Dr. Hari Singh Assistant Professor (SG) ( 91) 01792-239296 hari.singh@juit.ac.in For More Information Click here
Dr. Hari Singh is PhD, M.Tech and B.Engg. (Honors) in Computer Science & Engineering. He has a teaching experience of 21+ years at JUIT, Waknaghat, Solan (July 2018 – till now), PIET, Panipat (July 2016 – July 2018), and NCCE, Panipat (September 2001 – July 2016), that includes a significant administrative and research experience. His areas of interest are Distributed and Parallel Computing, Grid Computing, Cloud Computing, Machine Learning and Deep Learning, Programming and logic development. He has many awards, honors and recognitions to his credit. He delivered several invited/expert talks on recent research topics at renowned institutes and universities. He has published around 20 research papers/book chapters in SCI/Scopus indexed/peer-reviewed International Journals and edited books. He has also presented and published around 25 research papers in National/International Conferences. He has also worked as editor of proceedings of various International/National Conferences. He has attended/participated in around 45 workshops/FDPs at reputed Institutes/Universities/Organizations. He has organized several Conferences/Seminars/Workshops. He has supervised/supervising several M.Tech/PhD scholars. He has also handled an AICTE sponsored research project under the RPS scheme and two consultancy projects. He has been a member of professional societies such as CSI, ISTE, etc. He has been a member/reviewer of several Scopus-Indexed journals.
Research Interests:
Distributed and Parallel Computing, Grid Computing, Cloud Computing, Machine Learning and Deep Learning, Programming and logic development.
Open Project Titles:
1. Efficient sentiment/text analysis/classification through effective word embedding techniques.
2. Climate change prediction and its impacts on
(a) Extreme weather events such as cloud bursts, landslides etc.
(b) Climate change adaptation in agriculture, water sector, etc.
3. Waste management using waste generation prediction, waste classification, and other methodologies.
4. Computer aided diagnostics system for disease prediction and classification.
5. 5. Improving efficiency of distributed computing platforms such as Apache Spark, Apache Hadoop, Kubernetes, etc. and workload execution through
(a) Tuning internal parameters and I/O features.
(b) Application and architecture level scheduling.
(c) Resource management techniques etc.
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| 2024 (4) | 2023 (4) | 2022 (3) | 2021 (3) | 2020 (1) | 2019 (2) |
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