The Big Data Intelligence lab at KAIST is led by Prof. Joyce Jiyoung Whang at the School of Computing. The group engages in fundamental research on big data, emphasizing advanced algorithms for modeling and analyzing massive scientific and industrial datasets. In particular, the group focuses on graph machine learning and mining to interpret complex entity interactions and solve diverse real-world challenges with highly scalable algorithms.

Research Areas

Graph Machine Learning Deep Learning Knowledge Graphs Data Mining Big Data Analytics Data Science

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Professor

Joyce Jiyoung Whang (황지영)

Joyce Jiyoung Whang (황지영)

Associate Professor, School of Computing, KAIST
Adjunct Professor, Kim Jaechul Graduate School of AI, KAIST
Adjunct Professor, Graduate School of Data Science (GSDS), KAIST
Email: jjwhang@kaist.ac.kr
Office: KAIST, N1 Building 905
Education
Ph.D. in Computer Science, The University of Texas at Austin, TX, USA, 2015.
(Supervisor: Inderjit S. Dhillon)
Research Interests
Graph Machine Learning, Deep Learning, Data Mining, Big Data Analytics, and Data Science.
Curriculum Vitae

Members

Ph.D. Students

Chanyoung Chung (정찬영)

Chanyoung Chung (정찬영)

Mar. 2022 ~: M.S./Ph.D. Integrated Program in School of Computing

Mar. 2021 ~ Feb. 2022: M.S. Program in School of Computing

Feb. 2021: B.S. in Computing (double major: Mathematical Sciences), KAIST

Jaejun Lee (이재준)

Jaejun Lee (이재준)

Mar. 2023 ~: Ph.D. Program in School of Computing

Feb. 2023: M.S. in Computing, KAIST

Aug. 2021: B.S. in Computing (double major: Mathematical Sciences), KAIST

Heehyeon Kim (김희현)

Heehyeon Kim (김희현)

Sep. 2024 ~: Ph.D. Program in School of Computing

Aug. 2024: M.S. in Computing, KAIST

Aug. 2022: B.S. in IoT Artificial Intelligence Convergence, Chonnam National University

Minsung Hwang (황민성)

Minsung Hwang (황민성)

Sep. 2024 ~: Ph.D. Program in School of Computing

Aug. 2024: M.S. in Computing, KAIST

Feb. 2023: B.S. in Electrical Engineering (minor: Computing), KAIST

Jinhyeok Choi (최진혁)

Jinhyeok Choi (최진혁)

Mar. 2025 ~: Ph.D. Program in School of Computing

Feb. 2025: M.S. in Computing, KAIST

Feb. 2023: B.S. in Computing (minor: Electrical Engineering), KAIST

Kyeongryul Lee (이경률)

Kyeongryul Lee (이경률)

Mar. 2026 ~: Ph.D. Program in School of Computing

Feb. 2026: M.S. in Data Science, KAIST

Feb. 2024: B.S. in Data Science (double major: Financial Mathematics & Statistics), The University of Sydney

M.S. Students

Donggyu Yoon (윤동규)

Donggyu Yoon (윤동규)

Mar. 2025 ~: Program in School of Computing

Feb. 2025: B.S. in Computing (minor: Electrical Engineering), KAIST

Kidong Nam (남기동)

Kidong Nam (남기동)

Mar. 2025 ~: KT-AI M.S. Program in School of Computing

Aug. 2024: B.S. in Philosophy (double major: Computer Science and Engineering), Sogang University

Jeesoo Kim (김지수)

Jeesoo Kim (김지수)

Sep. 2025 ~: M.S. Program in Graduate School of Data Science

Aug. 2025: B.A. in Business Administration (double major: Computer Science and Engineering), Sogang University

Jeemin Kim (김지민)

Jeemin Kim (김지민)

Mar. 2026 ~: M.S. Program in School of Computing

Feb. 2026: B.S. in Computing (minor: Bio and Brain Engineering), KAIST

Seheon Kim (김세헌)

Seheon Kim (김세헌)

