Janak A.

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Profile:

Janak is a seasoned data scientist and engineer with a strong background in machine learning, data science, and software engineering. With a rich academic history from the Massachusetts Institute of Technology (MIT), Janak has applied his expertise in various industries, including energy, finance, and climate technology. As the founder of Adapt, Janak is focused on leveraging AI and data science to drive impactful solutions in the energy sector. His diverse experience, combined with his deep understanding of machine learning and AI, positions him as an insightful mentor for aspiring engineers and data scientists.
Machine Learning
Data Science
Software Engineering
Energy and Climate Technology

Academic Background:

Master of Engineering in Electrical Engineering and Computer Science, Massachusetts Institute of Technology (MIT)

  • Graduated with a perfect GPA of 5.0/5.0.
  • Focused on optimizing power systems with AI and data science techniques.

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Bachelor of Science in Electrical Engineering and Computer Science, MIT

  • Completed with a focus on software development, machine learning, and energy systems.
  • Active in various student organizations, including leadership roles in the MIT

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Bachelor of Science in Computer Science, Indian Institute of Technology, Bombay

  • Focused on software engineering and machine learning applications.
  • Engaged in extracurricular activities, including swimming.

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Professional Experience:

Founder @ Adapt

  • Leading a team focused on developing AI-driven solutions for climate change and energy management.
  • Innovating in the energy sector by applying data science and machine learning to solve complex environmental challenges

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Senior Data Scientist @ AutoGrid

  • Developed machine learning models to optimize energy distribution and demand forecasting.
  • Played a key role in the acquisition of AutoGrid by Schneider Electric by demonstrating the value of AI in energy management.

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Software and ML Engineer @ Shell

  • Built analytical tools in Python to predict commercial fuel prices, leveraging large datasets and machine learning models.
  • Developed and deployed a custom UI for use by Shell’s sales representatives, enhancing the efficiency of fuel pricing strategies.

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