Dr. Hirak Mazumdar is a distinguished Biomedical Researcher and Algorithm Developer with expertise in Computer Vision, Image Processing, and advanced Machine Learning Algorithms. He earned his PhD from Sogang University, South Korea, in collaboration with Samsung Mechatronics R&D, Suwon. Following his doctorate, he served as a Post-Doctoral Fellow at Cheongju National University, South Korea, where he contributed to a Ministry of Semiconductor Design-funded project, developing software for wafer testing during the semiconductor fabrication process using Machine Learning. Dr. Mazumdar then transitioned to the University of Houston, Texas, as a Post-Doctoral Scientist, working on a Department of Energy (DOE)-funded project focused on detecting groundwater contamination using Machine Learning.

Recognized for his academic leadership and mentorship, Dr. Mazumdar's current research interests encompass industrial big data analysis, intelligent medical sensor devices, sensor manufacturing systems, and quality assurance through complex Machine Learning algorithms. He has also gained valuable industry experience working with leading companies such as Samsung and Hyundai, where he specialized in Machine Learning and data fault analysis.

In addition to his work in industry, Dr. Mazumdar's research spans Nanotechnology, Nano Biosensor Simulation, and Computational Biology through numerical simulation. He is also experienced in biomedical image analysis, particularly in analyzing various cell cultures using Image Processing techniques.

My research experience spans across distinct phases, starting from my Ph.D. (2016-2021) to my ongoing post-Ph.D. work (2021-present). During my Ph.D., I focused primarily on sensor data analysis in the semiconductor industry. I developed a sequential and comprehensive algorithm for fault detection in semiconductor sensors, particularly useful during the wafer fabrication process. I investigated sensor correlations and applied machine learning to enhance defect detection and yield analysis, ultimately improving the manufacturing process. One of my significant contributions was observing sensor groupings to predict defects beyond specific threshold values, as documented in my paper "Sequential and comprehensive algorithm for fault detection in semiconductor sensors".

Additionally, I worked on prediction analysis and quality assessment of microwell array images, where I applied machine learning to detect non-circular, doughnut-shaped, and overlapping defects in medical imaging. This enabled me to develop a robust framework for assessing microwell fillings, which involved identifying artifacts in raw images and extracting features for further pattern recognition and analysis, as discussed in my work published in Electrophoresis and Filled a USA Patent (Chung, B. G., Mazumdar, H., Kim, T. H., & Lee, J. M. (2019). U.S. Patent Application No. 16/237,249).

In the post-Ph.D. phase, I have expanded my research into healthcare technology and sustainability, leveraging secure machine learning algorithms for healthcare applications. My work revolves around developing advanced frameworks for early diagnosis and personalized health management using digital health solutions. I have been working on integrating AI-driven systems into healthcare, focusing on remote monitoring, early screening, and digital health platforms like virtual clinics and telemedicine. My goal is to improve patient outcomes through predictive analytics, telemedicine for personalized care, and AI-based disease prevention and management.

Through my work, I aim to contribute to both industrial and healthcare sectors by integrating advanced algorithms with real-world applications, focusing on sustainability and innovation.

Professional Membership: 

1. IEEE Member

2. ACM Professional Member

Journal Editor: 

1. Review Editor: Frontiers in Artificial Intelligence (IF 4.3) (Pattern Recognition)

2. Guest Editor: MDPI Sensors (IF 3.4) Special Issue (Advances in Smart Nanomaterials and Quantum Sensors: Integrating AI/ML for Next-Generation Applications)

Awards: 

1. Samsung Dream Scholarship

2. Fulbright Fellow

3. STEM Ambassador, UHV, Texas, USA