229-4242, 2018.
  • Arkajyoti Saha, Swagatam Das, “Feature-weighted clustering with inner product induced norm based dissimilarity measures: an optimization perspective.”, Machine Learning, vol. 106, no. 7, pp. 951-992, 2017.
  • Arkajyoti Saha, Swagatam Das, “Axiomatic generalization of the membership degree weighting function for fuzzy C means clustering: Theoretical development and convergence analysis.”, Information Sciences, vol. 408, pp. 129-145, 2017.
  • Arkajyoti Saha, Swagatam Das, “Geometric divergence based fuzzy clustering with strong resilience to noise features.”, Pattern Recognition Letters, vol. 79, pp. 60-67, 2016.
  • Arkajyoti Saha, Swagatam Das, “Optimizing cluster structures with inner product induced norm based dissimilarity measures: Theoretical development and convergence analysis.”, Information Sciences, vol. 372, pp. 796-814, 2016.
  • Arkajyoti Saha, Swagatam Das, “Automated feature weighting in clustering with separable distances and inner product induced norms - A theoretical generalization.”, Pattern Recognition Letters, vol. 63, pp. 50-58, 2015.
  • Arkajyoti Saha, Swagatam Das, “Categorical fuzzy k-modes clustering with automated feature weight learning.”, Neurocomputing, vol. 166, pp. 422-435, 2015.
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Contact Information

Email: arkajyos@uci.edu

Phone: (949) 824-3276

Address: 2228 Bren Hall, Irvine, CA 92697

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This profile was created with the help of AI.

Last updated on 2/17/2026.