Potential New PhD Students

Our lab works at the forefront of deep learning on problems central to artificial general intelligence (AGI), including efficient continual and lifelong learning, bias-robust neural networks, self-supervised learning, and multimodal large language models. Much of our work is inspired by cognitive science.

Admission, Funding and Expectations

As a full-time PhD student in my lab, you will receive a full-tuition scholarship and a stipend, both guaranteed for five years. Unless you are funded by a fellowship (e.g., NSF GRFP), positions in my group are funded by research grants, so funding is often the limiting factor in how many students I can admit. If you are a US citizen, you may be eligible for university fellowships beyond the funding in my lab.

Competitive applicants have strong programming skills in Python and PyTorch/Jax, significant deep learning experience, and a solid foundation in linear algebra and calculus. I am especially interested in recruiting students with an interest and background in neuroscience, cognitive science, physics, mathematics, and related fields.

How to apply to work in my lab

If you would like to work in my lab, you must clearly state this in your statement of purpose. Your statement should describe why you want a PhD, your career objectives, your past research experiences, how your training has prepared you for deep learning research, and, at a high level, the areas you hope to work on. Much of the work in my group is brain-inspired, so familiarity with neuroscience or a serious willingness to learn it is important for many projects.

Applications are evaluated primarily on research ability and deep learning expertise, especially as demonstrated by papers in respected journals and/or AI venues (for example CVPR, NeurIPS, ICLR, ICML). We use PyTorch in my lab. Strong alignment with our research on continual learning and related topics is essential, as are clear communication skills and persistence on difficult problems.

You should demonstrate familiarity with my recent work where I am the senior (last) author. You can find some recent preprints here:
https://arxiv.org/search/?query=kanan+harun&searchtype=all&source=header.
Experience in AI industry roles or success in AI competitions (for example, Kaggle) is a plus. Your letters of recommendation should provide concrete evidence of your research and technical skills.

Apply here for Fall admission.

Reaching out

Applicants who already hold major external fellowships (for example NSF GRFP) should email me about potential openings in the lab, since such fellowships can substantially increase the number of students I am able to admit. In most years there are only 0-2 available slots in my group, and these are almost always constrained by grant funding and research alignment.

If you have published papers in continual learning or related areas, or in premier venues such as TPAMI, Nature, CVPR, ICCV, NeurIPS, ICLR, ACL, AAAI, ICML, or NAACL, you may also email me with a brief note that explains your interests and includes your CV and links to your papers.

Because of the high volume of inquiries and strict funding limits, I am only able to respond to emails from prospective students who either (1) already hold a major external fellowship or (2) have a strong publication record in research areas closely aligned with my lab, especially as demonstrated by papers in premier AI venues. If you do not meet one of these criteria, I will not be able to reply to your email, as I often receive 20+ inquiries daily from people who presumably didn’t read this message.