MINT group

I lead the the Machine Intelligence (MINT) group where I am fortunate to work with an amazing set of students and collaborators. We work on foundational topics relating to machine learning under limited supervision and sequential decision making, and ground our research in applications at the intersection of physical sciences and climate change.

Ph.D.

• Tung Nguyen
• Hritik Bansal (co-advised with Kai-Wei Chang)
• Siyan Zhao
• Daniel Israel (co-advised with Guy Van den Broeck)
• Shufan Li

Masters and Undergraduates

• John Dang
• Seongbin Park

Alumni

• Sudhanshu Agarwal (Qualcomm AI Research)
• Meihua Dang [primary advisor: Guy Van den Broeck] (PhD student at Stanford)
• Jason Jewik (Box)
• Siddarth Krishnamoorthy (AlphaGrep)
• Satvik Mashkaria (Tower Research)
• Shashank Goel (Tower Research)
• Baiting Zhu (Masters student at Stanford)

Prospective Interns and Students

Thank you for your interest in joining my group. Please read the following information before applying:

• Interns: I host a few interns during the summer quarter every year (typically remote due to pandemic restrictions). Students should have completed prior coursework in machine learning and deep learning, have experience with machine learning libraries (e.g., PyTorch), and have read at least 2 of my recent papers. If you are interested, please email me your CV and the above information.

• Undergraduate and Graduate Students: Due to the huge volume of mail, I will not be able to reply to individual mails from prospective students outside UCLA. I regularly take on students in my group at all levels. If you are interested, please apply directly to the appropriate program at UCLA and email me after you are admitted for available opportunities. Before emailing me, note that UCLA students should have completed prior coursework in machine learning and deep learning, have experience with machine learning libraries (e.g., PyTorch), and have read at least 2 of my recent papers.