Nandha Gopal | Engineering | Editorial Board Member

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Nandha Gopal | Engineering | Editorial Board Member

NANDHA COLLEGE OF TECHNOLOGY | India

Dr. N. Nandhagopal is a distinguished academic and researcher in Electronics, Communication Engineering, and Embedded System Technology, recognized for his extensive contributions to engineering education, research innovation, and academic leadership. With a strong foundation in electronics and applied electronics, further strengthened by advanced degrees including an M.E., Ph.D., and a highly commended D.Sc., he has developed deep expertise in embedded systems, medical image processing, and intelligent computational techniques. His doctoral research, focused on computer-aided diagnosis for automatic detection of brain tumors using MRI imaging, reflects his commitment to impactful, technology-driven healthcare solutions. Over the course of his career, he has held progressively responsible positions across several engineering institutions, beginning as a lecturer and advancing to Assistant Professor, Associate Professor, Professor, Head of Department, and Principal. His leadership roles demonstrate his ability to guide academic programs, mentor faculty, and enhance institutional quality. Throughout his professional journey, he has contributed to curriculum development, research supervision, and the implementation of innovative teaching methodologies aligned with AICTE standards. Dr. Nandhagopal is known for fostering research culture, promoting interdisciplinary collaboration, and integrating emerging technologies into engineering education. His strong academic background, combined with over a decade of teaching and administrative experience, highlights his dedication to advancing engineering knowledge and shaping the next generation of engineers.

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Featured Publications

Nandhagopal, N., & Karnan, M. (2010). Diagnose brain tumor through MRI using image processing clustering algorithms such as Fuzzy C Means along with intelligent optimization techniques. In Proceedings of the 2010 IEEE International Conference on Computational Intelligence and Computing Research (pp. 241–246). IEEE.

Navaneethan, S., & Nandhagopal, N. (2021). RE-PUPIL: Resource efficient pupil detection system using the technique of average black pixel density. Sādhanā, 46(3), 114.

Satya Sreedhar, P. S., & Nandhagopal, N. (2022). Classification similarity network model for image fusion using ResNet50 and GoogLeNet. Intelligent Automation & Soft Computing, 31(3), 1–12.

Radhakrishnan, M., Panneerselvam, A., & Nachimuthu, N. (2020). Canny edge detection model in MRI image segmentation using optimized parameter tuning method. Intelligent Automation & Soft Computing, 26(6), 1–10.

Nandhagopal, N., Navaneethan, S., Nivedita, V., Parimala, A., & Valluru, D. (2021). Human eye pupil detection system for different iris database images. Journal of Computational and Theoretical Nanoscience, 18(4), 1239–1242.

Ammasi Periasamy | Engineering | Best Researcher Award

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Ammasi Periasamy | Engineering | Best Researcher Award

University of Virginia | United States

Dr. Periasamy is an internationally renowned scientist recognized for his groundbreaking contributions to the development of advanced optical microscopy techniques for imaging and analyzing single cells, tissues, and living organisms. His pioneering research focuses on designing and developing cutting-edge optical methodologies to study molecular interactions and cellular processes in real time. A major highlight of his recent work is the development of the Fluorescence Lifetime Redox Ratio (FLIRR), an innovative technique used to investigate cellular metabolism and mitochondrial dysfunction, with promising applications in the early detection of prostate cancer and its correlation with PSA levels. Widely regarded as one of the pioneers of fluorescence lifetime imaging microscopy (FLIM), Dr. Periasamy has made significant advances in monitoring calcium oscillations within living cells and developing 2- and 3-color confocal, multiphoton, and FLIM-based Förster resonance energy transfer (FRET) imaging systems for visualizing protein interactions in living specimens. His prolific scholarly output includes over 185 refereed journal publications, numerous book chapters, and proceedings, along with more than 200 invited lectures at national and international platforms. As a respected leader in his field, he has edited three books and serves as the series editor for the “Cellular and Clinical Imaging” book series, encompassing 11 volumes. Dr. Periasamy also plays a key role in the global microscopy community as the chairperson and organizer of the annual SPIE conference on Multiphoton Microscopy in the Biomedical Sciences since 2001 and conducts a highly regarded hands-on training workshop on FLIM, FRET, and metabolic imaging at the University of Virginia each year. In recognition of his outstanding scientific achievements and contributions to optical microscopy, he was elected a Fellow of the SPIE Optical Society in 2012.

Profile: Scoups | Orcid | Google Scholar

Featured Publications

Alam, S. R., Mahadevan, M. S., & Periasamy, A. (2023). Detecting RNA–Protein Interactions with EGFP-Cy3 FRET by Acceptor Photobleaching. Current Protocols, 3(2), e689.

Norambuena, A., Sun, X., Wallrabe, H., Cao, R., Sun, N., Pardo, E., Shivange, N., Wang, D. B., Post, L. A., Ferris, H. A., Hu, S., Periasamy, A., & Bloom, G. S. (2022). SOD1 mediates lysosome-to-mitochondria communication and its dysregulation by amyloid-β oligomers. Neurobiology of Disease, 169, Article 105737.

Zhang, J., Wallrabe, H., Siller, K., Mbogo, B., Cassidy, T., Alam, S. R., & Periasamy, A. (2025). Measuring metabolic changes in cancer cells using two-photon fluorescence lifetime imaging microscopy and machine-learning analysis. Journal of Biophotonics, 18, e202400426.

 Alam, S. R., Wallrabe, H., Christopher, K. G., Siller, K. H., & Periasamy, A. (2022). Characterization of mitochondrial dysfunction due to laser damage by 2-photon FLIM microscopy. Scientific Reports, 12, Article 11938.

Zhou, L., & El-Deiry, W. S. (2009). Multispectral fluorescence imaging. Journal of Nuclear Medicine, 50(10), 1563-1566.