e-Prime - Advances in Electrical Engineering, Electronics and Energy - Volume: 12 - Arnab Mitra, Anabik Pal
Welcome to the Department of Computer Science at IISER Berhampur.
As the Chair, I am proud to introduce our institution’s newest academic unit dedicated to Computational Data Sciences. The department was established to drive interdisciplinary research at the intersection of computation, data, and scientific discovery. We work closely with other scientific departments and national institutes on data-intensive challenges that demand automated analysis, ML modeling, and efficient computation.
Our curriculum and research span fundamental, theoretical, and applied domains of computing, machine learning, and data sciences, while integrating modern Artificial Intelligence tools, High-Performance Computing, and Smart IoT applications. With expertise in ML, image analysis, cloud computing, HPC systems, embedded platforms, and smart IoT infrastructure, our faculty leads diverse initiatives in both foundational and applied Computational Data Sciences. We aspire to grow into a dynamic hub of pioneering research and academic excellence.
Supported by strong interdisciplinary collaboration, active faculty–student engagement, and advanced infrastructure—including GPU platforms, HPC servers, and specialized smart/embedded devices—we aim to cultivate innovation, rigor, and real-world impact. We invite you to join us in advancing computational data science and shaping future technologies and scientific discoveries.
The Department of Computer Science is the newest and an actively growing department at IISER Berhampur. Currently offering a minor in BS-MS degree (since 2022) and Ph.D. program in Computational Data Sciences (since 2024), the department offers several theoretical and applied undergraduate and graduate courses ranging from Algorithms and Machine Learning to Programming and Data Analytics. With 2 full-time faculty members and additional honorary/visiting faculty members from diverse research backgrounds, the department offers research opportunities in a variety of computer science domains. With several inter-disciplinary projects being conceptualized in collaboration with research groups from Physics, Chemistry, Biology, Earth sciences and Mathematics departments, the Department of Computer Science at IISER Berhampur offers a welcoming research environment for inquisitive PhD. and post-doctoral researchers enthusiastic to make impactful inventions, discoveries and contributions in newer frontiers of computer scientific research.
e-Prime - Advances in Electrical Engineering, Electronics and Energy - Volume: 12 - Arnab Mitra, Anabik Pal
Computers in Biology and Medicine - Volume: 140 - Anabik Pal, Akshay Chaturvedi, Aditi Chandra, Raghunath Chatterjee, Swapan Senapati, Alejandro F. Frangi, Utpal Garain
Computers in Biology and Medicine - Volume: 138 - Anabik Pal, Zhiyun Xue, Kanan Desai, Adekunbiola Aina F Banjo, Clement Akinfolarin Adepiti, L. Rodney Long, Mark Schiffman, Sameer Antani
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The group aims at understanding the mechanism of evolution of adaptive and non-adaptive characters in organisms. By employing phenotypic manipulation experiments, primarily using laboratory fruit fly populations, his group investigates phenotype - fitness correlations. The group then employs Experimental Evolution to investigate the evolution of these phenotypes in experimental populations in real-time.
The group aims at understanding the mechanism of evolution of adaptive and non-adaptive characters in organisms. By employing phenotypic manipulation experiments, primarily using laboratory fruit fly populations, his group investigates phenotype - fitness correlations. The group then employs Experimental Evolution to investigate the evolution of these phenotypes in experimental populations in real-time.
The group aims at understanding the mechanism of evolution of adaptive and non-adaptive characters in organisms. By employing phenotypic manipulation experiments, primarily using laboratory fruit fly populations, his group investigates phenotype - fitness correlations. The group then employs Experimental Evolution to investigate the evolution of these phenotypes in experimental populations in real-time.
The group aims at understanding the mechanism of evolution of adaptive and non-adaptive characters in organisms. By employing phenotypic manipulation experiments, primarily using laboratory fruit fly populations, his group investigates phenotype - fitness correlations. The group then employs Experimental Evolution to investigate the evolution of these phenotypes in experimental populations in real-time.