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DMIS Lab, Korea University
 * Home
 * Jaewoo Kang (P.I.)
 * Publications
 * 
   Research
    * Biomedical AI
    * NLP
    * Graph & ML

 * People

DMIS Lab, Korea University
 * Home
   
 * Jaewoo Kang (P.I.)
   
 * Publications
   
 * Research
   
   
    * Biomedical AI
    * NLP
    * Graph & ML

 * People
   
 * More
   
    * Home
    * Jaewoo Kang (P.I.)
    * Publications
    * 
      Research
       * Biomedical AI
       * NLP
       * Graph & ML
   
    * People






DMIS LAB


DATA MINING AND INFORMATION SYSTEMS LAB

PI: Prof. Jaewoo Kang, Dept. of Computer Science and Engineering, Korea Univ.

(고려대학교 컴퓨터학과 강재우교수 연구실)


ABOUT

Data science has advanced to the point where it is changing our world. It is now
the center of exploring and uncovering knowledge in different domains and acts
as a bridge to connect them. With ever growing amount of data and opportunity to
explore, the Data Mining and Information Systems (DMIS) lab aims to drive the
data science revolution.

The main focus of DMIS Lab is to utilize and leverage AI and machine learning
(ML) to solve problems in bioinformatics, drug discovery, and biomedical text
mining. In order to diversify and strengthen its arsenal, DMIS Lab also conducts
research in other areas such as natural language processing (NLP) and graph ML
in order to uncover more-refined techniques to carry out its larger mission.
Aside from conducting research, DMIS Lab also participates in various
international challenges and competitions in order to contribute to the communal
effort to tackle unmet needs in the field of biomedine, such as the DREAM
Challenges and the BioASQ Challenges.



NEWS

 * Oct. 2024: Dr. Hyunjae Kim's paper, Augmenting Biomedical Named Entity
   Recognition with General-domain Resources, is published in Journal of
   Biomedical Informatics (JBI), one of the top journals in Bioinformatics.
    This paper is a result of our fruitful collaboration with University of
   Liverpool, Yale University, and NIH. Congratulations!



 * Oct. 2024: Kiwoong Yoo's paper, TurboHopp: Accelerated Molecule Scaffold
   Hopping with Consistency Models, was accepted to NeurIPS 2024, one of the top
   conferences in Machine Learning.  Congratulations!



 * Sep. 2024: Chanwoong Yoon's paper, CompAct: Compressing Retrieved Documents
   Actively for Question Answering, was accepted to EMNLP 2024 (Miami), one of
   the top conferences in NLP. Congratulations!




 * Sep. 2024: Congratulations to Dr. Mogan Gim on his appointment as a
   tenure-track Assistant Professor in the Department of Biomedical Engineering
   at Hankuk University of Foreign Studies! 




 * Sep. 2024: Congratulations to Dr. Bumsoo Kim on his appointment as a
   tenure-track Assistant Professor in the School of Computer Science and
   Engineering at Chung-Ang University!




 * Jul. 2024: Donghee's and Jinkyu's paper, DeepClair: Utilizing Market
   Forecasts for Effective Portfolio Selection & Heedou's paper, LAPIS: Language
   Model-Augmented Police Investigation System were both accepted to the
   Conference on Information and Knowledge Management (CIKM), which is scheduled
   as an in-person conference taking place in Boise, Idaho, USA on October
   21-25, 2024. The former is based on collaboration with Imperial College
   London and Shinhan Bank, while the latter is with also Imperial College
   London and Korean National Police Agency. Congratulations for the authors of
   these two accepted papers!



 * Jun. 2024: Mogan's and Jueon's paper, MolPLA: a molecular pretraining
   framework for learning cores, R-groups and their linker joints &  Minbyul's
   paper, Improving medical reasoning through retrieval and self-reflection with
   retrieval-augmented large language models were published in Bioinformatics
   (OUP) and will be both orally presented in the upcoming ISMB conference in
   Montreal, Canada. The former is based on collaboration with Aigen Sciences
   while the latter is with Kyunghee University. Congratulations for the authors
   of these two published papers!



 * Apr. 2024:  🎉 Introducing Meerkat-7B: The First 7B Model to Pass USMLE! 🥳

There's a noticeable difference in performance between commercial large LMs and
open-source small LMs in the medical domain. While GPT-4 scored an impressive
90% accuracy on USMLE-style questions, the previous best 7B model managed only
52%, falling significantly below the USMLE passing threshold of 60%.

