Ariel K. Feldman

About Me.

I am a PhD Candidate in Neural Computation at Carnegie Mellon University interested in using electrophysiology and information theory to explore the neural circuitry underlying how we represent our environment and ourselves within it. Currently, I'm jointly advised by Dr. Pulkit Grover and Dr. Doug Weber. During my undergraduate education, I was lucky enough to work under the supervision of Dr. Caleb Kemere in the Realtime Neural Engineering Lab (RNEL) at Rice University. To read more about my research, both past and present, head over to my research page or check out the videos below!
Believe it or not, I like to do other things outside of research. Lil REL grew up with a ranch in Montana, and so I'm a big fan of being outside (even in those dreaded Houston summers). I practiced Taekwondo very seriously, to the point where I had several national and international titles by high school, but switched to teaching after a swivel chair shattered my Olympic dreams. Languages fascinate me, and I'm always looking to practice what I know or learn something new. A few more interests of note include salsa dancing, rodeo riding and pie eating, in no particular order...
Labs Worked With
Oral Presentations
Conference Posters
Classes TA'd



During my undergraduate career, I have found enjoyment in the intersection of the fields of engineering and neuroscience, the former of which I’d had little to no exposure to until coming to Rice. However, I have become deeply interested in how an engineering background enables me to further probe and interact with the brain, ultimately allowing for more innovative methods of decoding neural activity. In the Kemere Lab, I was working to understand the role of the hippocampus in both spatial navigation (see RELevator) and learning/memory (check out Shark-Wave). In my graduate and post-graduate careers, however, I would like to move more towards working on decoding the underlying neural activity of memory and consciousness, ideally to the point of understanding where replication through computer simulations becomes feasible.


When I got to Rice University, I realized I had nothing figured out. Classes were hard, I had no clue what my career path would look like — the impact my mentors and TAs had on me were incredibly powerful in those early years. I strive to help students navigating their early years of research or a new academic field, and come to love the field as I do.

My experience is as follows :

Course Development

Course Development

Rice Center for Engineering Leadership's IOT with Machine Learning & Python

Teaching high school students how to utilize realtime sensor data, along with the immense data available online, to create predicitive unsupervised machine learning algorithms and utilizing JSON/HTTP.

Academic Fellow

Academic Fellow

Computer Science, Neuroscience, Research & Writing

Academic Fellowships at Rice University aim to identify students who perform exceptionally in a certain course, major or field that may be able to provide free, on-call academic aid to students who reside in their residential colleges.

Teaching Assistant

Teaching Assistant


Teaching assistants are selected by professors on the basis of past class performance, understanding of material and willingness to help others via grading and weekly office hours, as well as exam review sessions. This is more specific than a Fellow.



Elisabeth Torres-Schulte Eugene Kim Lily Xie

As a newbie in academia, I needed a lot of help getting on my feet and figuring out how the system works. I try and pass that knowledge onto my undergrads, check them out here to see some awesome future neuroscientists!


Below, I have included some notes and course resources I've put together for classes I have TA'd and Fellowed for at Rice University.


Office hours, research help, pie appointments — you name it. Shoot me a message: