Researching with Dr. Hava Siegelmann (BINDS lab)

CICS 210: Data Structures (Fall 2023), COMPSCI 348: Principles of Data Science (Spring 2024), INFO 248: Introduction to Data Science (Summer 2024)

I was selected to join an REU program with Professor Alex Iosevich through the Georgen Institute for Data Science (GIDS) and sponsored by the National Science Foundation (NSF). I created my own project under Professor Iosevich’s approval where I independently analyzed prior multi-task learning literature, built my own project proposal, and found resources I could utilize to carry out experiments (RLlib). I led a team of students and guided the focus of our project throughout the program. We investigated a new mathematical framework for multi-task learning and multi-task deep reinforcement learning. This framework involves building a shared model plus task-specific models that when used together as a joint model perform effectively on each task. This framework can be utilized with any parameterized model (e.g. Linear Regression, Neural Networks) to perform any number of tasks and leverage information from one or more tasks to perform better on another.

I conducted multiple research projects under the supervision of Professor Ralf Haefner, predominantly employing machine learning to analyze neural data. In my main project, I investigated what architectures or features of an artificial neural network could mirror brain-like neural variability. Another project I had was tracking individual neurons over time in electrodes planted in a macaque visual cortex. Using response properties, waveform properties, and location, I built a generative model that measures similarity between neurons over time and space.

I worked as a TA under Professor Cantay Caliskan for Introduction to Statistical Machine Learning (DSCC265). My responsibilities included leading a twice-weekly office hours, grading exams and assignments.

I worked as a teaching assistant in Computational Introduction to Statistics (DSCC262). My responsibilities included leading a weekly workshop, grading exams and assignments, and proctoring exams.