Dr. Rakesh K. Pandey

About

Dr. Rakesh K. Pandey is an assistant professor at DIT University, India. He has 7+ years of working experience in industry and academics. His research interests include petroleum production optimization, reservoir performance analysis, oil and gas well testing, enhanced oil recovery, reservoir simulation, data analytics and machine learning.

Employment

• DIT University Assistant Professor and Head
  2018 - 2026
• Naithani Oil and Gas Services Private Limited Petroleum Field Engineer
  2017 - 2018
• Chandigarh University Assistant Professor
  2016 - 2017

Education

• Indian Institute of Technology (Indian School of Mines), Dhanbad M. Tech
  2014 - 2016
• Pandit Deendayal Petroleum University B. Tech
  2010 - 2014

Projects & Funding

Projects & funding information is unavailable.

Publications (23)

• Development of Grey Wolf Optimization-Assisted Machine Learning Frameworks for Trend Prediction of Nifty50 Index
  Lecture Notes in Networks and Systems 2027 DOI: 10.1007/978-3-032-19303-2_7
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• Minimum miscibility pressure estimation for CO2‐assisted EOR projects using grey wolf optimized intelligent models
  The Canadian Journal of Chemical Engineering 2026 DOI: 10.1002/cjce.70573
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• Investigation of Meta-Heuristically Tuned ML Frameworks for Well Placement Optimization
  Lecture Notes in Networks and Systems 2026 DOI: 10.1007/978-3-032-19303-2_9
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• Understanding how Artificial Intelligence is redefining the traditional Green HRM Practices for a Sustainable Economy
  MSW MANAGEMENT 2026
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• THE ROLE OF ANALYTICS AND ARTIFICIAL INTELLIGENCE AT THE WORKPLACE IN ENHANCING EMPLOYEE ENGAGEMENT MEDIATED BY EMPLOYEE TRUST AND AGE
  TPM – Testing, Psychometrics, Methodology in Applied Psychologyhttps://www.tpmap.org/article-view/?id=3572 2025 DOI: 10.5281/ZENODO.17863532
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• Beyond traditional analysis: Leveraging social media sentiments and market data for nifty50 returns forecasting
  2025
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• Machine Learning-assisted Investigation of Landslide Susceptibility for Aglar Watershed in the Lesser Himalaya Region
  Journal Of The Geological Society Of India 2025 DOI: 10.17491/jgsi/2025/174103
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• Applying a deep-learning surrogate model to simulate and compare achievable oil recovery by different waterflood scenarios
  Petroleum Science and Technology 2024 DOI: 10.1080/10916466.2023.2264902
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• PSO-tuned support vector classifier based Nifty50 index movement prediction using market positions and sentiment scores
  2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) 2023 DOI: 10.1109/ICCCNT56998.2023.10306670
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• Forecasting cumulative oil recovery from waterflood using a deep proxy model
  2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT) 2023 DOI: 10.1109/ICCCNT56998.2023.10307505
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