🎓 MS in Data Science @ Texas A&M University-Corpus Christi
🎓 B.S. in Food Science & Biotechnology @ SKKU Sungkyunkwan University
🔬 Former research intern @ Samsung Medical Center (Epidemiology & Clinical Data)
📊 Passionate about data-driven research, machine learning, and financial time series forecasting
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Awarded the SKKU President Award for a methane-reducing functional gum project (₩2M prize, graduation evaluation waived)
🔗 View SKKU article (English) -
Presented stock forecasting research at Coastal Bend Conference (2025) and NMSU Workshop (2025)
🔗 View LinkedIn post
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(2024.09–Present) Research Assistant @ Prof.Sreelekha Guggilam's Lab (TAMUCC) ▸ Conducting thesis research under Prof. Sreelekha Kadam at the intersection of financial time series modeling and social sentiment analysis
▸ Designing a Reddit sentiment-enhanced forecasting model combining custom VADER-based lexicons with multivariate transformer-based models ▸ Fine-tuning large foundation models using stock price data and implementing scalable inference pipelines for real-time market prediction -
(2022.08–2023.08) Clinical Data Research Assistant @ Samsung Medical Center – CCE (Clinical Center for Epidemiology) ▸ Supported data collection and analysis for clinical epidemiological studies under Prof. Juhee Cho (SAHIST / Johns Hopkins), Prof. Danbee Kang (SAHIST) ▸ Worked on structured health datasets related to rare and oncological diseases(cancer) ▸ Managed and cleaned clinical datasets and assisted in data coordination(protocols, data workflows)for epidemiology research
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(2022.03–2022.07) Research Assistant @ Prof. Jinhee Heo’s Lab (SKKU) ▸ Conducted scientific literature review and basic data handling for lab-scale experiments under Prof. Jinhee Hur (Ph.D. from Johns Hopkins, Postdoctoral Fellow at Harvard) ▸ Gained foundational experience in academic research and interdisciplinary collaboration
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Stock Forecasting using Transformer
Implemented Google TimesFM, Amazon Chronos, and ARIMA models for Tesla stock prediction using time-series data(PyTorch) -
Bayesian Cost Prediction in Healthcare
Compared Bayesian and Frequentist linear regression models on individual medical cost prediction (usingrethinkingpackage in R). Focused on uncertainty quantification and interpretability. -
[Ongoing] Reddit Sentiment–Enhanced Stock Forecasting
Multivariate forecasting with Reddit-based sentiment using custom lexicon and foundation time series models
- Data Science, Data Structures, Algorithms, Machine Learning
- Programming in Python, Problem Solving, Predictive Analytics, etc.
- ✉️ Email: yejincc99@gmail.com