Our new medical LM, Meerkat-7B, achieved a groundbreaking milestone by
surpassing the 60% passing threshold for the United States Medical Licensing
Examination (USMLE) for the first time among 7B-parameter models (with scores of
74.3% on the MedQA dataset and 71.4% on the USMLE sample test). Additionally,
our system outperformed GPT-3.5 (175B) by 13.1% across seven medical benchmarks,
indicating significant progress in open-source model development within the
medical field. (동아일보, 국민일보, AI타임스)

Congratulations to Dr. Hyunjae Kim and the Meerkat team on their remarkable
achievement!

- Paper: https://arxiv.org/abs/2404.00376

- Model: https://huggingface.co/dmis-lab/meerkat-7b-v1.0




 * Mar. 2024: Congratulations to Dr. Mujeen Sung on his appointment as a
   tenure-track Assistant Professor in the School of Computing at Kyung Hee
   University! 




 * Feb. 2024: Donghee Choi's paper, CookingSense: A Culinary Knowledgebase with
   Multidisciplinary Assertions, was accepted to LREC-COLING 2024, a notable
   international conference on computational linguistics resources. This feat is
   a result of our fruitful collaboration with Sony Research. Congratulations
   Donghee-san!



 * Jan. 2024: Ngoc-Quang Nguyen's paper, MulinforCPI: enhancing precision of
   compound–protein interaction prediction through novel perspectives on
   multi-level information integration, is published at Briefings in
   Bioinformatics, one of the top journal in Bioinformatics. Congratulations!



 * Jan. 2024: Hyunjae Kim's paper, Fine-tuning CLIP Text Encoders with Two-step
   Paraphrasing, is accepted to EACL 2024 (Findings of the ACL), one of the top
   conferences in NLP. Congratulations!



 * Oct. 2023: Two papers got accepted to EMNLP 2023 (Singapore), one of the top
   conferences in NLP. Congratulations!
   
   * Mujeen Sung's paper, Pre-training Intent-Aware Encoders for Zero- and
     Few-Shot Intent Classification, is accepted to EMNLP 2023.
   
   * Gangwoo Kim's paper, Tree of Clarifications: Answering Ambiguous Questions
     with Retrieval-Augmented Large Language Models, is accepted to EMNLP 2023.



 * Aug. 2023: We are celebrating over 4,000 citations to our BioBERT paper,
   which is both the first and most cited biomedical domain-specific
   transformer-based large language model. Congratulations to our team: Jinhyuk
   Lee (currently at Google DeepMind), Wonjin Yoon (Harvard Medical School),
   Donghyeon Kim (Hyundai Motors AI), Sunkyu Kim (AIGEN Sciences), and Chan Ho
   So (TmaxSoft)!




 * Jul. 2023: Our DMIS team (Gangwoo Kim, Hajung Kim, Chanhwi Kim, Mujeen Sung,
   Hyunjae Kim) achieved 1st place in RadSum23, the Multi-modal and
   Multi-anatomical Radiology Report Summarization Challenge. Congratulations!
   (인공지능신문, 이데일리)
   
   * We outperformed leading AI research groups, including Stanford University,
     Siemens, University College London, and The University of Texas at San
     Antonio.
   
   * DMIS led the multinational team effort, with researchers from Microsoft
     Research Asia, AIGEN Sciences, KAIST, and Beihang University participating.
   
   * The paper describing the winning model is available here.



 * Jul. 2023: Mogan's paper, ArkDTA: attention regularization guided by
   non-covalent interactions for explainable drug–target binding affinity
   prediction was published in Bioinformatics (OUP) and will be orally presented
   in the upcoming ISMB conference in Lyon, France . This work wouldn't have
   been completed without the supportive efforts of Junseok, Seungheun, Jueon,
   Chaeeun, Minjae and Sumin. Congratulations!



 * Jun. 2023: Congratulations to Dr. Buru Chang on the appointment as a
   tenure-track Assistant Professor in the Department of Artificial Intelligence
   at Sogang University! 




 * May. 2023: Minbyul's paper, Consistency Enhancement of Model Prediction on
   Document-level Named Entity Recognition will be published in Bioinformatics
   (OUP). Congratulations!



 * May. 2023: Two papers got accepted to ACL 2023 (Toronto, Canada), one of the
   top conferences in NLP. Congratulations!
   
   * Hyunjae Kim's paper, Automatic Creation of Named Entity Recognition
     Datasets by Querying Phrase Representations, is accepted to ACL 2023.
   
