AI Governance • Scientific Computing • Materials Discovery

Hyun-Jung Kim

Ph.D. in Theoretical Condensed Matter Physics

AI Governance Workstream Lead · Computational Materials Scientist

My background spans computational materials physics, OLED materials R&D, and enterprise AI governance at LG Display.

Current responsibilities include AI project review, technical scouting, committee operation, internal GitLab platform operation, MLOps enablement, and internal education for AI and AX adoption.

View selected work AI Tech Review Letters

GitHub LinkedIn ORCID Google Scholar Email

Profile

Computational materials physics and enterprise AI governance.

Research and project experience includes electronic-structure theory, quantum-chemical simulation, OLED materials analysis, AI project review, GitLab-based MLOps operation, and internal training materials.

30+ peer-reviewed papers

10+ years across academia and industry

14 & 100+ public GitHub repositories & stars earned

Humboldt Research Fellowship (for Postdoc.)
POSCO TJ Park (Cheong-Am) Science Fellowship
KIAS Academic Research Award
Outstanding Ph.D. Dissertation Award, Hanyang Univ.

Current Work

AI project review, emerging technology scouting, GitLab operation, and internal AI lectures

Current responsibilities cover AI initiative review, emerging technology scouting including quantum-computing use cases, internal GitLab platform management and operation, GitLab-based MLOps enablement, and internal AI lectures for AI and AX teams.

Governance

AI project review and emerging technology review

I prepare and review AI initiative materials, including project scope, expected deliverables, review records, risks, follow-up items, and early feasibility checks for new technologies such as quantum computing.

GitLab Operations

Internal GitLab platform operation and MLOps enablement

Responsibilities include internal GitLab platform management and operation, repository structures, collaboration workflows, deliverable tracking, and GitLab-based MLOps practice support.

Education

Internal AI lectures and adoption

Training materials and sessions cover AI/ML fundamentals, workflow automation, LLM application development, AX execution, and Git/GitLab collaboration.

AI Enablement Assets

Selected public artifacts for education, participation, and review.

Selected public artifacts related to education sites, an event participation system, and AI technology review notes.

AI Education

AI education materials and lecture sites

Web-based materials and lectures covering AI fundamentals, machine learning, AI/ML mathematics, LLM application development, AX execution, and Git/GitLab collaboration.

Event System

Hackathon participation platform

A Cloudflare-deployed audience participation system for a company-wide hackathon, covering real-time voting, cheering, quiz, raffle, admin, and wall views.

Vibe Vote Arena

AI Technology Review

AI Tech Review Letters

I use AI-assisted writing workflows to turn source material on AI technologies, frontier models, agent systems, and materials AI into readable technical reviews.

Review Hub

Trajectory

Roles and projects by period

The timeline lists graduate study, postdoctoral research, industrial materials R&D, and the current AI Governance role.

2025–Present

AI Governance Team, LG Display

Workstream lead covering AI project review, technical scouting, committee operations, internal education platforms, event participation systems, and early-stage exploration of quantum-computing use cases and external collaboration paths.

2022–2024

OLED Materials Research, LG Display

Applied quantum-chemical and DFT-driven analysis to molecular design problems, linking computation, mechanism analysis, and data-driven screening for industrial R&D.

2020–2022

Forschungszentrum Jülich

Visiting scientist and postdoctoral researcher at PGI-1 and IAS-1, supported by the Humboldt Research Fellowship, working on electronic structure, topology, and transferable modeling.

Worked with Prof. Stefan Blügel.

2015–2020

Korea Institute for Advanced Study

Postdoctoral researcher and research fellow in computational sciences and the Quantum Universe Center, developing theory-driven workflows for low-dimensional and topological materials.

Worked with Prof. Young-Woo Son.

2009–2015

Hanyang University

M.S. and Ph.D. in theoretical condensed matter physics, building the academic foundation in electronic structure, low-dimensional systems, and surface science.

Ph.D. supervisor: Prof. Joon-Hyung Cho.

