de Sa lab - Department of Cognitive Science (Prof. Virginia de Sa)

• Designed novel pretraining framework for a Brain Computer Interface (BCI) on intracortical data.

• Built an LSTM based model to decode characters and predict transitions within temporal data from single-stroked handwriting data.

• Working on fine-tuning the end-to-end pipeline using BCI signals.

Kiyonaga lab - Department of Cognitive Science (Prof. Anastasia Kiyonaga)

• Developed a web-application using jsPsych and javascript to obtain user responses on word pair similarity.

• Investigated the role of distributional cues and embodied mechanisms in language comprehension for individuals with varying levels of visual and verbal imagery.

• Utilized LLM and GloVe embeddings and constructed nested regression models to analyze the contribution of sensorimotor distance and vivid visual imagery scores in predicting similarity between word pairs.

• Employed statistical techniques such as likelihood ratio tests (LRT) and Akaike Information Criterion (AIC) to quantify model performance and assess significance.

• [Summer Session II - 2023] CSE - 21: Mathematics for Algorithms and Systems Analysis (Prof. Oliver Braun). 30+ students

• [Fall 2023] CSE - 21: Mathematics for Algorithms and Systems Analysis (Prof. Russell Impagliazzo). 350+ students

• [Winter 2024] COGS 9 - Introduction to Data Science (Prof. Meenakshi Khosla) 300+ students

• [Spring 2024] COGS 18 - Introduction to Python (Prof. Shannon E. Ellis) 600+ students

My duties as a TA includes:

1) holding in-person office hours

2) conducting weekly discussion sessions

3) leading the instructional team

4) designing questions and solutions for the midterm and final examinations,

5) grading homework and exams

6) conducting on demand 1-on-1 meetings with students

7) leading programming lab

Shtrahman lab - Department of Neuroscience (Prof. Matthew Shtrahman)

• Working on developing computational tools for understanding neuronal circuit activity and the function of other biological networks.

• Investigating the hyper excitability, synchrony of neuronal activity in an epilepsy mouse model using calcium imaging data in the Dentate Gyrus and CA1 region of the brain.

• Conducting statistical analyses to distinguish neuron firing patterns associated with normal and epileptic brain activities, on both sparse and dense neural coded data. Employing statistical tests to discern correlations in neuron firing behavior.