UROP: Machine learning modeling to optimize bioenergy production

Term: Spring 2023
UROP Department, Lab or Center: MIT D-Lab
Faculty Supervisor: Dr. Daniel Sweeney
Direct Supervisor: Dr. Priyabrata Pradhan
Compensation: UROP direct funding available if applicant accepted by February 14. Otherwise, credit or on volunteer basis.

About MIT D-Lab

D-Lab works largely on health, water, energy, and agriculture to achieve sustainable development goals through collaborative approaches. We have a long history of working with collaborators around the world to design and develop energy solutions for low-resource communities. D-Lab also offers dynamic, project-based energy classes during both semesters. More details on D-Lab research are available here.

Project overview

Over the last 20 years, D-Lab has been working with communities to provide improved cooking solutions and solid fuel use. In the past, D-Lab has been part of the Charcoal Project in order to bring together charcoal producers and provide them with more support. Currently, we are working to evaluating existing methods and multiple factors to better understand biochar production and share our finding with communities. To circumvent the costs and time associated with experimental approaches, machine learning techniques can be used to evaluate factors in the biochar production process. We are looking a motivated student to extract and analyze literature data, code, analyze results, and propose an experimental matrix.

Key research questions

  • What factors contribute to high quality biochar production and their importance?
  • Can ML modeling be used to design an experimental matrix based on findings?


Applicants should have an interest in machine learning modeling, python programming and bioenergy. Students with any engineering background are welcome.


Interested candidates should email Priyabrata Pradhan with a resume and brief explanation of why they are interested in this project.


Priyabrata Pradhan, MIT D-Lab Fulbright Postdoctoral Researcher