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Intro
Courses
Materials
Philosophy
History
Students

UMBC GTA · IUT Faculty · 10+ years

Teaching & Mentorship

Graduate teaching assistantships at UMBC (Advanced Computer Architecture, Advanced Machine Learning, Digital Image Processing, Circuit Theory, PLD) plus four-and-a-half years as faculty at Islamic University of Technology—focused on hardware intuition, reproducible labs, and clear feedback.

Explore courses Teaching philosophy

Courses taught

Representative offerings—expand each card for outcomes and format.

Advanced Computer Architecture (CMPE/CMSC 611)

UMBC · Graduate · Spring 2023 – Present

GTA support across multiple semesters for architecture depth topics—pipelines, memory hierarchies, cache design, and quantitative performance reasoning students apply in assignments and exams.

Outcomes

Role: recitations, grading, and office hours aligned with the lead instructor's syllabus.

  • Emphasis on performance and energy trade-offs across the memory hierarchy
  • Debugging mindset for simulation, written problems, and architectural design exercises

Advanced Machine Learning (CMPE 678)

UMBC · Graduate · Spring 2022

GTA for graduate ML course covering supervised and unsupervised learning, deep neural networks, and modern learning frameworks—bridging mathematical foundations to practical implementations.

Outcomes

Outcomes: students connect statistical theory to PyTorch/TensorFlow implementations with reproducible experiments and honest evaluation.

  • Lab assistance with Python, PyTorch, Scikit-learn, and Keras workflows
  • Feedback on model evaluation, reproducibility, and technical write-ups

Digital Image Processing (ENEE 612 / CMSC 691)

UMBC · Graduate · Fall 2022

Graduate TA for image processing bridging linear algebra, spatial and frequency-domain transforms, and practical filtering exercises in MATLAB and Python.

Outcomes

Outcomes: students connect mathematical structure to code and visual results they can explain.

  • Lab assistance with MATLAB / Python workflows
  • Feedback on reports and reproducible figures

Circuit Theory (CMPE 306)

UMBC · Undergraduate · Spring 2022

GTA for introductory circuit theory—KVL/KCL, AC/DC analysis, impedance, and measurement discipline using bench instruments and simulation tools.

Outcomes

Outcomes: students leave with stronger lab notebooks and clearer write-ups of what they measured.

  • Bench-level debugging, oscilloscope and multimeter use
  • Bridging analytical methods to SPICE simulation results

Programmable Logic Devices & Electronic Circuits (CMPE 415 / 314)

UMBC · Undergraduate · Spring 2021

GTA for PLD and electronics sequences—Boolean design, HDL entry, FPGA toolchain steps, and foundational electronic circuits lab.

Outcomes

Outcomes: students complete structured labs from schematic / HDL entry through simulation and demo.

  • Vivado / Quartus flow guidance and HDL debugging
  • Timing analysis and testbench habits introduced early

Faculty courses (IUT · 2016 – 2021)

Islamic University of Technology · Gazipur, Bangladesh

Assistant Professor & Lecturer covering theory and laboratory instruction: Semiconductor Devices, Advanced Electronics I, Numerical Methods, VLSI Circuits, Digital Electronics, Peripherals & Microprocessor, Signal & System, and AC Circuit lab.

Outcomes

Outcomes: theory paired with MATLAB, Python, CAD, LabVIEW, and Simulink laboratory practice.

  • Large-enrollment lecture + lab coordination across 6+ concurrent lab sections
  • Assessment design with transparent rubrics; simulation and bench-verification components

Course materials

Sample resources—replace links with your LMS or static files.

Image Processing

Lab briefings & visualization notes

Open
All courses

Contact for syllabi or collaboration

Email

Teaching philosophy

How I design the learning experience.

“Clarity is kindness. I teach so students can explain ideas to a teammate at a whiteboard—and know what to measure when things break.” — Mehedi Hasan Galib

Courses blend conceptual maps with hands-on work: short lectures, guided labs, and frequent feedback loops. I emphasize intellectual honesty—naming assumptions, comparing alternatives, and writing so the next reader can continue the work. From VLSI lab benches at IUT to architecture problem sets at UMBC, the principle is the same: measure first, then conclude.

Mentorship extends beyond grades: I help students build portfolios they are proud of, practice technical communication, and connect classroom themes to internships and research opportunities. Ten-plus years across two continents have reinforced that structured feedback cycles—not just content delivery—are what stick.

Rigor with empathy High standards paired with actionable feedback and multiple ways to demonstrate mastery.
Collaboration that teaches Structured peer review so students learn to give and receive technical critique.
Evidence over vibes Metrics, experiments, and postmortems—so opinions become testable claims.

Teaching history

A concise timeline of roles and themes.

2021 — 2025

Graduate TA · UMBC

Advanced Computer Architecture (CMPE/CMSC 611, Spring 2023 – present), Digital Image Processing (ENEE 612 / CMSC 691, Fall 2022), Advanced Machine Learning (CMPE 678, Spring 2022), Circuit Theory (CMPE 306, Spring 2022), Programmable Logic Devices (CMPE 415, Spring 2021), and Electronic Circuits (CMPE 314, Spring 2021)—recitations, grading, and student mentoring.

2016 — 2021

Assistant Professor & Lecturer · IUT

Theory: Semiconductor Devices, Advanced Electronics I, Numerical Methods. Lab: VLSI Circuits, Digital Electronics, Advanced Electronics I, Peripherals & Microprocessor, Signal & System, AC Circuit, Numerical Methods Lab, Simulation Lab—large-enrollment lecture and lab coordination with MATLAB, CAD, and LabVIEW.

2012 — 2013

Part-time faculty · AUST

Digital System Design laboratory instruction at Ahsanullah University of Science and Technology, Dhaka (short appointment, Nov 2012 – Jan 2013).

Student supervision

Representative supervised students and topics.

Mentorship

Graduate & undergraduate researchers

UMBC / IUT

Guidance on reproducible experiments, FPGA/RTL debugging habits, ML model evaluation, and writing for coursework and publication tracks—spanning UMBC GTA roles and IUT faculty supervision.

Open

Collaborative student projects

Course-integrated

Structured milestones, code review–style feedback, and portfolio-ready deliverables—scoped for FPGA, ML, architecture, or circuits coursework aligned with CMPE 415, 611, 678.