Dr. Mohd. Arshad

Dr. Mohd. Arshad

Associate Professor

Department of Mathematics
Indian Institute of Technology Indore

Copula Modelling Data Science Estimation Theory Information Theory Ranking and Selection Time Series Analysis
Email arshad@iiti.ac.in
Designation Associate Professor
Department Mathematics
Institute Indian Institute of Technology Indore
Research Group Statistics and Data Science Research Group

About

Dr. Mohd. Arshad is an Associate Professor in the Department of Mathematics at IIT Indore. Previously, he was an Assistant Professor at IIT Indore and Aligarh Muslim University. He earned his Ph.D. in Statistics from the Indian Institute of Technology Kanpur in 2015, under the supervision of Professor Neeraj Misra . He distinguished himself early on as a Gold Medalist in M.Sc. Statistics from CSJM University, Kanpur.

Dr. Arshad's research spans several areas of statistics and data science, including ranking and selection, copula modelling, machine learning, data science, estimation theory, and generalised order statistics. His contributions are reflected in over 50 research papers published in esteemed international journals, as well as two co-authored/edited books. At IIT Indore, Dr. Arshad leads the Statistics and Data Science Research Group, comprising Ph.D. scholars, postdoctoral researchers, and UG/PG project students. Together, they work on theoretical and computational challenges at the forefront of statistics and data science.

Beyond research, Dr. Arshad is actively engaged in the academic community, serving on the editorial boards of multiple journals and scientific societies. With over a decade of teaching experience across undergraduate and postgraduate courses, he remains committed to advancing statistical science through research, mentorship, and education.

55+

Journal/Conference Publications

9

Book Chapters

3

Books

25+

Invited Talks

20+

Student Projects Guided

Education

Ph.D.

Department of Mathematics and Statistics
Indian Institute of Technology Kanpur

M.Sc.

Statistics
C.S.J.M. University, Kanpur

B.Sc.

Statistics
C.S.J.M. University, Kanpur

Employment Details

Associate Professor

Department of Mathematics
Indian Institute of Technology Indore
September 23, 2025 – Present

Assistant Professor

Department of Mathematics
Indian Institute of Technology Indore
July 21, 2020 – September 22, 2025

Assistant Professor

Statistics and Operations Research
Aligarh Muslim University, Aligarh
March 06, 2014 – July 20, 2020

Editorial Experience

Associate Editor

Journal: Journal of Statistical Theory and Applications
Publisher: Springer

Associate Editor

Journal: Probability and Statistics
Publisher: Frontiers in Applied Mathematics and Statistics

Review Editor

Journal: Mathematics of Computation and Data Science
Publisher: Frontiers

Former Associate Editor

Journal: The Aligarh Journal of Statistics

Research Projects

Statistical Analysis of the Selected Treatment using Drop-the-Losers Designs

Funding Agency: ANRF (SERB), Govt. of India – CORE Research Grant
Status: Ongoing

Detection of Communities in Network

Funding Agency: IIT Indore
Status: Completed

Improved Estimation Based on Records

Funding Agency: SERB (DST), Government of India – MATRICS
Status: Completed

Selection and Related Estimation Problems

Funding Agency: UGC, New Delhi
Status: Completed

Statistical Modelling in Ranking and Selection

Funding Agency: Accelerate Vigyan, SERB (DST) – Karyashala
Status: Completed

Featured Publications

RoBoSS: A Robust, Bounded, Sparse, and Smooth Loss Function for Supervised Learning

M. Akhtar, M. Tanveer, M. Arshad

IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 47(1), 149–160 (2025)

A New Class of Copulas Having Dependence Range Larger Than FGM-Type Copulas

S. G. Zachariah, M. Arshad, A. K. Pathak

Statistics & Probability Letters, Elsevier, Vol. 206, 109988 (2024)

Selecting the Best of Two Gamma Populations Having Unequal Shape Parameters

N. Misra, M. Arshad

Statistical Methodology, Elsevier, Vol. 18, 41–63 (2014)

Research Articles

IEEE • Elsevier • Springer • Taylor & Francis • CRC Press

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