Dr Mullai Thiagu holds a PhD in Engineering Design from the Indian Institute of Technology Madras and brings over 15 years of experience across academia, research, space technology, VLSI, embedded systems, and high-performance computing. She has held academic positions at Krea University, Sri City, where she currently serves as Senior Lecturer in Computer Science and previously served as Visiting Assistant Professor.

Her doctoral research focused on developing heterogeneous CPU-GPU frameworks for accelerating 2D and 3D Digital Image Correlation algorithms. Her research interests include high-performance parallel computing, computer vision, digital image processing, VLSI design, FPGA prototyping and validation, and embedded systems. Her research has resulted in journal and conference publications focusing on Digital Image Correlation, GPU-accelerated computing, heterogeneous architectures, and Bi-Quintic B-Spline image interpolation.

Dr Thiagu has taught undergraduate, postgraduate, and interdisciplinary Computer Science courses and has mentored student projects and research-oriented coursework. Prior to her academic career, she worked with Satish Dhawan Space Centre (ISRO), NIELIT Chennai, and the semiconductor industry, contributing to VLSI and embedded systems, FPGA-based systems, computer architecture, and hardware–software co-design. She has also conducted technical training and executive education programmes, including GPU Computing programmes under the National Supercomputing Mission.

Research
Her research focuses on GPU-accelerated computing, computer vision, and digital image processing, with particular emphasis on developing efficient computational frameworks for image-based analysis. Her doctoral research explored heterogeneous CPU–GPU architectures for accelerating 2D and 3D Digital Image Correlation algorithms, addressing computational efficiency and performance for full-field displacement measurement.

As part of her future research plans, she is interested in exploring technology-assisted prenatal stress monitoring, using non-invasive sensing, signal and image processing, and computational methods to investigate physiological and behavioural indicators associated with stress during pregnancy. This direction would provide opportunities for interdisciplinary collaboration across computer science, healthcare, signal processing, and data analytics, with an emphasis on developing computational tools for monitoring and analysis.

Her broader technical interests include VLSI, FPGA, embedded systems, and computer architecture. Her future research will focus on GPU-accelerated, application-oriented computing frameworks integrating image processing, computer vision, heterogeneous architectures, and intelligent sensing.

Publications
• Thiagu, M., Subramanian, S. J., & Nasre, R. High-speed, two-dimensional digital image correlation algorithm using heterogeneous (CPU-GPU) framework. Strain, 56(3), e12342.
• Thiagu, M., Subramanian, S. J., & Nasre, R. (2019). Fast, Sub-pixel Accurate Digital Image Correlation Algorithm Powered by Heterogeneous (CPU-GPU) Framework. In Advancement of Optical Methods & Digital Image Correlation in Experimental Mechanics, Vol. 3, pp. 95–102, Springer.
• Thiagu, M., Nasre, R., & Subramanian, S. J. GPU-Accelerated Triangulation in the Stereo-DIC Algorithm Using a Heterogeneous Framework. SEM Annual Conference and Exposition on Experimental and Applied Mechanics, 2025.
• Thiagu, M., Subramanian, S. J., & Nasre, R. Pyramid-based initial guess estimation for 2D-DIC algorithm realized using heterogeneous (CPU-GPU) framework. International Conference on Digital Image Correlation and Non-contact Experimental Mechanics, Hangzhou, China.
• Thiagu, M., Subramanian, S. J., & Nasre, R. Accelerating Bi-Quintic B-Spline Image Interpolation on a GPU. IEEE HiPC Student Research Symposium, 2018 (Poster)

Teaching Modules
Dr Mullai Thiagu has over six years of university-level teaching experience in Computer Science, in addition to experience in technical training, curriculum development, and mentoring. She has taught undergraduate, postgraduate, and interdisciplinary courses at Krea University, Sri City, where she has served as Visiting Assistant Professor and currently serves as Senior Lecturer in Computer Science. She has taught a range of courses and modules, including Computational Thinking, Data Management, Data Structures and Algorithms, Digital Image Processing, Machine Learning, Information Systems and Data Analytics, GPU Computing, VLSI Design and Embedded Systems.

In addition to university teaching, Dr Thiagu has designed and delivered technical training programmes in FPGA Design, Embedded Systems, VLSI, and GPU Computing. At NIELIT Chennai, she contributed to curriculum development, conducted long-term and short-term programmes, faculty development programmes, and technical training, and mentored BE/BTech final-year projects.

She has conducted GPU Computing programmes under the National Supercomputing Mission and executive education for industry participants, with a focus on hands-on, interdisciplinary, and research-oriented learning.