National Institute of Technology Rourkela

राष्ट्रीय प्रौद्योगिकी संस्थान राउरकेला

ଜାତୀୟ ପ୍ରଯୁକ୍ତି ପ୍ରତିଷ୍ଠାନ ରାଉରକେଲା

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Faculty Profile

ORCID ID
Scopus ID
Researcher ID
Google Scholar ID

BIOGRAPHY

Dr. Sibarama Panigrahi is currently working as an Assistant Professor in the Department of Computer Science and Engineering at 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 awarded research grants from major funding agencies in India, including the Anusandhan National Research Foundation (ANRF) and the Odisha State Higher Education Council (OSHEC). As part of an OSHEC-sponsored project, he has developed and deployed an electricity load forecasting software for Tata Power Western Odisha Distribution Limited (TPWODL), one of India’s leading power distribution companies. He has over 10 years of experience in teaching and research. He has authored and co-authored over fifty research papers published in reputed international journals and conferences. His research interests include Soft Computing, Machine Learning, Deep Learning, Data Science, and Time Series Forecasting. He has served as a reviewer of more than 30 reputed international SCI Journals. He has also served as a project reviewer for ANRF and BRNS (Department of Atomic Energy) projects. He is an Associate Editor of the PLOS ONE Journal and the Scientific Reports Journal.

EXPERTISE INFORMATION

Research Group
  • Intelligent Computing and Computer Vision
Areas of Interest
  • Time Series Forecasting
  • Machine Learning & Deep Learning
  • Soft Computing
  • Data Science

Sibarama Panigrahi
ଶିବରାମ ପାଣିଗ୍ରାହୀ Assistant Professor Grade-I

Computer Science and Engineering

panigrahis@nitrkl.ac.in / panigrahi.sibarama@gmail.com

0661 - 246 2377

7377302566

Biosketch

53

PUBLICATIONS

2

SPONSORED PROJECTS

1

CONSULTANCY PROJECTS

12

DOCTORAL STUDENTS

6

CONTINUING EDUCATION

PERSONAL INFORMATION

Sibarama Panigrahi

Assistant Professor Grade-I

Computer Science and Engineering

Room Number: CS-336

Department of Computer Science and Engineering, National Institute of Technology Rourkela, Sundargarh, Odisha, India - 769008

2019

Ph.D.
Computer Science and Engineering
Veer Surendra Sai University of Technology (Formerly UCE Burla)

2013

M.Tech
Computer Science and Engineering
Veer Surendra Sai University of Technology (Formerly UCE Burla)

Teaching Experience
  • Computer Science and Engineering,  National Institute of Technology Rourkela,   03 Apr 2023 - Present
  • Computer Science and Engineering,  Sambalpur University Institute of Information Technology,   26 Sep 2016 - 31 Mar 2023

Consortium of Technologies for Sustainable Agriculture, Health , Energy and Environment Anusandhan National Research Foundation (ANRF), Science & Engineering Research Board (SERB)
  • Co-Investigator
  • 60
  • Running   Sponsored
Studies on Deep Learning Models for Crude Oil Price Forecasting Science & Engineering Research Board (SERB)
  • Principal Investigator
  • 26
  • Running   Sponsored
Scientific Study for Slope Stability Monitoring and Strata Management Plan BALASORE ALLOYS LIMITED
  • Co-PI
  • 05 Nov 2024 - 04 Nov 2026
  • Running   Consultancy

21
GOOGLE SCHOLAR H-INDEX 30
GOOGLE SCHOLAR I10-INDEX 17
SCOPUS H-INDEX
Total Publications: 53
View All Publications

S. K. Purohit and S. Panigrahi,"Decomposition-based hybrid methods employing statistical, machine learning, and deep learning models for crude oil price forecasting", Neural Computing and Applications, pp.1-46, Springer, April 2025, 10.1007/s00521-025-11178-6       Article

S. S. Pradhan and S. Panigrahi,"A study and development of high-order fuzzy time series forecasting methods for air quality index forecasting", Journal of Forecasting, pp.1-24, Wiley, May 2024, 10.1002/for.3153       Article