Mar. 2026 ~: M.S. Program in School of Computing

Feb. 2026: B.S. in Computing, KAIST

Alumni

Jaejun Lee (이재준)

Jaejun Lee (이재준)

M.S. in Computing, Feb. 2023, KAIST

Thesis: Image-based Augmented Knowledge Graph Embedding

Aug. 2021: B.S. in Computing (double major: Mathematical Sciences), KAIST

Seunghwan Kong (공승환)

Seunghwan Kong (공승환)

M.S. in Computing, Feb. 2023, KAIST

Thesis: Representation Learning on Knowledge Graphs with Entity Types

Aug. 2021: B.S. in Computing (double major: Mathematical Sciences), KAIST

Heehyeon Kim (김희현)

Heehyeon Kim (김희현)

M.S. in Computing, Aug. 2024, KAIST

Thesis: Fraud Detection Using Graph Neural Networks

Aug. 2022: B.S. in IoT Artificial Intelligence Convergence, Chonnam National University

Minsung Hwang (황민성)

Minsung Hwang (황민성)

M.S. in Computing, Aug. 2024, KAIST

Thesis: Theoretical Generalization Bounds for Knowledge Graph Representation Learning

Feb. 2023: B.S. in Electrical Engineering (minor: Computing), KAIST

Jinhyeok Choi (최진혁)

Jinhyeok Choi (최진혁)

M.S. in Computing, Feb. 2025, KAIST

Thesis: Spatio-Temporal Graph Forecasting by Modeling Long-Range Dependency via Selective State Spaces

Feb. 2023: B.S. in Computing (minor: Electrical Engineering), KAIST

Junho Park (박준호)

Junho Park (박준호)

M.S. in Computing, Feb. 2025, KAIST

Thesis: Root Cause Analysis for Microservice Systems with Resource-Sharing Dependencies

Aug. 2021: B.S. in Electrical Engineering and Computer Science, GIST

Kyeongryul Lee (이경률)

Kyeongryul Lee (이경률)

M.S. in Data Science, Feb. 2026, KAIST

Thesis: Probing Safety Vulnerabilities in Large Language Models and Multimodal Models via Auto-Generated Jailbreak Prompts

Feb. 2024: B.S. in Data Science (double major: Financial Mathematics & Statistics), The University of Sydney

Minhyeong An (안민형)

Minhyeong An (안민형)

M.S. in Computing, Feb. 2026, KAIST

Thesis: Graph-enhanced Retrieval-Augmented Generation for Microservice Root Cause Analysis with Large Language Models

Feb. 2024: B.S. in Computing (double major: Electrical Engineering), KAIST

Selected Publications

International Publications

‡: Equal Contribution, *: Corresponding Author

2025

Beneath the Facade: Probing Safety Vulnerabilities in LLMs via Auto-Generated Jailbreak Prompts

H. Kim, K. Lee, and J. J. Whang*

Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)

2025

Structure Is All You Need: Structural Representation Learning on Hyper-Relational Knowledge Graphs

J. Lee and J. J. Whang*

International Conference on Machine Learning (ICML)

2025

Stability and Generalization Capability of Subgraph Reasoning Models for Inductive Knowledge Graph Completion

M. Hwang, J. Lee, and J. J. Whang*

International Conference on Machine Learning (ICML)

2025

Unveiling the Threat of Fraud Gangs to Graph Neural Networks: Multi-Target Graph Injection Attacks against GNN-Based Fraud Detectors

J. Choi, H. Kim, and J. J. Whang*

AAAI Conference on Artificial Intelligence (AAAI)

2025

Unifying Inductive, Cross-Domain, and Multimodal Learning for Robust and Generalizable Recommendation

C. Chung, K. Lee, S. Park, and J. J. Whang*

Multimodal Generative Search and Recommendation (MMGenSR) Workshop at Conference on Information and Knowledge Management (CIKM)

2025

SAIF: A Comprehensive Framework for Evaluating the Risks of Generative AI in the Public Sector