   * Mujeen Sung's paper, Optimizing Test-Time Query Representations for Dense
     Retrieval, is accepted to Findings of ACL 2023.



 * Apr. 2023: Donghee Choi's paper, KitchenScale: Learning to Predict Ingredient
   Quantities from Recipe Contexts will be published in Expert Systems with
   Applications, one the most recognized journals with an impact factor of
   8.665. This paper is based on collaborative work with Sony Research and
   Sejong University. Congratulations!



 * Jan. 2023: Congratulations to Dr. Seongjun Yun, who joined Amazon (Vancouver,
   BC) as an applied scientist. Dr. Yun joined the M5 team that builds large
   pretrained models to support machine learning applications at Amazon.
   Congratulations!




 * Jan. 2023: Mujeen Sung received the NAVER Ph.D Fellowship Award as he showed
   outstanding performance in his research area.



 * Nov. 2022: Ngoc-Quang Nguyen's paper, Perceiver CPI: A nested cross-attention
   network for compound-protein interaction prediction, will be published in
   Bioinformatics (OUP), one of the top journals in the field of bioinformatics.
   Congratulations!



 * Nov. 2022: LIQUID: A Framework for List Question Answering Dataset
   Generation, co-first authored by Seongyun Lee and Hyunjae Kim, was accepted
   to AAAI 2023, one of the top conferences in artificial intelligence.
   Congratulations!




 * Oct. 2022: Four papers got accepted to EMNLP 2022, one of the top conferences
   in NLP. Congratulations!
   
   * Hyunjae Kim's paper, Simple Questions Generate Named Entity Recognition
     Datasets, is accepted to EMNLP 2022.
   
   * Gangwoo Kim's paper, Generating Information-Seeking Conversations from
     Unlabeled Documents,  is accepted to EMNLP 2022.
   
   * Gangwoo Kim's paper (co-authored), Saving Dense Retriever from Shortcut
     Dependency in Conversational Search,  is accepted to EMNLP 2022.
   
   * Wonjin Yoon's paper, Biomedical NER for the Enterprise with Distillated
     BERN2 and the Kazu Framework,  is accepted to EMNLP 2022 (Industry Track).



 * Sep. 2022: WonJin Yoon received an Academic Award, "Standigm Paper Award
   2022" (스탠다임 우수논문상) from the Korean Society for Bioinformatics (한국생명정보학회) with
   the paper entitled Sequence Tagging for Biomedical Extractive Question
   Answering (Bioinformatics 2022). Congratulations!



 * Sep. 2022: BERN2: an advanced neural biomedical named entity recognition and
   normalization tool, co-first authored by Mujeen Sung and Minbyul Jeong, will
   be published in Bioinformatics (OUP). Congratulations! [Demo]



 * Aug. 2022: RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe
   Completion using Cascaded Set Transformer co-first authored by Mogan Gim and
   Donghee Choi, got accepted at CIKM 2022, one of the top-tier conforences in
   Information and Knowledge Management domain. This paper is a fruitful result
   of collaborative work between our DMIS lab, Professor Park (FNAI Lab, Sejong
   University) and Sony AI (Tokyo, Japan) which aims to promote creative cooking
   in food industry. 




 * Jul. 2022: Congratulations to Dr. Jinhyuk Lee, who joined Google (Mountain
   View, CA) as a research scientist. Dr. Lee joined the NLP team at Google
   Research that created BERT and Transformer, working alongside Jeff Dean.
   Congratulations!





 * Jun. 2022: Sequence Tagging for Biomedical Extractive Question Answering,
   co-authored by WonJin Yoon and researchers at AstraZeneca UK and Sweden, as
   one of the results of research collaboration, will be published in
   Bioinformatics (OUP). Congratulations!



 * Apr. 2022: DyGRAIN: An Incremental Learning Framework for Dynamic Graphs,
   co-authored by Seoyoon Kim and Seongjun Yun, will be presented at IJCAI 2022.
   Congratulations!




 * Apr. 2022: Congratulations, Jungsoo Park, whose papers got accepted at ACL
   and NAACL!
   
   * Consistency Training with Virtual Adversarial Discrete Perturbation. NAACL
     2022 
   
   * FAVIQ: FAct Verification from Information-seeking Questions. ACL 2022




 * Apr. 2022: MSTR: Multi-Scale Transformer for End-to-End Human-Object
   Interaction Detection, co-authored by Bumsoo Kim and Junhyun Lee, got
   accepted at CVPR 2022. Congratulations!




