Dong-Hyuk Seo

Taeho Kim

Taeri Kim

Myung-Hwan Jang

Hong-Kyun Bae

Junho Song

Jiwon Hong

Yoonsuk Kang

Yunyong Ko

Yeon-Chang Lee

Dong-Kyu Chae

Irfan Ali

Yong-Yeon Jo

Masoud Hamedani

Won-Seok Hwang

Hyun-Kyo Oh

Jiwoon Ha

Duck-Ho Bae

Sang-Chul Lee

Min-Hee Jang

Seok-Ho Yoon

Seung-Hwan Lim

Seongun Cho

Hyunwoo Lee

Jeongseok Oh

Seongju Pyo

Chaehee Jeon

Bohye Han

Junpyo Kim

Hojung Shin

Minkyeong Shin

Hyomin Shin

Sohee Ban

Songkyung Yu

DaEun Lee

Juhyun Jeon

Jaehwan Lim

UiJong Kim

Ikhyeon Jo

Hongil Kim

Jin-Su Ryu

Juwon Yu

Haeri Jang

Hyeongjun Jang

Jiho Heo

Yebeen Kim

JaeHyun Lee

Yungi Kim

Jiyeon Kim

Soeun Han

Hyun-Soung You

Hyunsik Yoo

Eujeanne Kim

Jae-Seo Yu

Jihoo Kim

The Big Data Science Lab at Hanyang University Graduate School provides an enthusiastic research atmosphere and an excellent research environment. Furthermore, it offers various research funding programs through participation in government projects such as the Ministry of Education's BK21, MSIT's SW Star Lab Project, MSIT's AI Graduate School Support Project, Ministry of Information and Communication's IT Research Center, National Research Foundation's Leap Research Project (formerly National Designated Research Lab), and Research Foundation's Next-Generation Computing Project, as well as various industry projects with Samsung Electronics Co., Ltd., Hyundai Motor Company, Naver Corp., SKT Co., Ltd., KT Co., Ltd., NHN Co., Ltd., Mando Co., Ltd., and others. If you are interested in researching with the Big Data Science Lab, please contact us at the number below.

한양대학교 대학원 빅데이터 사이언스 연구실에서는 열정적인 연구 분위기와 좋은 연구 환경을 제공하고 있습니다.
또한, 교육부 BK21, 과기정통부 SW스타랩사업, 과기정통부 인공지능대학원 지원사업, 정보통신부 IT연구센터, 한국연구재단 도약연구사업(구: 국가지정연구실), 연구재단 차세대컴퓨팅사업 등의 정부사업과 삼성전자(주), 현대자동차(주), 네이버(주), SKT(주), KT(주), NHN(주), 만도(주) 등 다양한 산업체 과제 참여를 통한 다양한 연구비 지원 프로그램을 제공하고 있습니다.
빅데이터 사이언스 연구실과 함께 연구하는데 관심이 있으신 분들은 아래 연락처로 연락주시기 바랍니다.