K. Lee, H. Kim, and J. J. Whang*

AI for Public Missions (AIPM) Workshop at AAAI Conference on Artificial Intelligence (AAAI)

2024

PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning

J. Lee, M. Hwang, and J. J. Whang*

International Conference on Machine Learning (ICML)

2024

Why So Gullible? Enhancing the Robustness of Retrieval-Augmented Models against Counterfactual Noise

G. Hong, J. Kim, J. Kang, S. Myaeng, and J. J. Whang*

Findings of the Association for Computational Linguistics: NAACL (Findings of NAACL)

2024

SpoT-Mamba: Learning Long-Range Dependency on Spatio-Temporal Graphs with Selective State Spaces

J. Choi, H. Kim, M. An, and J. J. Whang*

Spatio-Temporal Reasoning and Learning (STRL) Workshop at International Joint Conference on Artificial Intelligence (IJCAI)

2023

VISTA: Visual-Textual Knowledge Graph Representation Learning

J. Lee, C. Chung, H. Lee, S. Jo, and J. J. Whang*

Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP)

2023

FinePrompt: Unveiling the Role of Finetuned Inductive Bias on Compositional Reasoning in GPT-4

J. Kim, G. Hong, S. Myaeng, and J. J. Whang*

Findings of Empirical Methods in Natural Language Processing (Findings of EMNLP)

2023

Representation Learning on Hyper-Relational and Numeric Knowledge Graphs with Transformers

C. Chung, J. Lee, and J. J. Whang*

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

2023

InGram: Inductive Knowledge Graph Embedding via Relation Graphs

J. Lee, C. Chung, and J. J. Whang*

International Conference on Machine Learning (ICML)

2023

Learning Representations of Bi-level Knowledge Graphs for Reasoning beyond Link Prediction

C. Chung and J. J. Whang*

AAAI Conference on Artificial Intelligence (AAAI)

2023

Dynamic Relation-Attentive Graph Neural Networks for Fraud Detection

H. Kim, J. Choi, and J. J. Whang*

Machine Learning on Graphs (MLoG) Workshop at IEEE International Conference on Data Mining (ICDM)

2022

Semantic Grasping via a Knowledge Graph of Robotic Manipulation: A Graph Representation Learning Approach

J. H. Kwak, J. Lee, J. J. Whang*, and S. Jo*

IEEE Robotics and Automation Letters

2022

HiddenCPG: Large-Scale Vulnerable Clone Detection Using Subgraph Isomorphism of Code Property Graphs

S. Wi, S. Woo, J. J. Whang, and S. Son*

The ACM Web Conference

2021

Knowledge Graph Embedding via Metagraph Learning

C. Chung and J. J. Whang*

International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

2021

Image-based Lifelogging: User Emotion Perspective

J. Bum, H. Choo, and J. J. Whang*

Computers, Materials & Continua

2021

Sentiment-based Sub-event Segmentation and Key Photo Selection

J. Bum, J. J. Whang*, and H. Choo*

Journal of Visual Communication and Image Representation

2020

MEGA: Multi-View Semi-Supervised Clustering of Hypergraphs

J. J. Whang, R. Du, S. Jung, G. Lee, B. Drake, Q. Liu, S. Kang, and H. Park

International Conference on Very Large Data Bases (VLDB)

2020

Sparse Probabilistic K-means

Y. M. Jung, J. J. Whang, and S. Yun*

Applied Mathematics and Computation

2020

Scalable Anti-TrustRank with Qualified Site-level Seeds for Link-based Web Spam Detection

J. J. Whang*, Y. Jung, S. Kang, D. Yoo, and I. S. Dhillon

Workshop on CyberSafety: Computational Methods in Online Misbehavior at the Web Conference

2019

Hyperlink Classification via Structured Graph Embedding

G. Lee, S. Kang, and J. J. Whang*

International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

2019

Non-exhaustive, Overlapping Clustering

J. J. Whang*, Y. Hou, D. F. Gleich, and I. S. Dhillon

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

2019

SmartGrip: Grip Sensing System for Commodity Mobile Devices through Sound Signals

