BIOGRAPHY
Dr. Sibarama Panigrahi is presently working as an Assistant Professor in the Department of Computer Science and Engineering, NIT Rourkela, Odisha, India. He has completed his M.Tech and Ph.D. in Computer Science and Engineering from Veer Surendra Sai University of Technology, Odisha, India. He has been sanctioned with four research grants from major funding agencies of India like Science and Engineering Research Board (SERB), Indian Council of Medical Research (ICMR), Odisha State Higher Education Council (OSHEC) and Hindalco. Recently, He has developed and deployed an electricity load forecasting software employing deep learning models for predicting the electricity load of Western Odisha in an Interval of 15 Minutes for the next 2 days for India’s one of the major Power Distribution Company Tata Power Western Odisha Distribution Limited (TPWODL) through his research project sponsored by OSHEC. The software is being used by Tata Power Western Odisha Distribution Limited (TPWODL) for Power Planning and Management. For this received letter of appreciation from TPWODL and Vice-Chancellor Sambalpur University. He has published more than 40 research papers in reputed Journals and Conferences. His research interest includes Swarm and Evolutionary Algorithms, Machine Learning, Deep Learning and Time Series Forecasting. He has served as a reviewer of more than 30 reputed international SCI Journals. He is a reviewer of SERB project evaluation team. He has delivered more than five invited technical talks in Seminars, Symposia, Webinars, Faculty Development Programs and Workshops in institutions of national importance. He is a Senior member of IEEE and presently working on developing Crude Oil Price Forecasting Methodologies employing Deep Learning Models through his project sponsored by SERB, Govt. of India. Apart from research, he loves to teach, deliver talks and learn by discussing with the audience.
EXPERTISE INFORMATION
Research Group
- Intelligent Computing and Computer Vision
Areas of Interest
- Time Series Forecasting
- Machine Learning & Deep Learning
- Soft Computing
Sibarama Panigrahi Assistant Professor Grade-I
Computer Science and Engineering
panigrahis@nitrkl.ac.in
38
PUBLICATIONS2
DOCTORAL STUDENTS2
CONTINUING EDUCATIONPERSONAL INFORMATION
Sibarama Panigrahi
Assistant Professor Grade-I
Computer Science and Engineering
Room Number: CS-303
Department of Computer Science and Engineering, National Institute of Technology Rourkela, Sundargarh, Odisha, India - 769008
2019
Ph.D.
Computer Science and EngineeringVeer Surendra Sai University of Technology (Formerly UCE Burla)
2013
M.Tech
Computer Science and EngineeringVeer Surendra Sai University of Technology (Formerly UCE Burla)
2009
B.Tech
Computer Science and EngineeringMajhighariani Institute of Technology and Science
Teaching Experience
- Computer Science and Engineering, Sambalpur University Institute of Information Technology, 26 Sep 2016 - 31 Mar 2023
Total Publications: 38
S. Panigrahi and H. Behera,"A hybrid ETS–ANN model for time series forecasting", Engineering Applications of Artificial Intelligence, vol.66, pp.49-59, Elsevier 2017, 10.1016/j.engappai.2017.07.007 Article
S. Panigrahi and H. Behera,"A study on leading machine learning techniques for high order fuzzy time series forecasting", Engineering Applications of Artificial Intelligence, vol.87, pp.103245, Elsevier 2020, 10.1016/j.engappai.2019.103245 Article
S. Panigrahi and H. Behera,"Time series forecasting using differential evolution-based ANN Modelling scheme", Arabian Journal for Science and Engineering, vol.45, no.12, pp.11129–11146, Springer 2020, 10.1007/s13369-020-05004-5 Article
R., H., and S. Panigrahi,"A novel probabilistic intuitionistic fuzzy set based model for high order fuzzy time series forecasting", Engineering Applications of Artificial Intelligence, vol.99, pp.104136, Elsevier 2021, 10.1016/j.engappai.2020.104136 Article
R. M. Pattanayak, H. S. Behera, and S. Panigrahi,"A novel high order hesitant fuzzy time series forecasting by using mean aggregated membership value with support vector machine", Information Sciences, vol.626, pp.494-523, Elsevier 2023, 10.1016/j.ins.2023.01.075 Article
Introduction to Data Science using Python Computer Science and Engineering (Short-term Course)
- Coordinator
- 20 May 2024 - 24 May 2024
- Brochure
Recent Trends in Time Series Forecasting using Deep Learning Models Computer Science and Engineering (Short-term Course)
- Coordinator
- 25 Dec 2023 - 29 Dec 2023
- Brochure
- CS2005 : Data Structures and Algorithms {Theory}
- CS2061 : Data Structure Applications and Algorithms {Theory}
- CS3303 : Computer Vision {Theory}
- CS6510 : Deep Learning {Theory}
- CS2081 : Data Structure Applications and Algorithms Laboratory {Practical}
- CS4374 : Computer Vision Laboratory {Practical}
- CS6475 : Soft Computing Laboratory {Practical}
Ph.D. Students [1]
Artificial Intelligence for Smart Health Care
Anindita JenaEnrolled: Jul 2023ContinuingCo-Supervisor
Executive Ph.D. Students [1]
Application AI/ML on Agriculture Input management
Niladri Bihari MohantyEnrolled: Aug 2023ContinuingCo-Supervisor
Awards And Honours
- Received Best Paper Award in recognition of the paper entitled “Forecasting Crude Oil Prices: A Machine Learning Perspective” at the 2nd International Conference on “Computing, Communication and Learning”, held during 29th to 31st August 2023, organized by Department of CSE, National Institute of Technology Warangal and sponsored by SERB, Department of Science and Technology, Govt. of India., 2023
- Qualified UGC NET in Computer Science and Applications for Assistant Professor in July 2016., 2016
- University Silver Medal for the Best Computer Science and Engineering Post Graduate for the year 2013, 2013
- Received MHRD Fellowship for M.Tech (July 2011-June 2013), 2011
Memberships / Fellowships
- IEEE Senior Member with ID:92911061, 2022