Dr. Jitendra Kumar Meher
Cognizant Technology Solutions, Solarad AI, Jawaharlal Nehru University, JNU, Berhampur University, .Kreate
0000-0002-3815-6786
About
Dr. Jitendra Kumar Meher is a seasoned meteorologist turned industry level data scientist w/12+ yrs of experience (Inc. PhD), specializing in the field of air quality study, meteorology & renewable energy. He possesses expertise in utilizing various gaseous and particulate matter data, meteorological datasets & models (Such as GCMs, WRF, WRF-Chem, WRF-Solar, reanalysis & satellite products) to generate short to extended-range forecasts. His analytical approach incorporates adv. MLOps & AI techniques, including exploring the application of GenAI & AgenticAI for tasks such as documentation and model accuracy enhancement. Dr. Meher is proficient in different programming languages & data management tools (Inc. Python, R, Shell Scripting & SQL) & has practical experience with various clouds (Like GCP & AWS). His contributions are further substantiated by his authorship of multiple validation whitepapers documenting onground project outcomes. The list is here - https://scholar.google.co.in/citations?user=uaJlfpkAAAAJ&hl=en
Employment
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Cognizant Technology Solutions SDM - Senior Data Scientist2024 - Present
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Solarad AI Chief Climate Scientist2023 - 2024
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.Kreate Weather Scientist and Team Lead2019 - 2023
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Indian Institute of Technology Kanpur Post Doctoral Fellow2018 - 2019
Education
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Jawaharlal Nehru University, JNU M.Sc.2009 - 2011
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Berhampur University B.Sc.2006 - 2009
Projects & Funding
Projects & funding information is unavailable.
Publications (20)
- Climate Change Scenarios of India with Special Emphasis on Sundarbans Delta and Western Himalayan Region Save
- Probabilistic evaluation of three generations of climate models for simulating precipitation over the Western Himalayas Save
- Validating Meteosat Second Generation and Himawari-8 Derived Solar Irradiance against Ground Measurements: Solarad AI’s Approach Save
- CMIP5 based past and future climate change scenarios over South Bihar, India Save
- Is the Western Himalayan region vulnerable with respect to downscaled precipitation? Save
- Selection of suitable predictors and predictor domain for statistical downscaling over the Western Himalayan region of India Save
- Are GCMs and Crop Model Capable to Provide useful Information for Decision Making? Save
- Evaluation of different large-scale predictor-based statistical downscaling models in simulating zone-wise monsoon precipitation over India Save
- Gridded data as a source of missing data replacement in station records Save
- Skill of CMIP5 climate models to reproduce the stability indices in identifying thunderstorms over the Gangetic West Bengal Save