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About

Teo Imoto-Tar | 井本タール テオ

My research interests align with mathematics, computer science, and neuroscience! Specifically, data analysis and computer vision applied to biomedical imaging.

I am an undergraduate student at the University of California, San Diego, currently seeking research opportunities in a lab. I have a strong programming background, with experience developing startup backends using Firebase and AWS, working with microcontrollers for the Micromouse robotics competition, participating in hackathons and game jams (using Unity and Ren'Py), and building data analysis projects in notebook environments. Most recently, I have been leading an fMRI-to-image generation project as part of ECE 285, a graduate-level course, which I plan to submit to the UCSD Undergraduate Tech Conference.

In my free time, I love making music! I have produced commissioned beats and worked on soundtracks for game jams. I also deeply appreciate capybaras. >:)

timototar@ucsd.edu Resume

Projects

BRAID: Brain Representation to Artificial Image via Diffusion

A cross-modal fMRI-to-image reconstruction model that generates images from brain activity using a diffusion-based generative pipeline.

[code]
BRAID Project Visual

User Recommendation with FAISS and Firestore

Work in progress user and compliment recommendation system for Murmur Platforms Inc. Below is a demo of our approach.

[code]

Events

Coursework

ECE 285 - Deep Generative Models (Pengtao Xie)

Bayesian networks, VAEs, GANs, MCMC, EM algorithm, diffusion models.

MATH 173A - Optimization Methods (Lijun Ding)

Descent methods, Nesterov Acceleration, Newton's Method, Armijo backtracking line search, and convex optimization techniques.

[code]

COGS 108 - Data Science in Practice (Shannon Ellis)

Machine learning with Python: Decision Trees, SVMs, KNN, geospatial, NLP (TF-IDF), and statistical models (Mann-Whitney U, Bootstrap, KS).

[code]

BIPN 147 - Computational Neurosystems (Terrence Sejnowski)

Computational models of memory, motor control, and perception. Covered RL algorithms.

PHYS 241/141 - Computational Physics I (Hongbo Zhao)

Simulations and numerical modeling in Python/C++. Focused on N-body simulations.

Core CSE Courses

CSE11, CSE12 (Paul Cao), and CSE29 (Solares Edwin), plus seminars like CSE87 (Gary Cottrell) and BENG87.

Misc

Other Section Image
Music Itch Doodles