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Celine L

- Research Program Mentor

PhD candidate at Cornell University


natural language processing, machine learning, broadly engineering, audio processing, computational linguistics


Hi! My name is Celine, and I am a PhD candidate in computer science at Cornell University. I currently work on questions in natural language processing, especially how natural language processing techniques can make programming and software more accessible. My undergraduate degree background is in electrical engineering-- for my capstone project, I worked on selective audio filtering. Outside of the office, I like to spend my time being (1) active and (2) creative. (1) I play volleyball and frequent the gym and Ithaca's beautiful trails. (2) In my spare time, I pick up knitting, writing, embroidery projects, digital art doodles, and painters tape wall art.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Could language models experience synesthesia?

Synesthesia is the experience in which some people (synesthetes) experience certain unrelated sensory or cognitive stimulation when experiencing another one. (For example, seeing colors when listening to music.) Word embedding models such as Word2Vec and GloVe are trained over large corpora of language to assign similar high-dimensional value vectors (word embeddings) to similar words. (For example, "apple" and "peach" would have more similar word embeddings than would "apple" and "swimming".) The goal of this project would be to determine whether these trained word embedding models might possess common synesthetic associations such as the letter A to the color red. How might these association, if any, vary across word embedding models trained on different languages?

Coding skills

Python, MatLab, LabView, C, C++, Java, OCaml, Golang, OpenCL, LTSpice, Verilog, Arduino, Latex, Visual Basic

Teaching experience

In my undergraduate career at the University of Pennsylvania, I worked as a lab TA for two different courses: a freshman introduction to circuitry + Arduino and a sophomore introduction to circuit theory. As a lab TA, I attended to students during lab session and my own office hours to guide them through the concepts throughout the course and the final project. As a master's student at the University of Pennsylvania, I TA'd a graduate-level course on machine learning, for which I helped explain concepts during my office hours and mentored three teams through their respective final projects.


Work experience

Merly Inc. (2022 - Current)
Research Scientist & Software Engineer
Intel Labs (2021 - 2022)
Research Scientist Intern
University of Pennsylvania (2020 - 2021)
Research Assistant
VMware (2019 - 2019)
Product Development Intern


University of Pennsylvania (UPenn)
BSE Bachelor of Science in Engineering (2020)
Computer Science, Electrical Engineering
University of Pennsylvania (UPenn)
MSE Master of Science in Engineering (2020)
Embedded Systems
Cornell University
PhD Doctor of Philosophy candidate
Computer Science

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