Upkar Singh
Ph.D., Indian Institute of Science, BengaluruMy work centres on computational algorithms and parallel computing methodologies to address complex, large-scale problems across scientific domains. I develop mathematically rigorous yet practical solutions that bridge theoretical computer science with applications in geosciences, biological systems, and scientific data analysis. A core focus lies in designing scalable numerical approaches that maintain precision while adapting to modern computing architectures, from high-performance clusters to distributed systems. This involves creating novel optimization techniques for simulation frameworks, intelligent data processing pipelines for multidimensional scientific datasets, and domain-specific algorithmic innovations that push the boundaries of what’s computationally feasible. My research philosophy emphasizes both the foundational aspects of algorithm design—such as stability, efficiency, and provable correctness—and their real-world implementation to enable transformative discoveries in fields ranging from seismic modelling to genomic analysis. By integrating principles from computer science and engineering, mathematics and domain sciences, I aim to build tools that not only solve computational bottlenecks but also reveal new insights in our understanding of complex natural and engineered systems.
Dr. Upkar has been an Assistant Professor at Chanakya University’s School of Engineering since June 2025. His research focuses on computational algorithms, parallel computing, and scientific computing, with applications in geosciences, data visualization, and computational biology.
His published work includes influential studies on ocean salinity tracking and scalable systems for ocean data analysis, appearing in leading journals such as Computers & Geosciences and Computer Graphics Forum. In his 2022 and 2024 papers, he pioneered advection-based methods to trace salinity propagation in the Indian Ocean, offering novel computational tools for environmental modelling.
At Chanakya University, Dr. Upkar teaches Discrete Mathematics in the core curriculum and actively supports academic leadership in computer science faculty hiring. He is a member of the upcoming Centre of Integrated Public Health (CIPH), where he collaborates with biologists, and computer scientists to develop next-generation tools that bridge algorithmic innovation with pressing real-world challenges in public health services in India.
- Ph.D., Computer Science and Automation, 2025, Indian Institute of Science, Bangalore, Karnataka
- M. Tech., Computer Science and Engineering, 2018, National Institute of Technology, Calicut, Kerala
- B.Tech., Computer Science and Engineering, 2016, Guru Nanak Dev University, Amritsar, Punjab
- Upkar Singh, T.M. Dhipu, P.N. Vinayachandran, and Vijay Natarajan. Front and skeleton features based methods for tracking salinity propagation in the ocean. Computers & Geosciences, 159:104993, 2022. ISSN 0098-3004. doi: https://doi.org/10.1016/j.cageo.2021.104993. URL: https://www.sciencedirect.com/science/article/pii/S0098300421002764.
- Upkar Singh, P.N. Vinayachandran, and Vijay Natarajan. Advection-based tracking and analysis of salinity movement in the indian ocean. Computers & Geosciences, 182:105493, 2024. ISSN 0098-3004. doi: https://doi.org/10.1016/j.cageo.2023.105493. URL: https://www.sciencedirect.com/science/article/pii/S0098300423001978.
- Toshit Jain, Varun Singh, Vijay Kumar Boda, Upkar Singh, Ingrid Hotz, P.N. Vinayachandran, and Vijay Natarajan. pyParaOcean: A System for Visual Analysis of Ocean Data. In Workshop on Visualisation in Environmental Sciences (EnvirVis). The Eurographics Association, 2023. ISBN 978-3-03868-223-3. doi: https://doi.org/10.2312/envirvis.20231100.
- Toshit Jain, Upkar Singh, Varun Singh, Vijay Kumar Boda, Ingrid Hotz, Sathish S. Vadhiyar, P. N. Vinayachandran, and Vijay Natarajan. A scalable system for visual analysis of ocean data. Computer Graphics Forum, January 2025. ISSN 1467-8659. doi:https://doi.org/10.1111/cgf.15279. URL http://dx.doi.org/10.1111/cgf.15279