Teaching & mentoring
I teach computational thinking through hands-on projects and mentor emerging researchers as they connect neuroscience questions with rigorous analytical methods.
Formal teaching
Experience ranges from focused graduate seminars to coordinating teaching teams for large undergraduate courses.
Evaluated coursework and supported project discussions for a specialized class in neural signal analysis.
Co-developed the curriculum, delivered lectures, and mentored course projects.
Coordinated 27 teaching assistants for a class of approximately 200 students, conducted labs, and supported assessment.
Prepared assignments and tutorials, conducted vivas and labs, evaluated work, and mentored student projects.
Delivered lectures, designed assignments, mentored projects, and evaluated student work.
Recent mentorship
Selected projects from an extensive mentoring record spanning undergraduate, master's, PhD, and medical trainees.
Mentoring projects on spindle source localization, olfactory targeted memory reactivation, self-supervised sleep decoding, and EEG features in long-term cancer survivors.
Recent mentees: Prajvala Mysore, Klara Viktoria Szilagyi, Pratheek Eranki, Samundhra Nepal, and Sanjana Mahale.
Mentoring region-aware reconstruction and foundational-model approaches for resting-state fMRI signal decoding.
Recent mentee: Ruthwik Reddy.
Guiding computational modeling of transcranial focused ultrasound for chronic pain and pediatric sickle cell disease.
Recent mentees: Dylan Aubel and Kevin Prince.
Previous mentorship has covered music cognition, cross-subject EEG representations, stimulus-response correlation, meditation, and self-supervised seizure detection.
Former mentees have progressed to doctoral training and research-focused industry roles.
Mentoring approach
I help trainees define a tractable scientific question, understand the signal and literature, build a reproducible analysis, and communicate what the evidence supports.
Discuss mentoring or teaching