 * Feb. 2022: Congratulations to Dr. Minji Jeon on the appointment of as a
   tenure-track Assistant Professor in the Department of Medicine at Korea
   University Medical School.




 * Feb. 2022: Congratulations to Dr. Donghyeon Park on the appointment as a
   tenure-track Assistant Professor in the Department of Data Science at Sejong
   University.




 * Dec. 2021: Congratulations to Dr. Kyubum Lee on joining Amgen Inc. (CA, USA)
   as Principal Data Scientist. Dr. Lee will work on data-driven clinical trial
   design and execution using ML and NLP.





 * Dec. 2021: WonJin Yoon et al.'s paper, KU-DMIS at BioASQ 9: Data-centric and
   model-centric approaches for biomedical question answering, is selected as
   the best paper in the BioASQ Lab at CLEF2021, one of the most highly valued
   venues in Biomedical NLP. Congratulations!



 * Nov. 2021: Seongjun Yun's paper, Neo-GNNs: Neighborhood Overlap-aware Graph
   Neural Networks for Link Prediction, was accepted to NeurIPS 2021, one of the
   top conferences in Machine Learning. Congratulations!




 * Nov. 2021: DMIS team scored top performance at 2 challenge tracks held by the
   BioCreative VII workshop. (인공지능신문, 뉴시스) 
   
   * Won third place at the relation extraction task: DrugProt: Text mining
     drug/chemical-protein interactions (Track 1). 🥉
     Paper: Using Knowledge Base to Refine Data Augmentation for Biomedical
     Relation Extraction (Wonjin Yoon, Sean Yi, Richard Jackson (External
     affiliation), Hyunjae Kim, Sunkyu Kim, Jaewoo Kang)
   
   * Won first place at the named entity recognition task: NLM-Chem Track: Full
     text Chemical Identification and Indexing in PubMed articles (Track 2).  🥇
     Paper: Improving Tagging Consistency and Entity Coverage for Chemical
     Identification in Full-text Articles (Hyunjae Kim, Mujeen Sung, Wonjin
     Yoon, Sungjoon Park, Jaewoo Kang)
   
   * Workshop information: https://biocreative.bioinformatics.udel.edu/news/ 





 * Aug. 2021: Two papers got accepted to EMNLP 2021, one of the top conferences
   in NLP. Congratulations!
   
   * Dr. Jinhyuk Lee's paper, Phrase Retrieval Learns Passage Retrieval, Too, is
     accepted to EMNLP 2021.
   
   * Mujeen Sung's paper, Can Language Models be Biomedical Knowledge Bases?, 
     is accepted to EMNLP 2021.



 * May. 2021: Two papers got accepted to ACL-IJCNLP 2021, one of the top
   conferences in NLP. Congratulations!
   
   * Dr. Jinhyuk Lee's paper, Learning Dense Representations of Phrases at
     Scale, is accepted to ACL-IJCNLP 2021. (한국경제, IT조선)
   
   * Gangwoo Kim's paper, Learn to Resolve Conversational Dependency: A
     Consistency Training Framework for Conversational Question Answering,  is
     accepted to ACL-IJCNLP 2021.



 * Apr. 2021: Gwanghoon Jang's paper, Predicting mechanism of action of novel
   compounds using compound structure and transcriptomic signature co-embedding,
   co-advised by Dr. Sungjoon Park and Prof. Jaewoo Kang, was accepted to
   ISMB/ECCB 2021. Congratulations! 



 * Mar. 2021: Bumsoo Kim's paper, HOTR: End-to-End Human-Object Interaction
   Detection with Transformers, was accepted to CVPR 2021 (Virtual, June 19-25),
   one of the most top-tier conferences for computer vision, for oral
   presentation!



 * Feb. 2021: Mujeen Sung received the 2020 KU Graduate School Achievement Award
   as he showed outstanding performance in his research area. 



 * Oct. 2020: Donghyeon Park's paper, FlavorGraph: A large-scale food-chemical
   graph for generating food representations and recommending food pairings, was
   accepted to Scientific Reports, an online peer-reviewed open access
   scientific mega journal published by Nature Research.



 * Oct. 2020: Minbyul Jeong, Mujeen Sung, Gangwoo Kim, Donghyeon Kim, Jaehyo
   Yoo, Wonjin Yoon and Jaewoo Kang won first place in both question answering
   and summarization of the BioASQ 8B (Phase B) Task B Challenge! 
   
