👨‍🔬 About me

🔭 I'm a Data Scientist working on SaaS platform, fault detection, ML models and digital twin of utility-scale solar plants.
👨‍🔬 My PhD research is on investigating structure-property relationships of organic semiconductors and predicting power conversion efficiency of organic solar cells.
🌱 I’m currently learning MLOps.
👯 I’m looking to collaborate on ML models for Solar Energy related projects (Utility-scale / Organic Solar Cells)
💬 Ask me about Solar Energy & Machine Learning.

💼 Work Experience

👨‍💻 Solar Analyst @ Futr Energy (June 2022 - November 2023)

Solar plant MPPT/SMB/String level fault detection and revenue loss calculation pipeline: Plant generation is examined on MPPT/SMB/String level to find anomaly type, downtime, and revenue loss due to individual anomaly.
Solar plant monitoring parameters calculation for dashboard and data analytics: All photovoltaic parameters required for solar plant monitoring, maintenance, and troubleshooting. Creating new interactive yearly graphs for individual inverters and complete plant generation.
Fault detection using thermal images (infrared images): YOLOV7 model is created to detect various solar panel faults using infrared images (thermal images) of solar plant captured using drone
Automating solar plant twin generation: Twin is created using tif and shp files. With following data using osgeo python library for geoanalytics, ai model is made.

👨‍🎓 Senior Research Fellow (SRF), Pursuing PhD @ LNMIIT (Feb 2018 - June 2022)

Prediction of photovoltaic properties in Organic Solar Cells: Machine Learning, Deep Learning, and Active Learning models to predict photovoltaic parameters in Organic Solar Cells and drawing meaningful insights.
Organic Solar Cell Fabrication and characterization: Organic solar cell fabrication. Characterization using Keithley-2450 SourceMeter, UV-Vis Spectrophotometer, Spectrofluorometer, Cyclic Voltammetry(CV), External Quantum Efficiency(for calculation of Integrated Jsc and Voltage Loss Analysis).

Prateek Malhotra, Subhayan Biswas, and Ganesh D. Sharma. “Directed Message Passing Neural Network for Predicting Power Conversion Efficiency in Organic Solar Cells.” ACS Applied Materials & Interfaces (2023).$|$ PDF
Prateek Malhotra, Juan C. Verduzco, Subhayan Biswas, and Ganesh D. Sharma. “Active Discovery of Donor: Acceptor Combinations For Efficient Organic Solar Cells.” ACS Applied Materials & Interfaces 14, no. 49 (2022): 54895-54906.$|$ PDF
Prateek Malhotra, Kanupriya Khandelwal, Subhayan Biswas, Fang-Chung Chen, and Ganesh D. Sharma. “Opportunities and challenges for machine learning to select combination of donor and acceptor materials for efficient organic solar cells.” Journal of Materials Chemistry C 10, no. 47 (2022): 17781-17811.$|$ PDF
Prateek Malhotra, Subhayan Biswas, Fang-Chung Chen, and Ganesh D. Sharma. “Prediction of non-radiative voltage losses in organic solar cells using machine learning.” Solar Energy 228 (2021): 175-186.$|$ PDF

Calculating Jsc from EQE This application calculates Jsc(Short Circuit Current Density) from EQE(External Quantum Efficiency) curve. Link
Calculating solar cell parameters from IV curve This application calculates all solar cell parameters: Jsc,Voc, FF, Pm, Rs, Rsh, and PCE. Link
Calculating rooftop plant capacity This application takes input as load (multiple equipments), their corresponding quantity and operational hours. Link
Solar DC Pump Design This application designs Solar DC Pump system using water drawn/day, variables ‘elevation’ and ‘peak sunshine hours’ as input. Link