Mahmudul Hassan
Summary
Doctoral researcher in Mechanical Engineering specializing in laser-based manufacturing, computer vision, and micro-polishing. Experienced in high-power laser platform design, multiphysics simulation, and image-driven quality control. Dedicated educator with experience mentoring 900+ students, advancing applied engineering learning, and leading impactful community initiatives.
Education
Ph.D., Mechanical Engineering
M.S., Mechanical Engineering
B.S., Mechanical Engineering
Experience
Graduate Research Assistant
- Engineered ultra-fast X-ray imaging (50,000 fps, 60k+ frames) to decode keyhole dynamics in laser polishing; extracted geometry with ±5 µm accuracy via bi-regional Otsu binarization, elevating finish quality by predicted ~25% and reducing instability by 40%.
- Developed and validated a synchronized 200 W laser-LabVIEW DAQ system through ~50 heating trials; minimized activation timing error to <5 ms and established predictive thermal models.
- Collaborated with scientists from BIAS, TU Wien, and Argonne National Lab to advance laser X-ray imaging, contributing to multiple high-impact joint publications.
- Designed and deployed a next-generation 3 kW laser platform with five programmable beam profiles and thermal-stable optics, accelerating experimental throughput by ~60%.
Graduate Consultant, Global Quality Excellence
- Reduced brake system part rejection rates by projected 20% through defect analysis of 20+ parts and recommending process changes saving $50k/year.
Graduate Teaching Assistant
- Taught Manufacturing: Metals and Automation to 900+ students, integrating metal production, automation, and metrology to raise average scores by ~15%.
- Created PLC lab manuals and programming guides, leading 90+ labs annually and enabling 90% success in ladder logic automation.
Graduate Research Assistant
- Built and validated 3D ABAQUS FEA models against chip morphology and surface topography; explored 15+ parameter sets to establish optimal feed and tool geometry.
- Developed the first high-fidelity ABAQUS/Explicit micro-milling simulation for AM CFRP; engineered anisotropic Johnson-Cook material models to replicate laminate failure.
Skills
Technical
- MATLAB, Python
- ABAQUS, SolidWorks
- MasterCam, PLC
- CNC Machining, SEM
- Docker, Illustrator
Analysis
- Image Processing
- Finite Element Analysis
- Manufacturing Optimization
- Metrology, 3D Printing
Other
- Project Leadership
- Technical Communication
- Data Analysis & Visualization
- Design and Prototyping
Key Projects
- High-Performance MD5 Hash Cracking: Built multi-level parallel MD5 cracker (CPU, MPI, CUDA), boosting throughput from 0.356 Mhash/s to 6.778 Ghash/s (~19,000x).
- Advanced Finite Element Analysis: Implemented mixed FE methods to reduce numerical locking, improving displacement accuracy ~20%.
- Movement Detection with OpenCV: Created real-time webcam motion tracker with time-stamped archival for low-cost security.
- Reduced-Order Modeling with ML: Built SVD-based models predicting PDE solutions with <5% error and 95% faster runs.
Selected Publications
- P. Faue, L. Rathmann, M. Möller, Mahmudul Hassan, et al. "High-speed X-ray study of process dynamics caused by surface features during continuous-wave laser polishing", CIRP Annals, 2023.
- Md Mahmudul Hassan, J. Ma, M. P. Jahan, "A Comparative Numerical Investigation on Machining of Laminated and 3D Printed CFRP Composites", IMECE 2022.
- Mahmudul Hassan, J. Ma, M. P. Jahan, "Numerical modeling and simulation of machining of 3D printed CFRP composite", Manufacturing Letters, 2022.
- N. M. Cococcetta, M. P. Jahan, et al. incl. Md Mahmudul Hassan, "Sustainable Post-Processing of 3D Printed Thermoplastic CFRP Composites Using Cryogenic Machining", Journal of Manufacturing Processes, 2021.
- ...and 5+ other High Impact Journal Publications.