Junseok (June) Oh

Hi! I'm Junseok, pursuing an MSE in Data Science at the University of Pennsylvania. My goal is to develop human-centric social robots that support caregivers and patients through multimodal interaction.

I study multimodal social attention: how an agent can infer who needs attention, what matters in the moment, and when assistance is appropriate from cues like gaze, head orientation, language, and turn-taking. At the MIT Media Lab Personal Robots Group (mentored by Dong Won Lee and Dr. Hae Won Park), I work on multimodal egocentric head-gaze prediction. Previously, I worked on health-focused projects spanning smartphone-based biosensing and single-cell analysis. I also have industry experience at Hewlett Packard Enterprise (HPE), where I worked full-time as a Cloud AI Software Engineer and previously interned in Data Science.

I earned my B.S. in Computer Science from Purdue University, with a minor in Mathematics.

Email  /  CV  /  Scholar  /  GitHub

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Research
Egocentric head gaze prediction overview Social Egocentric Head Gaze Prediction with Vision Embeddings Fused with Speaker Audio Language
Junseok Oh*, Dong Won Lee*, Louis-Philippe Morency, Cynthia Breazeal, Hae Won Park
In Preparation
project page

We study social egocentric head-gaze prediction by fusing vision embeddings with speaker-aware audio and language cues.

Smartphone-integrated Salmonella detection platform Smartphone-Integrated Optomechanical Dual-Mode Instrument for Salmonella Typhimurium Detection
Hyun Jung Min, Hansel A. Mina, Junseok Oh, Amanda J. Deering, J. Paul Robinson, Bartek Rajwa, Euiwon Bae
IEEE Sensors Journal, 2025
paper

We develop a smartphone-integrated, optomechanical dual-mode biosensing instrument that combines vision-based readout with frequency-shift measurements to enable low-cost, rapid detection of Salmonella Typhimurium for practical food-safety monitoring.

Research Projects
Stanford Cardiovascular Institute scRNA-seq

K-BioX - Stanford Cardiovascular Institute
Jan 2022 – Aug 2022 and Jan 2024 – May 2024
Advisors: Dr. Siyeon Rhee and Prof. Joseph C. Wu

Built an automated scRNA-seq pipeline over public GEO datasets to compare adult vs. P12 developmental stages, then used GSEA, cell-to-cell interaction profiling, and PCA/UMAP to surface adipogenesis/angiogenesis signals across epicardial adipose tissue (EAT) datasets.

Wittgen Biotechnology, UC Berkeley SkyDeck

Wittgen Biotechnology - UC Berkeley SkyDeck
May 2022 – Aug 2022
Research Intern

Worked on ML for high-resolution tumor classification and tailored drug recommendations by processing RNA-seq data from 40+ cancer patients, contributing to an AI platform for cancer heterogeneity profiling, and using Seurat for single-cell analysis and cell-type differentiation.

Teaching
Purdue Computer Science CS 25200 - Systems Programming
Undergraduate TA, Spring 2023

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