Pinki Khatun

Dr. Pinki Khatun

Postdoctoral Researcher

Numerical Optimization and Data Analysis Research Group (NODA)

Department of Industrial Engineering

University of Florence

Email: pinki.khatun@unifi.it|pinkikhatun.nla@gmail.com

Research Interest

Numerical Linear Algebra
Preconditioning
Scientific Machine Learning

Biography

Dr. Pinki Khatun is currently a Postdoctoral Researcher in the Department of Industrial Engineering at the University of Florence, Italy, working under the supervision of Prof. Margherita Porcelli on the project “Numerical Methods for Optimization Problems on Manifolds,” within the framework of MOLE (Manifold Constrained Optimization and LEarning). Previously, she worked as a Postdoctoral Fellow in the Department of Mathematics at the Indian Institute of Technology Gandhinagar (IITGN), under the supervision of Dr. Abhinav Jha, from May to October 2025. She pursued her Ph.D. in Mathematics at the IIT Indore, under the guidance of Prof. Sk. Safique Ahmad, and defended her thesis in May, 2025. She holds an M.Sc. and B.Sc (Hons.) in Mathematics from Aliah University, Kolkata. She is deeply engaged in research in Numerical Linear and Multilinear Algebra, specifically developing efficient and scalable iterative methods and preconditioners to accelerate the Krylov subspace methods to solve large sparse linear systems. Pinki's research contributions include the design of robust preconditioners to accelerate Krylov subspace methods like GMRES and MINRES, the derivation of structured condition numbers, and backward error analysis for stability and sensitivity studies. Recently, she has expanded her research to include multilinear systems and tensor decompositions. She has authored several publications in leading journals, including Linear Algebra and its Applications, Journal of Computational and Applied Mathematics, Linear and Multilinear Algebra, and Electronic Transactions on Numerical Analysis. She is committed to fostering collaboration across disciplines and translating mathematical advancements into practical applications in computational science and engineering. Pinki is dedicated to continuing her research in these fields and contributing to the development of efficient numerical methods for real-world computational challenges.

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