Education
- University of California, Davis (2018-Present)
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- PhD Student - Electrical and Computer Engineering
- Course Highlights:
- Engineering: Linear Signals and Systems, Random Signals and Noise, Reinforcement Learning, Digital Signal Processing, Optimal and Adaptive Filtering, Neural Control Systems.
- Olin College of Engineering (2012-2016)
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- B.S. Electrical and Computer Engineering (2016)
- Course Highlights:
- Engineering: Controls, Elecanisms, Analog and Digital Communications, Power Supply Design, High Voltage Electronics, Microelectronic Circuits, MADVLSI
- Design: Design Nature, User-Oriented Collaborative Design, Sustainable Design
Research
- Deep Learning for Channel State Information Estimation in Massive MIMO Networks
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- Using convolutional, recurrent neural networks for estimating downlink CSI in simulated massive MIMO networks.
- Presented at UCDavis ECExpo (Video, slides)
- Fading Channel Characterization via Generative Adversarial Networks
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- Using variational GANs to generate approximate non-additive wireless communications channel.
- Google Colab
Teaching
- Head Teaching Assistant: EEC 160 Analog and Digital Communications (Fall 2019)
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- Wrote solutions for 8 writtten homework assignments and 5 MATLAB-based computer assignments based on problems from Modern Digital and Analog Communication.
- Hosted bi-weekly office hours answering conceptual questions about signal analysis and analog/digital modulation.
- Teaching Assistant: Internet of Things (Summer 2019)
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- Helped design and run a summer course teaching high school students embedded programming for IoT devices.
- Read about it here!
- Private Tutor (01/2019 to 05/2019)
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- Taught concepts from signal processing, control theory, and digital systems to help client pass Fundamentals of Engineering Exam for Electrical and Computer Engineering.
- Teaching Assistant: EEC 157A Control Systems (Fall 2018)
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- Conducted lab sessions to assist students in implementing linear system analysis and compensation techniques in MATLAB and with debugging robotic system learning kits (RSLKs).
Professional Experience
Projects
Graduate
CUDA-based Batcher-Banyan Network
Implemented GPU program that performs bitonic sort via a sorting network. Project presentation here. Project report here. Github here.
Maximum Mutual Information Design for MIMO Systems: Paper Review
Replication of results from " Maximum Mutual Information Design for MIMO Systems With Imperfect Channel Knowledge". Project report here. Github here.
Stochastic Gradient Descent: An Overview
Term paper summarizing stochastic gradient descent in the context of machine learning. See paper here.
Recovering Temporal Dynamics via GPFA
Using Gaussian Process Factor Analysis (GPFA) to estimate behavioral dynamics of animal based on neuronal population data. Final presentation here Github here.
LPC Vocoder
Implemented a vocal synthesizer using linear predictive coding. Github here. Demo here.
Reinforcement Learning and Resource Allocation
Applied multi-armed bandit framework to problem of resource allocation in simple wireless communications network. Github here.
Undergraduate
Harley-Davidson SCOPE
Acted as liaison between Olin student team and Harley-Davidson engineers. Project archival poster here. More info here.
Rice and Sustainability
Collaborated with other students to evaluate the experience of cooking rice, the environmental impact associated with cooking rice, and an alternative design with less impact.
Space Origin: X
Programmed kinematic rocket model of falling rocket in embedded C. Designed website. Project site here.
Analog Levitation
Designed and built analog circuit which utilized light-based feedback to suspend a metal ball in mid-air. Demo video here.
Design for Blacksmiths
Studied blacksmiths, identified their pain-points, and developed a concept for a thermally-insulated smart glove, removing the need for tongs.