서동혁/김세인’s paper accepted in ACM WWW

김민정/손지원/이연창’s paper accepted in ACM WWW

김태호/김준표’s paper accepted in ACM WSDM

강윤석’s paper accepted in IEEE Access

장명환/박정민’s paper accepted in ACM KDD

장명환/신민경’s paper accepted in ACM CIKM

류성은/고윤용’s paper accepted in ACM CIKM

고윤용/이다은/유송경’s paper accepted in ACM CIKM

마수드/오정석/조성운’s paper accepted in ACM KDD

김태리/반소희’s paper accepted in ACM KDD

정동호/김태리’s paper accepted in ACM SIGIR

손지원’s paper accepted in ACM SIGIR

장명환/조익현’s paper accepted in ACM WWW

유송경/이다은/고윤용’s paper accepted in ACM WWW

서동혁/신효민’s paper accepted in ACM WWW

배홍균/장해리’s paper accepted in ACM WWW

고윤용/류성은’s paper accepted in ACM WWW

류성은’s paper accepted in ACM SAC

고윤용’s paper accepted in IEEE Transactions on Knowledge and Data Engineering

이연창/신호중’s paper accepted in AAAI

김태호/장형준/유주원’s paper accepted in AAAI

김태리/허지호’s paper accepted in AAAI

이연창/이재현’s paper accepted in ACM KDD

손지원’s paper accepted in ACM KDD

이연창’s paper accepted in ACM CIKM

서동혁/임재환’s paper accepted in ACM CIKM

서동혁/손지원/김남혁’s paper accepted in ACM CIKM

김민정/이연창’s paper accepted in ACM CIKM

김민정/이연창/강윤석’s paper accepted in ACM TKDD

이연창’s paper accepted in ACM Computing Surveys

안지원/배홍균’s paper accepted in ACM WWW

박정민/장명환/배덕호’s paper accepted in ACM WWW

박정민/장명환’s paper accepted in ACM WWW

배홍균/김예빈’s paper accepted in ACM WWW

강윤석’s paper accepted in ACM WWW

고윤용/류성은’s paper accepted in ACM CSCW

손지원/서동혁/송준호’s paper accepted in ACM SAC

김태리/허지호/김홍일’s paper accepted in AAAI

SCOUT: Structure-Aware Aspect and Anchor-Count Selection for Positional Attribute Augmentation

Retracing and Restoring: Chronological Context Preservation for Effective Dynamic Recommendation

Leveraging Retrieval-Augmented Language Models for Accurate Item/Feature Selection in Conversational Recommender Systems

PANther: Party-specific Attention-based Networks for Political Perspective Detection

Accelerating Storage-based Training for Graph Neural Networks

RealGraphGPUWeb: A Convenient and Efficient GPU-Based Graph Analysis Platform on the Web

Learning Short-Term and Long-Term Patterns of High-Order Dynamics in Real-World Networks

Is This News Still Interesting to You?: Lifetime-aware Interest Matching for News Recommendation

An Efficient PIM-Based Graph Engine on a Single Machine

STARLINE: Contrastive Learning with Modality-Aware Graph Refinement for Effective Multimedia Recommendation

SIGEM: A Simple yet Effective Similarity based Graph Embedding Method

CATER: A Cluster-Based Alternative-Term Recommendation Framework for Large-ScaleWeb Search at NAVER

CAPER: Enhancing Career Trajectory Prediction using Temporal Knowledge Graph and Ternary Relationship

Rating-Aware Homogeneous Review Graphs and User Likes/Dislikes Differentiation for Effective Recommendations

MELON: Learning Multi-Aspect Modality Preferences for Accurate Multimedia Recommendation

COHESION: Composite Graph Convolutional Network with Dual-Stage Fusion for Multimodal Recommendation

RealGraphOF: A High-Performance Graph Engine for Very Large Graph Analysis

Ranking Items by the Current-Preferences and Profits: A List-wise Learning-to-Rank Approach to Profit Maximization

HyGEN: Regularizing Negative Hyperedge Generation for Accurate Hyperedge Prediction

Exploring Search Volumes of Terms in Web Portals for Accurate Event-Aware Traffic Prediction

CROWN: A Novel Approach to Comprehending Users’ Preferences for Accurate Personalized News Recommendation

A Novel Traffic Flow Prediction Model based on a Direct Spatio-Temporal Graph

HI-DR: Exploiting Health Status-Aware Attention and an EHR Graph+ for Effective Medication Recommendation

ESPRESSO: An Effective Approach to Passage Retrieval for High-Quality Conversational Recommender Systems

Disentangling, Amplifying, and Debiasing: Learning Disentangled Representations for Fair Graph Neural Networks

RealGraph GPU++ : A GPU-Based Graph Engine with Direct Storage-to-DM IO

HearHere: Mitigating Echo Chambers In News Consumption through an AI-based Web System

PolarDSN: An Inductive Approach to Learning the Evolution of Network Polarization in Dynamic Signed Networks

Leveraging Trustworthy Node Attributes for Effective Network Alignment

Towards Fair Graph Anomaly Detection:Problem, Benchmark Datasets, and Evaluation

Empowering Traffic Speed Prediction with Auxiliary Feature-Aided Dependency Learning

RealGraphGPUWeb: A Convenient and Efficient GPU-based Graph Analysis Platform on the Web

RealGraphGPU++: A High-Performance GPU-based Graph Engine with Direct Storage-to-DM IO

Item-Ranking Promotion in Recommender Systems

Is the 'Impression Log' Beneficial to Evaluating News Recommender Systems? No, it is Not!

