Jeongeun Park

Jungeun Kim

Taewook Kim

Joonbum Leem

Yujin Baek

Gye Eun Jeong

ChangHyun Won

BaRom Kang

Jihyun Jang

Hyun Jun Park

Siwoon Lee

Dongyup Shin

Jinmo Gu

Jisang Yoon

Donguk Yang

Youngjun Kim

Woongki Lee

Youngjin Kim

Sujeong Hwang

Sangrok Lee

Minchae Kim

Hyukjae Kwon

Jeongmin Yu

Jeanho Kim

Jinnyeong Heo

HyeongWoo Jeon

Welcome to MLCF Lab. We are looking for highly motivated postdocs, Ph.D, and M.S. students who are interested in working in the area of Deep Learning. Multimodal Learning and Computational Finance (MLCF) Lab focuses on research and development of artificial intelligence technologies, especially in the areas of multimodal learning and computational finance. Multimodal learning involves processing and understanding information from multiple modalities such as text, image, audio, and video. Computational finance applies computational methods and artificial intelligence techniques to solve complex problems in finance, such as algorithmic trading, risk management, and fraud detection. Our lab aims to contribute to both academic and industrial fields by developing innovative solutions that combine these two cutting-edge areas. Our core research interests include Machine Learning, Data Mining, AIX (딥러닝기반 융복합연구), Robot Learning, Multi-modal Deep Learning, Financial Artificial Intelligence, Human-Computer Interaction, Stochastic Processes, and Probability Theory. Recent research topics also cover Artificial Intelligence for Good, Deep Learning/Deep Reinforcement Learning in Finance, Multi-modal Sign Language Translation, Deep Learning/Natural Language Processing in Medicine, Automated Machine Learning (AutoML), Explainable Deep Neural networks, Multi-modality Fusion Architecture Search, Fast and Accurate Object Detection, Deep Reinforcement learning based Energy Consumption Optimization, Deep learning in Autonomous Driving, Deep learning in Civil Engineering and Construction, Deep Learning for Gesture Recognition, and Fast Deep Neural Networks. Students interested in applying to Yonsei University Graduate School of Information MLCF Lab should contact via email with their transcript and resume. The lab selects students through a lab test. Postdocs, Ph.D, and M.S. students interested in Deep Learning are encouraged to apply by sending an email with their curriculum vitae and transcript. The lab is affiliated with Yonsei University, Graduate School of Information, Department of Artificial Intelligence. For inquiries, the lab can be reached at +82-2-2123-4194. The page also includes a detailed 'Recent Activities and News' section covering awards, paper acceptances, research projects, industry collaborations, and invited talks from 2015 to 2026.

다중 모달 학습 및 전산 금융(MLCF) 연구실은 인공지능 기술, 특히 다중 모달 학습 및 전산 금융 분야의 연구 개발에 중점을 둡니다. 다중 모달 학습은 텍스트, 이미지, 오디오, 비디오와 같은 여러 모달리티의 정보를 처리하고 이해하는 것을 포함합니다. 전산 금융은 알고리즘 거래, 위험 관리, 사기 탐지와 같은 금융 분야의 복잡한 문제를 해결하기 위해 전산 방법과 인공지능 기술을 적용합니다. 저희 연구실은 이 두 가지 최첨단 분야를 결합한 혁신적인 솔루션을 개발하여 학술 및 산업 분야 모두에 기여하는 것을 목표로 합니다.

Standardized outcomes reporting in metabolic and bariatric surgery

Pragmatic solutions to reduce the global burden of stroke: a World Stroke Organization–Lancet Neurology Commission

Clinical practice guidelines for the perioperative nutrition, metabolic, and nonsurgical support of patients undergoing bariatric procedures – 2019 update: cosponsored by American Association of Clinical Endocrinologists/American College of Endocrinology, The Obesity Society, American Society for Metabolic &amp; Bariatric Surgery, Obesity Medicine Association, and American Society of Anesthesiologists

Progesterone Action in Endometrial Cancer, Endometriosis, Uterine Fibroids, and Breast Cancer