N. Kim, J. Lee, J. J. Whang, and J. Lee*

Personal and Ubiquitous Computing

2018

Fast Asynchronous Anti-TrustRank for Web Spam Detection

J. J. Whang*, Y. S. Jeong, I. S. Dhillon, S. Kang, and J. Lee

Workshop on MIS2: Misinformation and Misbehavior Mining on the Web at ACM International Conference on Web Search and Data Mining (WSDM)

2017

Non-Exhaustive, Overlapping Co-Clustering

J. J. Whang* and I. S. Dhillon

ACM Conference on Information and Knowledge Management (CIKM)

2017

An Empirical Study of Community Overlap: Ground-truth, Algorithmic Solutions, and Implications

J. J. Whang*

ACM Conference on Information and Knowledge Management (CIKM)

2016

Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering

Y. Hou, J. J. Whang, D. F. Gleich, and I. S. Dhillon

SIAM International Conference on Data Mining (SDM)

2016

Overlapping Community Detection Using Neighborhood-Inflated Seed Expansion

J. J. Whang*, D. F. Gleich, and I. S. Dhillon

IEEE Transactions on Knowledge and Data Engineering (TKDE)

2015

Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming

Y. Hou, J. J. Whang, D. F. Gleich, and I. S. Dhillon

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)

2015

Scalable Data-driven PageRank: Algorithms, System Issues, and Lessons Learned

J. J. Whang, A. Lenharth, I. S. Dhillon, and K. Pingali

International European Conference on Parallel and Distributed Computing (Euro-Par)

2015

Non-exhaustive, Overlapping k-means

J. J. Whang, I. S. Dhillon, and D. F. Gleich

SIAM International Conference on Data Mining (SDM)

2013

Stochastic Blockmodel with Cluster Overlap, Relevance Selection, and Similarity-Based Smoothing

J. J. Whang, P. Rai, and I. S. Dhillon

IEEE International Conference on Data Mining (ICDM)

2013

Overlapping Community Detection Using Seed Set Expansion

J. J. Whang, D. F. Gleich, and I. S. Dhillon

ACM Conference on Information and Knowledge Management (CIKM)

2012

Scalable and Memory-Efficient Clustering of Large-Scale Social Networks

J. J. Whang, X. Sui, and I. S. Dhillon

IEEE International Conference on Data Mining (ICDM)

2012

Scalable Clustering of Signed Networks using Balance Normalized Cut

K. Chiang, J. J. Whang, and I. S. Dhillon

ACM Conference on Information and Knowledge Management (CIKM)

2012

Parallel Clustered Low-rank Approximation of Graphs and Its Application to Link Prediction

X. Sui, T. Lee, J. J. Whang, B. Savas, S. Jain, K. Pingali, and I. S. Dhillon

International Workshop on Languages and Compilers for Parallel Computing (LCPC)

Domestic Papers

2025

Root Cause Analysis for Microservice Systems Using Anomaly Propagation by Resource Sharing (자원 공유에 따른 이상치 전파를 활용한 마이크로서비스 시스템 결함의 근본 원인 분석)

박준호, 황지영

정보과학회논문지 (Journal of KIISE), 2025년 4월

2022

Knowledge Graph Embedding with Entity Type Constraints (개체 유형 정보를 활용한 지식 그래프 임베딩)

공승환, 정찬영, 주수헌, 황지영

정보과학회논문지 (Journal of KIISE), 2022년 9월

2022

Knowledge Graph Embedding with Dynamic Attention (동적 어텐션을 이용한 지식그래프 임베딩)

