Jinwoo Seol
AI & Bioinformatics Software Engineer
Seoul
Summary
“A Full-Cycle AI Software Engineer Maximizing the Value of Biological Data”
Based on domain expertise built through a combined major in Life Sciences and Computer Engineering at POSTECH, I have developed practical, commercial-grade software in the fields of molecular diagnostics and CGT (Cell & Gene Therapy). I led the development of Digital PCR/Melting analysis systems, designing signal processing and ultra-precise algorithms that improved resolution by 2–5 times compared to existing methods and were applied as patents. Based on these technologies, I implemented an MSI prediction AI model achieving over 95% accuracy on clinical datasets, significantly enhancing diagnostic precision.
In the CGT field, I designed deep-learning algorithms for microscopy image analysis, achieving over 99.5% accuracy in cell recognition. I possess strong capabilities in implementing complex biological data into software usable in real medical environments. In addition to end-to-end development skills using C++/Python/Java/Qt and experience responding to medical device regulations (CE-IVDR/MFDS), I have designed and implemented cybersecurity technologies such as equipment and network communication encryption, database access control, and stored data encryption, enabling me to take responsibility for protecting clinical data.
Overview
4
4
years of professional experience
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)
Work History
AI Engineer – Digital PCR & Melting Analysis
OPTOLANE
10.2024 - Current
- Development of a diagnostic MSI prediction AI model with over 95% accuracy on clinical data based on digital melting curves
- Development of ML-based analysis modules for melting curve QC, cluster separation, and noise removal
- Construction of a complete analysis pipeline including signal processing, feature extraction, and AI inference
- Design, development, and patent registration of core ultra-precise Tm analysis and calibration algorithms that increase resolution by 2–5 times compared to existing methods
Tech: Python, Scikit-learn, Cursor AI
AI Cell Recognition System Development
OPTOLANE
06.2024 - Current
- Design of a CGT analysis system combining AI-based cell recognition with proprietary PCR assay data
- Development of a deep-learning–based cell recognition model with over 99.5% accuracy for automated microscopy image analysis
- Construction of the full pipeline for CGT analysis including data preprocessing, AI inference, and result visualization
- Independent development of a prototype including UI and analysis functions within two months using Cursor AI
- Tech: PyTorch, TensorFlow, PySide6, PyQt, Cursor AI
Automated DNA Extraction Device Development
OPTOLANE
09.2023 - Current
- Completion of a prototype through establishment of core functions and architecture of a nucleic acid extraction system
- Design of UI scenarios and system optimization aimed at usability and security based on analysis of medical professionals’ requirements
- Development of automated consumable inspection functions and optimal path calculation systems capable of flexibly responding to various situations
- Reduction of the device control interface development period from four months to two months through outsourcing vendor management, shortening the overall project schedule
- Preparation of user manuals and technical documents for CE and MFDS certification
- Tech: StarUML, Draw.io, Android, Java
Diagnostic PCR Instrument Software Development
OPTOLANE
10.2022 - Current
- Development of Qt-based UI and analysis algorithms on Linux and Windows platforms
- Development of diagnostic data integration functions with AWS servers using Java on Windows
- Diagnostic data management and performance optimization using MariaDB
- Design and implementation of cybersecurity functions required for medical device software, including equipment and network communication encryption, database access control, and stored data encryption
- Compliance with regulation-based development processes through preparation of user manuals and technical documentation for CE-IVDR and MFDS certification
- Tech: C++, Qt, Java, Linux, MariaDB, SQL, Eclipse, SVN
Deep Learning-Based Breast Cancer Targeting Model
Personal Project
03.2022 - 06.2022
- Design of a breast cancer prediction model based on EfficientNet-B2, achieving an initial accuracy of 86%
- Improvement of model accuracy up to 93% by applying probability-density–based targeting enhancement techniques
- 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
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.
Core Competencies
- High-Precision AI Modeling – Experience developing MSI prediction AI with over 95% accuracy on clinical data and deep-learning–based cell recognition models with over 99.5% accuracy in the CGT field
- Digital Analysis Performance Innovation – Development of Digital Melting signal correction and ultra-precise algorithms improving resolution by 2–5 times, with related patents
- End-to-End Development – End-to-end development of diagnostic software from planning to deployment using C/C++, Python, Java, and Qt
- Regulatory & Security Compliance – Experience responding to CE-IVDR/MFDS regulations and implementing cybersecurity functions such as communication encryption, database access control, and data encryption
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.