Negative Sampling in Next-POI Recommendations: Observation, Approach, and Evaluation

Low Mileage, High Fidelity: Evaluating Hypergraph Expansion Methods by Quantifying the Information Loss

MONET: Modality-Embracing Graph Convolutional Network and Target-Aware Attention for Multimedia Recommendation

VITA: 'Carefully Chosen and Weighted Less' Is Better in Medication Recommendation

Random-walk-based or Similarity-based Methods, Which is Better for Directed Graph Embedding?

SIMD Optimization for Improving the Performance of a CPU-Based Graph Engine

IO Optimization Strategies for a GPU-Based Graph Engine with HighPerformance Storage

SAGE: A Storage-Based Approach for Scalable and Efficient Sparse Generalized Matrix-Matrix Multiplication

ELTRA: An Embedding Method based on Learning-to-Rank to Preserve Asymmetric Information in Directed Graphs

LATTE: A Framework for Learning Item-features to Make a Domain-Expert for Effective Conversational Recommendation

TrustSGCN: Learning Trustworthiness on Edge Signs for Effective Signed Graph Convolutional Networks

RealGraph+: A High-Performance Single-Machine-Based Graph Engine that Utilizes IO Bandwidth Effectively

KHAN: Knowledge-Aware Hierarchical Attention Networks for Accurate Political Stance Prediction

Is the Impression Log Beneficial to Effective Model Training in News Recommender Systems? No, It’s NOT

GELTOR A Graph Embedding Method based on Listwise Learning to Rank

C-Affinity: A Novel Similarity Measure for Effective Data Clustering

Disentangling Degree-related Biases and Interest for Out-of-Distribution Generalized Directed Network Embedding

Orchestrating Large-Scale SpGEMMs using Dynamic Block Distribution and Data Transfer Minimization on Heterogeneous Systems

A Competition-Aware Approach to Accurate TV Show Recommendation

LANCER: A Lifetime-Aware News Recommender System

A GPU-Based Graph Engine for Large-Scale Network Analysis

손지원’s international patent application

손지원/한보혜’s patent application

손지원/권용진’s patent application

김태리/최제범/신호중’s patent application

배홍균/이현우’s patent application

표성주/이재현’s patent application

정소빈’s patent application

서동혁/김태리/김세인’s patent application

김태리/박혁주’s patent application

김태호/안병수’s patent application

김민정/손지원’s patent application

오정석/조성운’s patent application

정동호/김태리’s patent application

류성은’s patent application

서동혁/신효민’s patent application

김태호/김준표’s patent application

배홍균/김예빈’s international patent application

김태리/허지호’s international patent application

서동혁/손지원’s patent application

이재현/배홍균’s patent application

서동혁/임재환’s patent application

김민정’s patent application

김태호/유주원’s patent application

김태호/장형준’s patent application

장해리/배홍균’s patent application

김예빈/배홍균’s patent application

허지호/김태리’s patent application

Sang-Wook Kim

Visitor (invited by Prof. Gio Wiederhold)

Postdoctoral Researcher (invited by Dr. Philip Yu)

Visiting Professor (invited by Prof. Christos Faloutsos)

Professor

Research Associate Professor

Postdoc

Jeewon Ahn

Ph.D. Candidate

Jiwon Son

Dongho Jeong

Jeong-Min Park

Seongeun Ryu

MinJeong Kim

Sobin Jung

Byeongsoo Ahn

Jeongwon Seo

Taekwon Chung

Sein Kim

Hanseok Oh

Dongmin Lee

Nammin Kim

JungHyun Lee

Big Data Science Laboratory - Data Science Lab.

교수님 소개

김상욱

연구실 소개

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

서동혁/김세인’s paper accepted in ACM WWW

김민정/손지원/이연창’s paper accepted in ACM WWW

김태호/김준표’s paper accepted in ACM WSDM

연구실 보유 특허

대학별 입시끈

우리 연구실 모집

교수님 소개

김상욱

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

서동혁/김세인’s paper accepted in ACM WWW

김민정/손지원/이연창’s paper accepted in ACM WWW

김태호/김준표’s paper accepted in ACM WSDM

연구실 보유 특허

최근 3년간 연구실적 높은 연구실

대학별 입시끈

우리 연구실 모집