Jinwoo Seol
AI & Bioinformatics Software Engineer
Seoul
Summary
I specialize in developing AI-driven diagnostic analysis systems that integrate biological insight with advanced deep learning techniques. My work spans Digital PCR, Digital Melting, and CGT platforms where I independently design and implement end-to-end pipelines—from signal processing and feature extraction to AI inference. I build production-ready prototypes using Python, C++, and Qt, develop high-precision Tm calibration algorithms, and create ML modules for QC, clustering, and noise reduction. With hands-on experience in medical software security, regulatory documentation, and clinical-grade workflows, I deliver reliable solutions suitable for both research and clinical settings.
Overview
4
4
years of professional experience
Work History
AI Engineer – Digital PCR & Melting Analysis
OPTOLANE
10.2024 - Current
- Designed and developed ultra-high-precision melting analysis algorithms with 0.1°C resolution, including core calibration logic.
- Authored and listed patents for Digital Melting analysis and calibration technologies.
- Built ML-based modules for melting curve QC, cluster separation, noise removal, and digital melting feature extraction.
- Implemented AI models for MSI diagnosis using digital melting Tm histogram patterns.
- Developed a complete analysis pipeline covering signal processing, feature engineering, and inference.
AI Cell Recognition System Development
OPTOLANE
06.2024 - Current
- Designed an AI-driven CGT (Cell & Gene Therapy) analysis framework integrating cell-recognition models with PCR-based assay data.
- Built deep learning models for automated cell detection in microscope images.
- Developed the full workflow: data preprocessing, AI inference, visualization, and reporting.
- Independently built a working prototype—including UI and analysis functions—using Cursor AI within 2 months.
- Structured analysis logic and user flow optimized for research and clinical environments.
- Tech: PyTorch, TensorFlow, PySide6, PyQt, Cursor AI
Automated DNA Extraction Device Development
OPTOLANE
09.2023 - Current
- Defined core system functionality and architecture for prototype development.
- Designed UI and operation scenarios focusing on ease-of-use and clinical workflow.
- Built automated consumable-checking functions and optimized motion paths for efficiency.
- Shortened external development cycle from 4 months to 2 months through vendor management.
- Prepared CE/MFDS documentation including operation manuals.
- Tech: StarUML, Draw.io, Android, Java
Diagnostic PCR Instrument Software Development
OPTOLANE
10.2022 - Current
- Developed Qt-based UI and analysis algorithms for Windows and Linux.
- Implemented AWS integration using Java to synchronize clinical test data.
- Managed diagnostic data with MariaDB, optimizing query speed and storage efficiency.
- Designed and implemented cybersecurity features: encrypted device/network communication, DB access control, and encrypted data storage.
- Authored user manuals and technical documentation for CE-IVDR and MFDS compliance.
- Tech: C++, Qt, Java, Linux, MariaDB, SQL, Eclipse, SVN
Deep Learning-Based Breast Cancer Targeting Model
Personal Project
03.2022 - 06.2022
- Developed a breast cancer subtype prediction model using a custom EfficientNetB2-based deep learning architecture.
- Built a complete preprocessing pipeline including normalization, augmentation, and class balance correction.
- Improved accuracy and generalization through transfer learning, dropout tuning, and cross-validation.
- Validated prediction reliability using Grad-CAM to confirm biologically meaningful feature activation patterns.
- Achieved 91% overall accuracy, outperforming baseline CNN models in stability and consistency.
- Tech : NumPy, Pandas, Matplotlib, Seaborn, TensorFlow, Keras, Scikit-learn, Jupyter Notebook
Education
Bachelor of Science - Double Major: Life Science & Computer Engineering
POSTECH (Pohang University of Science And Technology)
South Korea02.2022
Skills
Deep Learning, Computer Vision
Timeline
AI Engineer – Digital PCR & Melting Analysis
OPTOLANE
10.2024 - Current
AI Cell Recognition System Development
OPTOLANE
06.2024 - Current
Automated DNA Extraction Device Development
OPTOLANE
09.2023 - Current
Diagnostic PCR Instrument Software Development
OPTOLANE
10.2022 - Current
Deep Learning-Based Breast Cancer Targeting Model
Personal Project
03.2022 - 06.2022
Bachelor of Science - Double Major: Life Science & Computer Engineering
POSTECH (Pohang University of Science And Technology)
의료 개발 경험
- Genexine, Inc. 분석팀
- 인턴 프로그램
- DNA 클로닝을 통한 폐암 DNA 치료제 백신 개발
- 폐암 DNA 치료제 백신으로서의 기능 확인
- C-BIOMEX
- 유방암 유발 단백질 검출 펩타이드 기반 바이오마커 개발
- 항원-항체 반응을 이용한 펩타이드-단백질 친화도 분석
- 한국뇌연구원 (정서, 인지질환 연구 그룹)
- 우울증에 관여하는 뇌의 보상경로 자극에 따른 쥐의 행동변화 연구
- 우울증에 의한 쥐의 유전자 발현 변화 분석
Core Competencies
- Experienced in developing predictive modeling projects leveraging deep learning technologies
- Skilled in UI design, operational workflow architecture, and end-to-end development management
- Proficient in delivering projects using multiple programming languages, including C/C++, Java, and Python
- Strong understanding of medical device development grounded in extensive biological knowledge
Medical Development Experience
Neurogenetics Laboratory, POSTECH
- Modeling of neurodevelopmental disorders associated with congenital brain malformations.
Neuro-Epigenetics Laboratory, POSTECH
- Characterization of activity-dependent transcriptional regulation of the Arc gene in neuronal cells.
Molecular Neuroscience Laboratory, POSTECH
- Viral-mediated neural pathway mapping for anatomical and functional connectivity confirmation.
Analysis Team, Genexine, Inc.
- Development and validation of DNA-based therapeutic vaccine constructs targeting lung cancer.
C-BIOMEX
- Development of peptide-based diagnostic biomarkers for breast cancer and assessment of peptide–protein binding affinity.
Korea Brain Research Institute (KBRI)
- Analysis of behavioral phenotypes and gene-expression alterations in murine depression models under neural stimulation.