News
- [08/2023] Started PhD in Vision Science at UC Berkeley
- [08/2023] Named CIVO Fellow by the UC Berkeley Center for Innovation in Vision and Optics
- [10/2022] Paper accepted at NeurIPS 2022, Medical Imaging Workshop
- [05/2022] Received UC Berkeley EECS B.S. degree
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A Machine Learning Approach to Predicting Dry Eye-Related Signs, Symptoms and Diagnoses from Meibography Images
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Meng C. Lin,
Peter Wang,
Tejasvi Kothapalli,
Andrew D. Graham,
Stella X. Yu
American Academy of Optometry (AAOPT) Annual Meeting, 2022 (Oral Presentation)
abstract /
slides /
press (Healio)
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Meng C. Lin,
Andrew D. Graham,
Tejasvi Kothapalli,
Peter Wang,
Jennifer Ding,
Vivien Tse,
Stella X. Yu
Association for Research in Vision and Ophthalmology (ARVO) Annual Meeting, 2023
abstract
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Andrew D. Graham,
Tejasvi Kothapalli,
Peter Wang,
Jennifer Ding,
Vivien Tse,
Penny A. Asbell,
Stella X. Yu,
Meng C. Lin
Heliyon, 202
paper
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Andrew D. Graham,
Peter Wang,
Tejasvi Kothapalli,
Helen Tasho,
Alisa Molina,
Vivien Tse,
Sarah M. Chang,
Stella X. Yu,
Meng C. Lin
Nature Scientific Reports, 2025
paper
We propose a machine learning approach that predicts dry eye related signs, symptoms and diagnoses from subject data.
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Tracking the Dynamics of the Tear Film Lipid Layer
Tejasvi Kothapalli, Charlie Shou, Jennifer Ding,
Peter Wang,
Andrew D. Graham,
Tatyana Svitova,
Stella X. Yu, Meng C. Lin
NeurIPS Workshop, 2022
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paper /
poster /
slides /
arXiv
We use computer vision to track the tear film lipid layer spread.
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Senior Honors Thesis: Studying Dry Eye Syndrome with Machine Learning
Tejasvi Kothapalli
Senior Honors Thesis, 2022
thesis
Studied Dry Eye Disease diagnosis with machine learning in two regimes: (1) patient tabular data and (2) ocular surface recordings.
Advised by Prof. Stella Yu and
Prof. Meng Lin. Earned an A+ :). Also, huge thanks to Peter Wang for all
the mentorship and guidance.
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Saving Energy in Homes Using Wi-Fi Device Usage Patterns
Tejasvi Kothapalli
International Journal of Energy Optimization and Engineering (IJEOE), 2018
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publication site
In order to reduce energy wastage in homes, this work detects the presence of residents through Wi-Fi device usage
and tries to automatically turn off unused electronic appliances.
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Controlling Tensegrity Robots through Evolution using Friction based Actuation
Tejasvi Kothapalli, Adrian Agogino
NASA Technical Reports, 2017
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publication site
This study investigates a control pattern for successful locomotion in tensegrity robots through an evolutionary algorithm.
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