Presenting in ASA sectional meeting
PhD Candidate (Major in Statistics)
Dept. of Mathematics, University of Mississippi
Hume Hall 208
(662) 380-4564 | mhasan4@olemiss.edu
I am a Ph.D. candidate (Major in Statistics) expecting graduation in May 2024 at the Dept. of Mathematics, University of Mississippi. I am looking for a postdoc position/faculty position to start my career in Teaching and research. My research interests are Machine learning \Statistical Learning: GAN model, Reinforcement learning, optimization, and neural networks. Besides, I like to work in Bayesian statistics, time series analysis, and Big data.
Education:
Ph.D. in Mathematics (Concentration in Statistics), University of Mississippi, USA. Expected Graduation date: May 2024.
Dissertation: Error analysis and convergence rates of f-divergence for generative adversarial networks (GANs). Advisor: Dr. Hailin Sang.
M.S. in Mathematics (Major in Statistics), University of Mississippi, USA. Graduation date: May 2022.
M.S. in Mathematics, Jahangirnagar University, Dhaka, Bangladesh. Graduation date: May 2014.
Thesis: New algorithmic approach to design layout in facility layout planning problems. Advisor: Dr. Md Sharif Uddin.
B.S. in Mathematics, Jahangirnagar University, Dhaka, Bangladesh. Graduation date: May 2012.
Research Interest:
Machine Learning /Statistical Learning: GAN model, Optimization, Deep learning, Neural network.
Statistical consulting, Bayesian statistics, Time series, and Big Data.
Teaching Experience:
Graduate Teaching Assistant, August 2019-Present, Dept. of Mathematics, University of Mississippi ,USA
Lecturer, January 2015 - August 2019, BRAC University, Dept. of Mathematics & Natural Sciences (MNS) Dhaka, Bangladesh
Research Experience:
Research Fellow, March-October, 2018, ICE Lab, Dept. of Computer Science and Engineering, Polytechnic di Torino, Italy
Projects: Bi-level Optimization. Advisor: Dr. Guido Perboli.
Research Internship:
Health data Research Assistant, Summer, 2023, Center for Pharmaceutical Marketing and Management (CPMM), University of Mississippi. USA
Projects: 1. Data scaling analysis for Poisson and gamma generalized linear model
2. Geographically weighted regression model with spatial point data.
Advisor: Dr. Bentley & Dr. K. Bhattacharya.
Summer school reserach and Training
Big Data Summer School, IBM Research Institute, Almaden July 9-22, 2023
Course studied: Matrix and Tensor algebra computation and sketching techniques by MATLAB.
Instructor: Dr. Clarkson, Dr. Horesh, Dr. Ubaru, (IBM), Dr. Misha Kilmer (Tufts University), Dr. Tamara Kolda (MathSci.ai).
Funded by Simons Laufer Mathematical Sciences Institute .
Machine Learning Theory Summer School, Princeton University June 25-30, 2023
Course studied: Statistical mechanics of deep learning dynamics, Wasserstein gradient flows for sampling and estimation, Exact analysis of deep learning in high-dimensions, Regimes of training in DDNs: Neural Tangent Kernel, Feature Learning, and Sparsity, Dynamical mean-field theory and the replica method.
Instructor: Dr. Pehlevan (Harvard), Dr. Rigollet (MIT), Dr. Pennington, and Dr. Adlam (Google Brain), Arthur Jacot (NYU)
Funded by NSF & Princeton University (ORFE).
Summer School in Bio-statistics, University of Washington June 25-30, 2022
Course studied: Statistical genetics, Bayesian Statistics and Multi-variable statistics for genetics using R.
Instructor: Dr. Bruce Weir, Dr. Ken Rice (UW).
Funded by NSF, Regeneron & GSK Pharmaceuticals.