Summary
Motivated Senior student in Electrical Engineering with hands-on research
experience in neuromorphic AI systems and mixed signal electronic design.
Started original neuromorphic AI project in Nano Neurotechnology Lab as a freshman.
Previously led a project on decentralized neural recording arrays.
Education
Bachelor of Science in Electrical Engineering
- Minors: Computer Science, Mathematics
- Expected Graduation: May 2026
- GPA: 3.93
Research Experience
Leading original project translating biophysical findings into a novel neuromorphic AI model to create faster-learning and more computationally efficient AI.
Designed analog, transistor-level circuits for a novel implantable system of microchips for in vivo neural spike recording to gather large-scale neural data.
Technical Skills
Programming Languages
- Python: Proficient (PyTorch, Scikit-learn, NumPy, Matplotlib)
- C++: Proficient (Experience with CUDA for GPU acceleration of ML models)
- C: Intermediate (Microcontrollers and data structures)
Hardware & Neural Interfaces
- Circuit Design: Transistor-level analog circuit design for implantable neural recording systems
- Simulation Tools: Cadence Virtuoso, LTspice
Presentations and Awards
- 12/2024 Guest Lecturer for UIUC's CS591 course on Biologically Plausible AI |
post
- 10/2024 CERN Institute's Fast Machine Learning for Science conference: Contributed Talk &
Conference Proceedings
- 10/2024 Society For Neuroscience 2024: Poster Session
- 10/2024 Biomedical Engineering Society 2024: Annual Meeting Poster Session
- 04/2024 Purdue BME Symposium: 1st Place Oral Presentation
- 04/2024 Purdue Neuroscience and Physiology Seminar
- 06/2023 Purdue SURF Scholar: Highly selective, paid summer program for undergraduate researchers