Clinical Practice Guidelines For The Perioperative Nutrition, Metabolic, and Nonsurgical Support of Patients Undergoing Bariatric Procedures – 2019 Update: Cosponsored By American Association of Clinical Endocrinologists/American College of Endocrinology, The Obesity Society, American Society For Metabolic &amp; Bariatric Surgery, Obesity Medicine Association, and American Society of Anesthesiologists

A microfluidic culture model of the human reproductive tract and 28-day menstrual cycle

Progesterone resistance in endometriosis: Link to failure to metabolize estradiol

Clinical Practice Guidelines for the Perioperative Nutrition, Metabolic, and Nonsurgical Support of Patients Undergoing Bariatric Procedures – 2019 Update: Cosponsored by American Association of Clinical Endocrinologists/American College of Endocrinology, The Obesity Society, American Society for Metabolic and Bariatric Surgery, Obesity Medicine Association, and American Society of Anesthesiologists

Endometrial receptivity in the eutopic endometrium of women with endometriosis: it is affected, and let me show you why

Standardized Outcomes Reporting in Metabolic and Bariatric Surgery

ASMBS position statement on prevention, detection, and treatment of gastrointestinal leak after gastric bypass and sleeve gastrectomy, including the roles of imaging, surgical exploration, and nonoperative management

Estrogen Receptor-β, Estrogen Receptor-α, and Progesterone Resistance in Endometriosis

Transcriptional Cross Talk between the Forkhead Transcription Factor Forkhead Box O1A and the Progesterone Receptor Coordinates Cell Cycle Regulation and Differentiation in Human Endometrial Stromal Cells

Altered expression of HOXA10 in endometriosis: potential role in decidualization

KCC2 rescues functional deficits in human neurons derived from patients with Rett syndrome

Role of Progesterone in Endometrial Cancer

The role of progesterone signaling in the pathogenesis of uterine leiomyoma

Paracrine activation of WNT/β-catenin pathway in uterine leiomyoma stem cells promotes tumor growth

Increased Activation of the PI3K/AKT Pathway Compromises Decidualization of Stromal Cells from Endometriosis

Crowdsourcing HIV Test Promotion Videos: A Noninferiority Randomized Controlled Trial in China

Large Language Models for Financial Time Series Forecasting: A Survey

Multi-modal Co-learning of Stock Price Movement Prediction and Causal Relation Mining

Multi-task Learning for Financial Risk Prediction with Transformer Encoder

Learning Multi-modal Representations for Fake News Detection on Social Media

ESGCN: Edge Squeeze Attention Graph Convolutional Network for Traffic Flow Forecasting

TiVaT: A Transformer with a Single Unified Mechanism for Capturing Asynchronous Dependencies in Multivariate Time Series Forecasting

Towards Temporal Fusion Beyond the Field of View for Camera-based Semantic Scene Completion

Dynamic Factor-Informed Reinforcement Learning for Enhancing Portfolio Optimization

MVFormer: Diversifying Feature Normalization and Token Mixing for Efficient Vision Transformers

Hierarchical Multi-modal Fusion Architecture Search for Stock Market Forecasting

Leveraging the Power of MLLMs for Gloss-Free Sign Language Translation

Multi-View Slot Attention Using Paraphrased Texts for Face Anti-Spoofing

HeLPNet: Facial Structure-aware Landmark Coordinate Regression with Heatmap-guided Local Patch Embedding

DiffSLT: Enhancing Diversity in Sign Language Translation via Diffusion Model

Data Augmentation with Flickering Backgrounds and Instances for Instance Segmentation

Three Cars Approaching within 100m! Enhancing Distant Geometry by Tri-Axis Voxel Scanning for Camera-based Semantic Scene Completion

Investigated Predictors of Construction Workers Ongoing Fatigue: Random Forest Approach

Looping In: Exploring Feedback Strategies to Motivate Human Engagement in Interactive Machine Learning

AI vs. Human-Generated Content and Accounts on Instagram: User Preferences, Evaluations, and Ethical Considerations

Human, do you think this painting is the work of a real artist?

Multi-label material and human risk factors recognition model for construction site safety management

Integrated recognition assistant framework based on deep learning for autonomous driving: Human-like restoring damaged road sign information

Do Topological Characteristics Help in Knowledge Distillation?

