CV

My interdisciplinary experience spans neuromorphic computing, machine learning hardware, semiconductor process integration, and circuit design. These variants are tailored to highlight specific skillsets relevant to different opportunities.

Download my complete academic CV to learn more about my education, research experience, publications, and professional achievements.

Basics

Name Md Zesun Ahmed Mia
Label PhD Candidate in Electrical Engineering
Email zesun.ahmed@psu.edu
Phone 814-280-7244
Url https://zesun33.github.io
Summary PhD candidate in Electrical Engineering at Penn State specializing in neuromorphic computing, machine learning hardware, and device-circuit co-design. Former Graduate Technical Intern at Intel Corporation with experience in advanced semiconductor manufacturing and AI-driven process optimization.

Work

  • 2025.05 - 2025.07
    Graduate Technical Intern
    Intel Corporation
    Designed and executed Design of Experiments (DOE) for exploratory thin film deposition projects, contributing to advanced technology node development.
    • Designed and executed Design of Experiments (DOE) for exploratory thin film deposition projects, contributing to advanced technology node development
    • Investigated first-of-its-kind process integration tool for advanced technology node development, evaluating integration feasibility and process window optimization
    • Conducted comprehensive material characterization using DSIMS, XRR, stress analysis, and TEM image analysis to validate process performance and material properties
    • Developed predictive analysis framework using AI and machine learning to assess thin film deposition impact on semiconductor process flows and device characteristics
  • 2024.08 - 2025.05
    Graduate Teaching Assistant
    Pennsylvania State University
    Teaching and supporting Cadence Virtuoso, schematic/layout design, and lab courses.
    • Cadence Virtuoso instruction
    • Schematic design
    • Layout design
    • Lab supervision
  • 2022.08 - Present
    Graduate Research Assistant
    Pennsylvania State University
    Research in neuromorphic computing, ML hardware, and device-circuit co-design. Leading comprehensive projects on spintronic/ferroelectric devices and advanced ML accelerators.
    • Developed fabrication processes for and characterized spintronic devices; performed electrical characterization of Ferroelectric FETs (FeFETs)
    • Engineered physics-based device models using TCAD (Silvaco/Sentaurus) and developed compact models in Verilog-A and MATLAB
    • Architecting novel, high-performance ML accelerator tailored for Transformer-based workloads with hardware-software co-design
    • Pioneered hardware-aware training framework integrating fabricated spintronic devices into system-level designs
    • Investigated advanced neuromorphic algorithms (Equilibrium Propagation, Astromorphic Transformer) vs traditional DNN/SNN models
    • Developed adaptive STDP learning rule for Dynamic SNNs enabling continual learning for cybersecurity applications
  • 2021.02 - 2022.08
    Lecturer
    University of Liberal Arts Bangladesh
    Taught Digital Circuit Design, Device Physics, and Power Electronics courses.
    • Digital Circuit Design
    • Device Physics
    • Power Electronics
    • Course instruction
  • 2020.09 - 2021.07
    R&D Engineer (Part-time)
    SEMWAVES Ltd.
    Designed 50 KW solar-hydro hybrid system for Bangladesh implementation.
    • Solar-hydro hybrid systems
    • Renewable energy design
    • 50 KW system implementation
  • 2020.02 - 2021.02
    Lecturer (Part-time)
    Bangladesh University of Engineering & Technology (BUET)
    Supervised laboratory sessions for Digital Circuit Design (Cadence Virtuoso) and Power Electronics courses.
    • Digital Circuit Design lab supervision
    • Cadence Virtuoso instruction
    • Power Electronics lab sessions
    • Student mentoring and guidance

Education

  • 2022.08 - 2024.08

    University Park, PA, USA

    MS
    Pennsylvania State University
    Electrical Engineering
    • Neuromorphic Computing for Lifelong Learning
  • 2022.08 - 2027.08

    University Park, PA, USA

    PhD
    Pennsylvania State University
    Electrical Engineering
    • Neuromorphic Computing
    • Device-Circuit Co-design
    • ML Hardware
  • 2015.02 - 2019.04

    Dhaka, Bangladesh

    BSc
    Bangladesh University of Engineering & Technology (BUET)
    Electrical and Electronic Engineering
    • Electronics
    • Signal Processing
    • Power Systems

Publications

Skills

Programming Languages
Python
MATLAB
C++
Verilog
Shell scripting
Modern Coding & AI Tools
Advanced use of generative AI tools (Cursor, Copilot, VSCode, Cline) for research, teaching, and code development
Skilled in prompt engineering and integrating AI assistants into academic workflows
EDA/Simulation Tools
Cadence Virtuoso
Spectre
HSPICE
TCAD Sentaurus
COMSOL Multiphysics
ModelSim
Synopsys (Design Compiler, PrimeTime, VCS)
Device/Process Characterization
AFM
SEM
Electrical Testing
Hall effect characterization
TEM
Reliability testing
Magnetic Probe Station (SemiProbe Magnetic Probing System)
Keithley and Keysight instruments with LabVIEW
Nanofabrication Process Skills
Optical Lithography (MLA150) and Electron Beam Lithography (EBPG5200)
Ion beam dry etching and wet chemical etching
Material deposition using Temescal FC-2000 Evaporator (CVD)
Profilometer, Ellipsometer, Optical Microscopes characterization
Data Analysis & Statistical Tools
Pandas
NumPy
JMP
Jupyter
Data Visualization
Statistical Analysis
Machine learning frameworks and neuromorphic simulation tools

Languages

English
Fluent
Bengali
Native speaker

Interests

Research
Neuromorphic Computing
ML Hardware
Edge AI
Semiconductor Technology
Teaching
Course Design
Mentoring
Lab Supervision
Academic Instruction

Awards

References

Dr. Abhronil Sengupta
PhD Advisor and Associate Professor at Pennsylvania State University. Expert in neuromorphic computing and device-circuit co-design.

Projects

  • 2023.01 - 2025.01
    Astromorphic Transformers
    Research on bio-inspired transformer architectures published in IEEE TCDS, focusing on cognitive and developmental computing systems.
    • IEEE TCDS Publication
    • Bio-inspired AI
    • Transformer Architecture
  • 2023.01 - 2024.10
    Electronic Braille Device
    Development of ultra low cost, low power, high speed electronic Braille device for accessibility applications.
    • Accessibility Technology
    • Low Power Design
    • iCACCESS 2024