황민성, 황지영

한국컴퓨터종합학술대회 논문집, 2022년 6월

Patents

2025

복층 지식 그래프 임베딩 방법 및 그 시스템

황지영, 정찬영

등록번호: 10-2834344-0000

Projects

National Research Foundation of Korea

  • Responsible Multimodal Graph AI (책임 있는 멀티모달 그래프 인공지능)
    Mar. 2025 ~ Feb. 2028 Principal Investigator
  • Extendable Graph Representation Learning (확장 가능한 그래프 표현학습)
    Mar. 2022 ~ Feb. 2025 Principal Investigator
  • MARS Artificial Intelligence Integrated Research Center (MARS 인공지능 통합연구센터)
    Aug. 2018 ~ Feb. 2024
  • Semi-Supervised Multi-View Learning with Graphs (다각적 데이터 융합을 통한 그래프기반 준지도 학습)
    Mar. 2019 ~ Feb. 2022 Principal Investigator
  • Modeling Information Propagation by Exploiting the Clustering Structure of Massive Social Networks (거대 소셜 네트워크의 클러스터링 구조를 활용한 정보 전파 메커니즘 모델링)
    Nov. 2016 ~ Oct. 2019 Principal Investigator

Samsung Electronics

  • AI Agent-based Omni Knowledge Graph Construction and its Applications (AI Agent 기반 Omni Knowledge Graph 구축 및 활용 기술 개발)
    Oct. 2025 ~ Sep. 2030 Principal Investigator
  • Knowledge Graph Modeling for Semiconductor Data (반도체 공정 데이터의 다각적 분석을 위한 지식 그래프 모델링)
    Sep. 2020 ~ Sep. 2023 Principal Investigator

Institute of Information & communications Technology Planning & Evaluation (IITP)

LG AI STAR Talent Development Program for Leading Large-Scale Generative AI Models in the Physical AI Domain (Physical AI 분야의 거대 생성모델 기술 선도를 위한 LG AI STAR 인재양성 사업)
Jul. 2025 ~ Dec. 2028
Development of AI Technology to support Expert Decision-making that can Explain the Reasons/Grounds for Judgment Results based on Expert Knowledge (전문지식 대상 판단결과의 이유/근거를 설명가능한 전문가 의사결정 지원 인공지능 기술개발)
Apr. 2022 ~ Dec. 2026

Kyobo & DPLANEX

  • Multimodal Cross-Domain Recommendation Systems for Personalized Services (개인 맞춤형 서비스를 위한 멀티모달 크로스 도메인 추천 시스템)
    Dec. 2024 ~ Nov. 2025 Principal Investigator
  • GNN-based Insurance Fraud Detection (그래프 신경망(GNN) 기반 보험사기 예측 연구)
    Aug. 2022 ~ Nov. 2025 Principal Investigator

Telecommunications Technology Association (TTA)

  • 생성형 AI의 기술 혁신에 대응 가능한 안정성 평가체계 수립 연구
    Oct. 2024 ~ Dec. 2024 Principal Investigator
  • AI 위험 분야별 안전성 평가를 위한 데이터셋 로드맵 구축
    Oct. 2024 ~ Dec. 2024 Principal Investigator

DevStack

  • Development of a Technology for Analyzing Root Causes and Proposing Countermeasures for Containerized OpenStack Service’s Failures Using LLM and Knowledge Graphs (거대언어모델 및 지식그래프를 활용하여 컨테이너화된 오픈스택 장애원인 분석 및 대응방안 제시 기술개발)
    Mar. 2025 ~ Nov. 2025 Principal Investigator
  • Development of Intelligent Kubernetes Fault Cause Analysis and Response Proposal Method Using LLM and Knowledge Graphs (LLM 및 지식그래프를 활용한 지능형 K8s 장애 원인 분석 및 대응 방안 제시 기술 개발)
    May 2024 ~ Nov. 2024 Principal Investigator

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[학생 모집 중]

석사 신입생: 지원서 링크

학부 연구생: 지원 링크

우리 연구실에 관심있는 학생들은 jjwhang@kaist.ac.kr 로 문의바랍니다.

Location

KAIST, N1 Building

Prof.: N1, 905

Lab.: N1, 921

Admin.: N1, 904

Email

Professor Joyce Jiyoung Whang

jjwhang@kaist.ac.kr

Tel

Prof.: 042-350-3584

Lab.: 042-350-7784

Admin.: 042-350-7884