Mr. Md Ahasan Ahamed | Analytical Chemistry | Analytical Chemistry Award

Bangladesh University of Textiles, Bangladesh

Profiles

• ORICD Profile
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Early Academic Pursuits

The academic journey began with a B.Sc. in Mechanical Engineering from Bangladesh University of Engineering and Technology (BUET) in 2014. During this phase, research was conducted on electricity generation from compression of speed breakers, demonstrating an early interest in applied engineering solutions. Further academic advancement led to a M.S. in Mechanical Design and Production Engineering from Konkuk University, South Korea (2020-2022), where the research focused on developing a pre-programmed microdroplet generator for controlling chemical concentrations. Currently, pursuing a Ph.D. in Electrical Engineering at Pennsylvania State University (2022-2026), integrating Recombinase Polymerase Amplification (RPA) with nanopore sensing for point-of-care disease detection.

Professional Endeavors

With over six years of teaching and research experience, the professional journey includes roles as Lecturer and Assistant Professor at Bangladesh University of Textiles (BUTEX) and BGMEA University of Fashion & Technology (BUFT) from 2014 to 2020. Transitioning into the research domain, positions were held as a Graduate Research Assistant at Konkuk University (2020-2022) and Pennsylvania State University (2022-Present). Recently, appointed as a Visiting Scholar at Indiana University, Bloomington (2025-Present), further broadening the academic and research exposure.

Contributions and Research Focus

A strong research background in point-of-care (POC) devices, disease diagnosis, and sensor technology has led to significant contributions in designing microfluidic devices and nanopore sensors. Proficiency in biochemical reaction methodologies, including Polymerase Chain Reaction (PCR), Recombinase Polymerase Amplification (RPA), Loop-mediated Isothermal Amplification (LAMP), and CRISPR/Cas12, has played a crucial role in developing diagnostic tools for infectious diseases like Monkeypox, SARS-COVID, Cowpox, and HIV.

Impact and Influence

The research has had a profound impact on healthcare and diagnostic technologies, especially in early detection methods for infectious diseases. The work in integrating machine learning algorithms with sensor-based diagnostics has pushed the boundaries of automation and accuracy in medical testing. The interdisciplinary nature of the research—bridging mechanical design, electrical engineering, and biotechnology—positions it as a key contributor to next-generation disease detection systems.

Academic Citations & Publications

With a growing influence in the academic world, the research work has been recognized with 67 citations, 18 published papers, and 6 conference and poster presentations. The continuous contribution to high-impact journals and international conferences highlights the commitment to advancing knowledge in biomedical engineering and sensor technology.

Technical Skills

Expertise spans across instrumentation, fabrication, and analysis, including hands-on experience with: 3D Printing: Asiga UV Max X43, Ultimaker 3.0, Laser Systems: Universal Laser Systems, Microscopy: Optical Microscopes, Nikon Ti U Inverted Camera, pco.edge 5.5, Sensors & Electronics: Pressure Sensors (PX-309 series, Eve flow series), Axopatch 200b, Molecular Diagnostic Tools: Thermal Cycler (BIORAD T100), Plasma Treatment Machines, Software & Programming: MATLAB, Python, and Machine Learning Algorithms.

Teaching Experience

With over six years of teaching experience, expertise has been shared in Mechanical Engineering, Engineering Drawing, Machine Design, MATLAB, and Python programming with undergraduate students. The ability to bridge theoretical knowledge with hands-on applications has benefited students in engineering and research domains.

Legacy and Future Contributions

Looking ahead, the focus remains on developing innovative diagnostic devices that are cost-effective, rapid, and highly accurate for real-world applications. The integration of machine learning with nanopore sensors will continue to be a significant area of exploration. Additionally, mentoring future researchers and students in interdisciplinary fields will be an integral part of academic and professional contributions.

Notable Publications