   * 고려대 컴퓨터학과 연구팀이 의학, 생물학 질문에 답하는 인공지능 시스템 경진 국제대회인 BioASQ 대회에서 미국 캘리포니아대학
     샌디에고(UCSD), 매사추세츠대학 (UMass), 중국 푸단대학 (Fudan Univ), 일본 도쿄대학(University of
     Tokyo)를 제치고 2년 연속 우승했다. (이데일리)
   
   * 사람이 읽기에 자연스러운 문장으로 질문에 대한 답을 할 수 있는 인공지능 시스템이라는 점에서 앞으로 임상적으로 유의한 의사결정 지원
     도구를 개발하는데 활용될 수 있을 것으로 기대된다. 




 * Sep. 2020: Jungsoo Park's paper, Adversarial Subword Regularization for
   Robust Neural Machine Translation, was accepted to Findings of ACL: EMNLP
   2020, an anthology journal of ACL which is one of the top-tier conferences
   for computational linguistics.



 * Sep. 2020: Miyoung Ko's paper, Look at the First Sentence: Position Bias in
   Question Answering, was accepted to EMNLP 2020, one of the best renowned
   conferences for NLP-related publications!



 * Sep. 2020: Recently, BioBERT: a pre-trained biomedical language
   representation for biomedical text mining co-first authored by Dr. Jinhyuk
   Lee and Wonjin Yoon has been ranked as the most read papers in Bioinformatics
   which is one of the top-tier journals in the domain. 

Also, BioBERT was included in the Best Papers for the Natural Language
Processing Section of the 2020 IMIA (International Medical Informatics
Association) Yearbook (link). Congratulations once again to the authors for this
grand achievement!




 * Jul. 2020: Enhancing the interpretability of transcription factor binding
   site prediction using attention mechanism, co-first authored by Sungjoon
   Park, Yookyung Koh, and Hwisang Jeon, was accepted to Scientific Reports.
   Congratulations!



 * Apr. 2020: MAPS: Multi-Agent reinforcement learning-based Portfolio
   management System, co-first authored by Jinho Lee and Raehyun Kim, is
   accepted to IJCAI 2020, one of the top conferences for general AI. 
   
   *  MAPS is an hedge fund like portfolio management system trained with
     cooperative multi-agent reinforcement learning. 
   
   * It is inspired by the fact that hedge fund's entire portfolio is manged by
     multiple investors, working together to maximize risk-adjusted return. 



 * Apr. 2020: Congratulations to Sunkyu Kim for publication to Cell Systems!
   
   * Sunkyu Kim's team won 1st place in the NCI-CPTAC DREAM Proteogenomics
     Challenge in 2017 (outperforming UCLA(3rd), Stanford(13th)).
   
   * Assessment of the Limits of Predictability of Protein and Phosphorylation
     Levels in Cancer is a paper for the DREAM challenge and is worked with
     Heidelberg University, Icahn School of Medicine and New York University. 



 * Apr. 2020: Sunkyu Kim's paper, Improved survival analysis by learning shared
   genomic information from pan-cancer data, was accepted to ISMB 2020, top
   conference in Bioinformatics.



 * Two papers got accepted to ACL 2020, one of the top conferences in NLP.
   
   * Dr. Jinhyuk Lee's paper, Contextualized Sparse Representations for
     Real-Time Open-Domain Question Answering, is accepted to ACL 2020.
   
   * Mujeen Sung's paper, Biomedical Entity Representations with Synonym
     Marginalization,  is accepted to ACL 2020.



 * Jan. 2020: Wonjin Yoon received the NAVER Ph.D Fellowship Award as he showed
   outstanding performance in his research area.

 * Nov. 2019: Congratulations! Our DMIS team (Sungjoon Park, Minji Jeon, Sunkyu
   Kim, Junhyun Lee, Seongjun Yun, Bumsoo Kim, Buru Chang) has been selected as
   the top performers in the IDG-DREAM Drug-Kinase Binding Prediction Challenge.
   As one of the best performers, we presented our model at the RSG with DREAM
   Conference, NY in November.   (Link)
   
   * 연구팀은 11월 뉴욕에서 개최된 RSG with Dream Conference에서 우승자 자격으로 초청되어 AI기반
     버추얼약물스크리닝모델을 발표했다. (매일경제, 한국대학신문, 연합뉴스)
   
   * 드림 챌린지는 미국  IBM과 Sage Bionetworks가 주최하는 의생명분야 데이터과학 국제 경진대회로 세계적으로 권위를 인정받고
     있는 대회이며 연구팀은 일리노이대-칭화대 컨소시움, 노스캐롤라이나대 팀과 함께 약물활성예측 드림챌린지 공동 최우수팀으로 선정되었다.