Scholarship

Selected publications, tools, and research themes

#AI-for-materials, #phase-transition, #topological-materials, #chiral-CDW, and #scientific-software, built around first-principles, quantum-chemical, and tight-binding workflows.

Selected publications

Machine Learning Strategy Towards Inverse Design of Blue TADF Emitter SID Symposium Digest of Technical Papers, 2024. Co-first author; OLED materials AI/ML.
Circular Dichroism of Emergent Chiral Stacking Orders in Quasi-One-Dimensional Charge Density Waves Physical Review Letters 128, 046401 (2022). Corresponding author.
Origins of the structural phase transitions in MoTe₂ and WTe₂ Physical Review B 95, 180101(R) (2017). First author; Rapid Communication.
Competing Magnetic Orderings and Tunable Topological States in Two-Dimensional Hexagonal Organometallic Lattices Physical Review B 93, 041404(R) (2016). First author; KIAS selected research achievement.
Driving Force of Phase Transition in Indium Nanowires on Si(111) Physical Review Letters 110, 116801 (2013). First author.

Google Scholar

Open-source research tools

TBFIT Slater-Koster tight-binding parameter fitting toolkit for transferable model development.
VASPBERRY Berry-curvature and Chern-number post-processing workflow for VASP WAVECAR data.
VASPBAUM Band-unfolding pipeline for VASP-based electronic-structure analysis.

Research map

Selected works

The full publication list and citation record remain in the CV and Google Scholar profile.

#AI-for-materials

Blue TADF emitter inverse design using DFT-based training data and graph neural networks.
AI/ML workflows for simulation-backed materials screening and property prediction.
Related materials papers: Dirac-like band valley transition; twisted WSe₂ photoemission; dimensionality-driven MoTe₂ phase transition.

#phase-transition

Indium nanowires on Si(111), MoTe₂/WTe₂, and low-dimensional structural stability.
First-principles analysis of electronic and bonding changes behind phase transitions.
Related papers: Driving Force of Phase Transition in Indium Nanowires on Si(111); Stabilization and Manipulation of Electronically Phase-Separated Ground States; Equivalence of electronic and mechanical stresses; Origins of structural phase transitions in MoTe₂ and WTe₂; Anomalous dimensionality-driven phase transition of MoTe₂.

#topological-materials

2D organometallic lattices, magnetic ordering, quantum anomalous Hall states, and valley/spin responses.
Topological materials work across PRB Rapid, PRL, Physical Review Materials, and Nano Letters publications.
Related papers: Competing magnetic orderings and tunable topological states; Ferromagnetic Weyl fermions in Gd₂C; Z₂ topology of bismuth; symmetry-dictated grain boundary state; competing edge structures of Sb and Bi bilayers; reshaped Weyl dispersions in MoTe₂.

#chiral-CDW

Chiral stacking orders in quasi-1D charge density waves and circular dichroism response.
Connected to VASPBERRY-based Berry curvature and topological post-processing workflows.
Related papers: Two-dimensional chiral stacking orders in quasi-one-dimensional charge density waves; Circular Dichroism of Emergent Chiral Stacking Orders.

#scientific-software

TBFIT, VASPBERRY, and VASPBAUM as reusable tools for tight-binding, topology, and VASP analysis.
Open-source research workflows designed around interpretable electronic-structure calculations.

Future Work

Quantum-computing approaches for materials calculation and inverse design

Planning work on how quantum-computing methods could be connected to materials property calculation, candidate search, and inverse-design workflows. The current focus is problem framing, feasibility review, and hybrid quantum-classical workflow design rather than completed implementation.

Quantum computing Materials property calculation Inverse design Hybrid quantum-classical workflows

Contact

Contact and profile links

The CV and external profiles linked below contain the fuller academic and project record. I can also discuss internal AI adoption, AI-agent construction and use, GitLab-based workflows, materials modeling, and quantum-computing feasibility review.

Reach out

Email CV CV (KR) GitHub LinkedIn ORCID