kenish asmaniwala

Invited as an AI hacker to code in the Tech for Sustainability Hackathon of 4 days, organized by Siemens AI Lab to solve the challenges in the future electric grid systems. • Developed a proof of concept for start-up idea of Automated Load balancing system. Programmed all machine learning part of the concept. Developed load and electricity price forecasting model for Spain national grid. • Collaborated start-up idea won 2nd prize among 1800 start-up ideas worldwide, along with 3000 euros prize money.

Worked on Implementing machine learning in hydrogen policy development in Nordic and African countries. • Developed mid-term load and multiple energy forecasting models. • Predicted Residual load for 6 months. • Modelled the Electrolyser with the option to optimize its capacity. • Predicted possible hydrogen production and Levelized cost.

Participated at Europe’s one of the largest research centres and received the opportunity to work on German Household Load data analysis and forecasting comparison. • Developed the visual analytics tool for the German household Load Profile Generator. • Researched more than 25 literature-based visualizations, to effectively study and publish load profiles. • Developed a data pipeline to automize processes such as data import, wrangling, visualization and PDF report generation.

Worked in a start-up for 2 years, played a crucial role in bringing early-stage growth, by performing multiple value-additional tasks. • Designed different pressure vessels based on an IBR (Indian Boiler Regulations). Wrote new project proposals and trained new employees. Pitched project ideas and helped to bring new investors on board. • Helped to scale a startup 16 folds (from 3 employees to 50 employees) in a span of 2 years.

As a process engineer, Designed JES (Job Element sheet) of BIW, FCM and RTB parts of Ford Figo Aspire under guidance of process engineer Nidhi Gupta.

Data Wrangling, Data Visualization, Linear Regression, Logistic Regression, Decision Tree, Support Vector Machines, Random Forests, Feature Engineering & Model Selection, Clustering, Dimensionality Reduction, Artificial Neural networks, Recurrent Neural Networks.

Project Energy Systems (Exergoeconomic analysis), Solar Photovoltaics Technology, Wind Energy, Fuel-cell Technology, Power Electronics, Conversion of Renewable Energies, Integration of Renewable Energies, Sector Coupling (Power-to-X), Components of Energy Conversion, Energy Economics and Systems, Energy Storage and Conversion, Energy for Building, Science Writing, Environmental Management, Computer-Aided Modelling for Energy Systems, Innovation Management.