Image is All for Music Retrieval: Interactive Music Retrieval System Using Images with Mood and Theme Attributes

“Is Text-Based Music Search Enough to Satisfy Your Needs?” A New Way to Discover Music with Images

Nursing diagnoses as factors associated with delirium among intensive care unit patients with sepsis: A retrospective correlational study

Development of an HVAC system control method using weather forecasting data with deep reinforcement learning algorithms

CSLT-AK: Convolutional-embedded Transformer with an Action Tokenizer and Keypoint Emphasizer for Sign Language Translation

Decompose, Adjust, Compose: Effective Normalization by Playing with Frequency for Domain Generalization

Text mining-based four-step framework for smart speaker product improvement and sales planning

Deep Learning-Based Defect Detection Framework for Ultra High Resolution Images of Tunnels

Pro-attention: Efficient Probability Distribution Matching-based Attention through Feature Space Conversion

ADEL: Adaptive Distribution Effective-matching Method for Guiding Generators of GANs

“Do not deceive me anymore!” Interpretation through model design and visualization for Instagram counterfeit seller account detection

Ultra-lightweight face activation for dynamic vision sensor with convolutional filter-level fusion using facial landmarks

AutoDefect: Defect text classification in residential buildings using a multi-task channel attention network

Bounding-box Object Augmentation with Random Transformations for Automated Defect Detection in Residential Building façades

Convolutional Neural Network-Based Regression for Predicting the Chloride Ion Diffusion Coefficient of Concrete

Risk factor recognition for automatic safety management in construction sites using fast deep convolutional neural networks

Stock market forecasting using a multi-task approach integrating long short-term memory and the random forest framework

Automatic Classification of Thyroid Findings Using Static and Contextualized Ensemble Natural Language Processing Systems: Development Study

Predicting Success of Outbound Telemarketing in Insurance Policy Loans Using an Explainable Multiple-Filter Convolutional Neural Network

Deep-learning-based Automated Terminology Mapping in OMOP-CDM

Accelerating multi-class defect detection of building façades using knowledge distillation of DCNN-based model

Automated defect classification in the maintenance phase using a channel attention-based convolutional neural network model of natural language processing

DeepOption: A Novel Option Pricing Framework Based on Deep Learning with Fused Distilled Data from Multiple Parametric Methods

Defect-Detection Model for Underground Parking Lots Using Image Object-Detection Method

Automatic Concrete Damage Recognition Using Multi-Level Attention Convolutional Neural Network

MultiDefectNet: Multi-class Defect Detection of Building Façade based on Deep Convolutional Neural Network

Action-Specialized Expert Ensemble Trading System with Extended Discrete Action Space Using Deep Reinforcement Learning

Stock Market Forecasting with Super-High Dimensional Time-Series Data Using ConvLSTM, Trend Sampling, and Specialized Data Augmentation

Predicting Concrete Compressive Strength using Deep Convolutional Neural Network based on Image Characteristics

Multimodal Learning and Computational Finance Lab (MLCF)

교수님 소개

김하영

연구실 소개

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

TiVaT: A Transformer with a Single Unified Mechanism for Capturing Asynchronous Dependencies in Multivariate Time Series Forecasting

Towards Temporal Fusion Beyond the Field of View for Camera-based Semantic Scene Completion

Dynamic Factor-Informed Reinforcement Learning for Enhancing Portfolio Optimization

연구실 보유 특허

대학별 입시끈

우리 연구실 모집

교수님 소개

김하영

연구실 키워드

알럼나이가 간 회사

연구실 지원 방법

대우 조건

연도별 논문 인용수

저널 & 학회 논문 출판 수

연구실 논문 목록

TiVaT: A Transformer with a Single Unified Mechanism for Capturing Asynchronous Dependencies in Multivariate Time Series Forecasting

Towards Temporal Fusion Beyond the Field of View for Camera-based Semantic Scene Completion

Dynamic Factor-Informed Reinforcement Learning for Enhancing Portfolio Optimization

연구실 보유 특허

최근 3년간 연구실적 높은 연구실

대학별 입시끈

우리 연구실 모집