Computer Science & Engineering and Information Technology (CSE&IT)

Dr. Hari Singh

Dr. Hari Singh
Assistant Professor (SG)
( 91) 01792-239296
hari.singh@juit.ac.in
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Biography :

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. Sentiment analysis for text data using efficient vectorization and other techniques through NLP, ML and DL.

2. Computer aided diagnostics system for disease prediction using ML and DL techniques.

3. Waste management using waste generation prediction, waste classification and other methodologies with ML and DL techniques.

4. Objects detection and recognition using ML and DL techniques.

5. Improving efficiency of distributed computing platforms such as Apache Spark and workload execution by
(a) tuning internal parameters and I/O features
(b) application and architecture level scheduling
(c) resource management techniques etc.

Author Publication Profile:
Conference(s) :