Mentor Areas
I am interested in the interface of AI and soft/living matter physics. Our collaborators have developed electronic circuits that learn how to perform AI tasks on their own, without a processor or external memory. We are interested in seeing how far we can push these systems, which are far more energy-efficient than artificial neural networks, using both experimental and computational approaches.
Right now I am particularly interested in developing and understanding contrastive local learning networks, which learn how to perform supervised learning tasks on their own, without a computer. Generally I am interested in collective phenomena in soft and living matter systems. More detailed can be found in my publication list, most easily accessed using Google Scholar.
Description:
Interested students should contact me to discuss possible projects. Exceptions for payment can be made for first generation, low income or under-represented minority students.
Preferred Qualifications
Interest in computer programming or laboratory research is required.
Details:
Preferred Student Year
First-year, Second-Year, Junior
Academic Term
Fall, Spring, Summer
I prefer to have students start during the above term(s).Volunteer
Yes
Yes indicates that faculty are open to volunteers.Paid
No
Yes indicates that faculty are open to paying students they engage in their research, regardless of their work-study eligibility.Work Study
Yes
Yes indicates that faculty are open to hiring work-study-eligible students.