Hi! Welcome to my website! :)
As a Stanford Energy Fellow, I focus on developing emerging memory technologies using oxide semiconductors and low dimensional materials for energy-efficient AI, advised by Prof. H.-S. Philip Wong and Prof. Alberto Salleo.
I obtained my PhD in Electrical and Computer Engineering from the Georgia Institute of Technology, advised by Prof. Eric M. Vogel. My PhD research focused on adaptive oxide-based brain-inspired analog and in-memory computing devices. By exploring optimizations at the material, device, and system levels, in collaboration with IBM, I worked toward enhancing the performance and energy-efficiency of these devices.
PhD in Electrical and Computer Engineering, 2024
Georgia Institute of Technology
MS in Electrical and Computer Engineering, 2022
Georgia Institute of Technology
Materials Engineering, 2019
Purdue University
BSc in Materials Engineering, 2017
Bangladesh University of Engineering and Technology
Georgia Tech ECE Featured Graduate, Spring 2024: GT ECE Feature; FB, GT ECE; LinkedIn, GT ECE; IG, GT ECE; Twitter, GT ECE
Stanford Energy Postdoctoral Fellowship 2024: Stanford Feature; Georgia Tech Feature; IG, GT ECE; LinkedIn, GT ECE
MRS Graduate Student Award 2023: GT ECE Feature; Georgia Tech MSE Feature; MRS Feature, Twitter, GT MSE; FB, GT MSE; IG, GT MSE; LinkedIn, GT ECE; LinkedIn, GT MSE
APL Machine Learning Outstanding Oral Presentation Award, MRS 2023: GT ECE Feature; Twitter, GT ECE; LinkedIn, GT ECE
Outstanding Graduate Student Award, Georgia Tech ECE 2023: GT ECE Feature; LinkedIn, GT ECE
EECS Rising Stars 2023: EECS Rising Stars Feature
Cadence Scholarship 2023: Acceswire News Feature; Cadence Design Systems Feature; Georgia Tech Feature; X, GT ECE; FB, GT ECE
IBM PhD Fellowship Award 2022-2024: IBM Official Feature; GT ECE Feature
“The scientific equations we seek are the poetry of nature.” –Prof. Chen Ning Yang
“Success is not final, failure is not fatal: it is the courage to continue that counts.” –Winston S. Churchill