Curriculum Vitae
Ho-min Park
| Email: homin.park@ghent.ac.kr | GitHub: powersimmani | ORCID: 0000-0001-9937-8617 |
Education
Ph.D. in Computer Science Engineering (2018 - 2025)
Ghent University, Belgium
- Dissertation: “Advancing Detection through Deep Learning for Industrial, Environmental, and Health Applications”
- Advisors: Prof. Wesley De Neve, Prof. Arnout Van Messem
M.S. in Computer Engineering (2016 - 2018)
Ajou University, Suwon, South Korea
- Thesis: “Cited count prediction modeling from large citation network”
B.S. in Computer Science and Engineering (2010 - 2016)
Ajou University, Suwon, South Korea
ML Education & Curriculum Design
AI Vacation School (AIVS) - Founder & Lead Instructor (2021 - 2025)
Ghent University Global Campus
- Founded and led a volunteer-driven ML bootcamp (100+ hours per session) for undergraduate students
- Designed a 20-lecture curriculum: regression, MLPs, CNNs, RNNs, Transformers, LLMs, GANs, Diffusion models, XAI
- Created original materials: presentation slides, Google Colab notebooks, Excel worksheets
- Mentored over 10 entry-level AI researchers
Funded Projects
Depression Diagnosis & Drug Adherence Research (2022 - 2025)
- Developed models for MuSe-Stress and MuSe-Personalization challenges
- Achieved 2nd place (MuSe-Personalisation 2023) and 3rd place (MuSe-Stress 2022)
- Funding: NRF Korea, Department of Biotechnology India, Ghent University Global Campus
Environmental Monitoring Project (2020 - 2023)
- Led development of MP-Net for automated microplastics detection
- Funding: Special Research Fund of Ghent University
Smart Packaging System Development (2018 - 2021)
- Developed and patented two AI-powered measurement systems
- Funding: Ministry of Trade, Industry, and Energy (MOTIE), Korea
Awards
| Award | Event | Year |
|---|---|---|
| 2nd Place | MuSe-Personalisation Challenge 2023 | 2023 |
| 3rd Place | MuSe-Stress Challenge 2022 | 2022 |
| Best Presentation | IIAE Conference | 2019 |
Skills
ML & AI
- Architectures: CNN, RNN, LSTM, GRU, Transformer, GAN, Diffusion Models, MLPs
- Techniques: Transfer Learning, Feature Engineering, Model Explainability (SHAP, CAM)
- Tools: PyTorch, PyTorch Lightning, WandB, Python
Languages
- Korean: Native
- English: Professional (TOEIC 860, OPIc IH)
Certifications
- TOEIC: 860 points (2024)
- OPIc: Intermediate High (2024)
- Information Processing Engineer (2015)