Harilal Remesan

Manage solar test field data using PostgreSQL-Timescale, InfluxDB, and other timeseries-optimized databases. Perform end-to-end analysis, from raw data processing to deploying interactive visualization tools (Grafana, Python, Plotly, Dash) for actionable insights. Optimize data pipelines for solar performance metrics. Develop ML models for time series forecasting of TANDEM, TOPCON, and PERC solar cells. (LSTM, TFT) Calculate key performance metrics like yield and deploy data-logging hardware in test fields.

-Collaborate with R&D, Chemistry, Production, Quality, and Customer Support teams to analyze and troubleshoot issues. -Develop cloud-deployable software for automating data analysis and reporting for electrolysers and production processes. -Build dashboards to uncover usage trends using Grafana, Python Dash, and Jupyter-Voila. -Develop ML models (LSTM, TFT) to predict electrolyser life, customer segmentation, and churn, applying statistical methods to analyze complex datasets.

-Led numerical simulations and mathematical modeling for dynamic engine systems and electric motors. - Automated internal workflows using Python, including NLP-based query detection and OCR for data extraction. -Developed AI solutions for autonomous driving, including object detection with YOLO. -Published technical papers and received multiple awards for contributions to numerical simulation and ML.