S. K. Purohit and S. Panigrahi,"Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models", Information Sciences, vol.658, pp.120021, Elsevier, February 2024, 10.1016/j.ins.2023.120021       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

S. S. Pradhan, S. Panigrahi, S. K. Purohit, and J. K. Dash,"Study and development of hybrid and ensemble forecasting models for air quality index forecasting", Expert Syatems, Wiley, September 2023, 10.1111/exsy.13449       Article

ENVIRONOMETRICS using AI & ML Humanities and Social Sciences (Workshop)
  • Co-Coordinator
  • 15 Dec 2025 - 19 Dec 2025
  • Brochure
Fourth International Conference on Computing, Communication and Learning (COCOLE) Computer Science and Engineering (Conference)
Applied Data Science Computer Science and Engineering (Short-term Course)
Crisp and Fuzzy Time Series Forecasting using Deep Learning Techniques (CFTSFDL - 2024) Computer Science and Engineering (Workshop)
Introduction to Data Science using Python Computer Science and Engineering (Short-term Course)
Recent Trends in Time Series Forecasting using Deep Learning Models Computer Science and Engineering (Short-term Course)

  • CS2005 : Data Structures and Algorithms {Theory}
  • CS2008 : Database Engineering {Theory}
  • CS2011 : Introduction to AI and ML {Theory}
  • CS2061 : Data Structure Applications and Algorithms {Theory}
  • CS3303 : Computer Vision {Theory}
  • CS6315 : Data Science {Theory}
  • CS6355 : Applied Data Science {Theory}
  • CS6510 : Deep Learning {Theory}
  • CS1000 : Basic Programming {Practical}
  • CS1010 : Programming for Problem Solving {Practical}
  • CS2064 : Database Design Laboratory {Practical}
  • CS2081 : Data Structure Applications and Algorithms Laboratory {Practical}
  • CS2672 : AI and ML Laboratory {Practical}
  • CS4374 : Computer Vision Laboratory {Practical}
  • CS6070 : Product Development Laboratory {Practical}
  • CS6385 : Data Science Laboratory {Practical}
  • CS6475 : Soft Computing Laboratory {Practical}

Ph.D. Students [7]
Studies on Machine Learning Techniques for Crude Oil Price Forecasting
Sourav Kumar Purohit
Enrolled:
Graduated :  2025
Supervisor
Forecasting of Air Quality Index using Machine Learning Techniques
Sushree Subhaprada Pradhan
Enrolled:
Graduated :  2024
Supervisor
Machine Learning and Deep Learning in Time Series Analytics
Kedar Kumar Dora
Enrolled: Jul 2025
Continuing
Supervisor
Crude Oil Price Forecasting
Chinmaya Ranjan Padhan
Enrolled: Jul 2024
Continuing
Supervisor
Air Quality Index Forecasting
Baikuntha Sahu
Enrolled: Jul 2024
Continuing
Supervisor
Time Series Classification
Souveek Roy
Enrolled: Jul 2024
Continuing
Supervisor
Artificial Intelligence for Smart Health Care
Anindita Jena
Enrolled: Jul 2023
Continuing
Co-Supervisor
Executive Ph.D. Students [5]
Ph.D.
Sanjib Kumar Parida
Enrolled: Jul 2025
Continuing
Co-Supervisor
AI and ML (including Deep Learning, NLP, AI for Digital Healthcare)
Asutosh Sarangi
Enrolled: Jul 2025
Continuing
Co-Supervisor
FuzzyTime Series forecasting
Garimella Vivekananda
Enrolled: Jul 2024
Continuing
Supervisor
Forecasting of Stock Price using Machine Learning Techniques
Aditya Ranjan Patra
Enrolled: Jul 2024
Continuing
Supervisor
Application AI/ML on Agriculture Input management
Niladri Bihari Mohanty
Enrolled: Aug 2023
Continuing
Co-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,   2016
  • University Silver Medal for the Best Computer Science and Engineering Post Graduate for the year,   2013
  • Received MHRD Fellowship for M.Tech,   2011
Memberships / Fellowships
  • IEEE Senior Member with ID:92911061,   2022