 * Oct. 2019: [특별기고] 데이터주도과학과 인공지능. (DATA@KU 4호. 2019.10)

[특별기고]데이터주도과학과 인공지능 – 과학의 패러다임변화를 이끌다컴퓨터학 분야 노벨상이라 불리는 튜링어워드를 받은 짐그레이는 고대로부터
현대까지의 과학의 패러다임변화를 다음과 같이 설명한다. 인류가 과학을 하는 방식이 수천년 전에는 자연현상을 설명하는 경험적 과학이었고,
수백년전부터는 이를 모델링하고 일반화하는 이론적 과학, 수십년 전부터는 이론적 분석이 어려운 복잡한 현상을 컴퓨터 시뮬레이션을 통해 해석하고,
현재는

 * Sep. 2019: Congratulations! DMIS team outperformed Google team and  won 1st
   place at BioASQ challenge, a challenge on large scale biomedical semantic
   indexing and question answering.
   
   * By using BioBERT, our team(Wonjin Yoon, Jinhyuk Lee, Donghyeon Kim, Minbyul
     Jeong) produced outstanding results for all 5 test batches on BioASQ Task
     7B-Phase B (challenge results -
     http://bioasq.org/participate/seventh-challenge-winners ). 
   
   * 의생명 분야의 질의 응답 시스템 경진대회인 BioASQ 대회에서 Google 제치고 1위 [Task 7B-Phase B] (고려대
     보도자료, 전자신문, 연합뉴스)



 * Sep. 2019: Congratulations to Dr. Jinhyuk Lee and Wonjin Yoon for BioBERT
   publication in Bioinformatics!
   
   * BioBERT: a pre-trained biomedical language representation model for
     biomedical text mining is the first biomedical language representation
     model pre-trained on large-scale biomedical corpus and achieves
     state-of-the-art performances on various biomedical NLP tasks. (paper ,
     code)
   
   * With BioBERT, DMIS team won 1st place at BioASQ challenge.   



 * Sep. 2019: Seongjun Yun's paper, Graph Transformer Networks, got accepted to
   In Advances in Neural Information Processing Systems (NeurIPS 2019), one of
   the top-tier conferences in Machine Learning alongside with ICML.




 * Aug. 2019: Donghyeon Park's paper, KitcheNette: Prediction and Ranking Food
   Ingredient Pairings based on Siamese Neural Network, got accepted to IJCAI
   2019, one of the top-tier conferences for general AI.
   
   * DMIS 연구팀은 100만개의 레시피를 분석하고 식재료의 조합을 추천하는 Siamese Neural Network기반의 AI모델을
     개발했다. 해당 모델은 전통적인 기계학습 모델들의 예측 및 추천 성능을 월등히 뛰어넘었으며 연구결과는 인공지능 최고 권위 학술대회 중
     하나인 IJCAI-19, Macao에서 발표될 예정이다. (고려대 보도자료, YTN 사이언스, 매일경제, 연합뉴스, 서울신문,
     IT조선)
   
   * 연구팀은 사용자가 직접 식재료 조합을 찾아보고 연구결과를 활용할 수 있도록 웹페이지를 제공하고 있다. (KitcheNette)



 * May. 2019: Real-Time Open-Domain Question Answering on Wikipedia with
   Dense-Sparse Phrase Index, co-first authored by Jinhyuk Lee, is accepted to
   ACL 2019, the top conference in computational linguistics and natural
   language processing. 



 * May. 2019: ReSimNet: Drug Response Similarity Prediction using Siamese Neural
   Networks, co-first authored by Minji Jeon and Donghyeon Park, has been
   accepted to Bioinformatics, the best journal for computational biology.
   
   * ReSimNet measures the transcriptional response similarity of the two
     chemical compounds, and the team achieved first place in the
     Multi-targeting Drug DREAM Challenge with this model (outperforming Janssen
     Pharmaceutica).  



 * Apr. 2019: Self-Attention Graph Pooling, co-first authored by Junhyun Lee and
   Inyeop Lee, has been accepted to ICML 2019, the top conference in machine
   learning. 



 * Apr. 2019: SAIN: Self-Attentive Integration Network for Recommendation,
   co-first authored by Seoungjun Yun and Raehyun Kim, got accepted by SIGIR
   2019, the best conference in Information Retrieval.



 * