hi, i'm seema

cogsci student & signal processing researcher

what i do

I'm interested in tools that bridge technology and the human experience, especially the ones that help us quantify things that usually feel impossible to measure. That's what drew me to neurotech and wearables.

Right now I'm at the Chiba Lab, building systems that capture classroom environments through multimodal biosensor data.

outside the lab

When I'm not at the lab, I'm playing piano, going on a run, thrifting, or making yet another Spotify playlist. Here's my most recent one:

Mitski
this is mitski
playlist

let's connect

Always happy to chat about research, neurotech, music, or anything in between.

about me

cognitive science & computer science at uc san diego

Seema

I'm a senior at UCSD studying Cognitive Science (Machine Learning and Neural Computation) with a CS minor. At the Chiba Lab, I work on building and deploying multimodal biosensor systems to study how the autonomic nervous system shapes children's behavior and learning. Learning about the brain and body has also become a personal journey. Understanding how my own brain works is part of what pulls me toward neurotech, wearables, and the tools that make the invisible measurable. That interest runs deep into signal processing too: good research depends on clean, accurate data, and I find a lot of meaning in the work of making noisy physiological signals actually usable.

experience

UCSD
Undergrad Researcher
Chiba Lab · UCSD
UC Scholar
UC Scholar
Undergraduate Research Hub
Abwaab
Data Science Intern
Abwaab
IRA
Robotics Instructor
International Robotics Academy

skills

PythonSignal ProcessingMachine LearningBiosensorsC++JavaEmbedded SystemsGit/GitHubExperimental DesignBCIsLSL

leadership

Co-President · Tritons Prosthetic Society
May 2025 – present
Teaching Assistant · Neural Signal Processing (COGS 118C)
Jan 2026 – present
Peer Mentor · Cognitive Science Student Association
Nov 2022 – present
view resume →

work

research, class projects, and things i built for fun

Optical Illusions in CLIP
Analyzed how CLIP encodes perceptual ambiguity using the rabbit-duck illusion, designed systematic image perturbations to evaluate model bias, and compared outputs against human perception data.
Computer VisionMachine LearningPerceptual AI
Biosignal Processing Pipeline
Developed a Python pipeline for cleaning and extracting physiological features from noisy wearable data, including motion artifact removal and PPG/EDA filtering for HR and HRV extraction.
Signal ProcessingWearablesData Engineering
EEG-based Attention Classification
Designed an EEG-based attention classification pipeline for an adaptive neurofeedback system using real-time OpenBCI data, signal preprocessing, and frequency-domain analysis.
NeuroscienceSignal ProcessingBCI
Sarcastic Headline Generator
Explored whether character-level RNNs can learn sarcasm using The Onion dataset with RNN, LSTM, and GRU architectures.
NLPDeep LearningRNN / LSTM
Zebrafish Multiscale Dynamics Analysis
Translated mathematical formulations from a neuroscience paper into a working implementation of the Iterative Coarse Graining (ICG) algorithm.
PythonMultiscale AnalysisComputational Neuroscience