Principal Investigator (Assistant Professor)
Ankit is broadly interested in the intersection between machine learning and computational neuroscience. He works with neuroscientists to build a bridge between artificial and real neuronal networks, using theories and experiments with artificial nets to understand and make testable predictions about real brain circuits. Ankit returned to academia after spending 6 years in industry, building real-time inference systems trained on large-scale data for ballistic missile defense (MIT Lincoln Laboratory), and high-frequency trading. He received his graduate and undergraduate degrees in Computer Science and Applied Mathematics from Harvard University, and completed a postdoctoral training at Rice University with Richard G. Baraniuk.
Josue Ortega Caro
Josue is a Computational Biology Ph.D. studying the role of non-cortical areas in visual processing using neural-inspired deep learning and spiking neural networks. In addition, I study how do different deep learning architectures might benefit from neural principles.
Second-year Ph.D. student at Rice University and previously MS at Ecole Normale Superieure in Applied Mathematics and MS at KU Leuven in Artificial Intelligence, my research is now focusing on time-frequency representations, more especially on wavelet logons applied to medical data and on learning how to optimize via reinforcement learning framework.
Robert Theron Brockman II
I am a third year Neuroscience PhD student at Baylor College of Medicine. My primary research interest is understanding how the brain provides human consciousness with perceptual features. I am especially interested in how the brain generates subjective human color experiences.
M.S. Applied Mathematics, Rice University; B.S. Applied Mathematics, Sichuan University. My previous research is about computer graphics and geometric modeling. I am now researching on the interpretability and explainability of deep neural networks.
M.S. Electrical Engineering, Southeast University; B.S. Electronics and Information Engineering, Huazhong University of Science and Technology. My research interests lie in interpretability and explainability of deep learning, and generative models such as generative adversarial networks
Wanjia (Robin) Liu
My name is Robin and I’m a second year CS PhD student. My research is focused on building retinomorphic models inspired by biological retina on a functional level. We adapt retinomorphic signals in deep learning video tasks such as action recognition and reinforcement learning.
Undergraduate Students and Alumnus
Hi! I’m Ameesh, and I’m a junior undergrad at Rice studying Computer Science. I’ve most recently worked on the LSTM Probing project in lab, where I helped theorize the underlying structure of how an LSTM learns written languages.
While working in Dr. Patel’s lab, I worked on translating the locust LGMD neuron model into an RNN framework in TensorFlow. I graduated Rice in 2017 with a BA in Statistics and now work at Buoy Health, a health tech startup, on the machine learning side of understanding and improving on our ability to figure out what is causing a patient’s symptoms.
I’m an undergraduate intern currently researching with Professor Aaron Courville on Visual Reasoning. I’m in the final year of my Bachelor’s in Computer Science at Rice University. In the past, I’ve contributed towards state-of-the-art semi-supervised deep learning models, worked to improve indoor location accuracy algorithms for Google Maps, and built fraud detection models for Uber. My current research interests lie in Deep Learning, Reinforcement Learning, and Reasoning. Check out my website for more info about me if you’re interested!
Raymond graduated Rice in 2017 with a B.A. in Computer Science. He spent the first 8 months researching here working to build a software package around ODE-based Recurrent Networks. His technical passions include Vision, NLP, Codebase Sustainability, and avoiding the mouse in any way possible. he currently works as a Backend Engineer at Plaid Technologies and is planning to attend Graduate School starting 2019. Outside of technology, Raymond enjoys basketball among other sports and makes music.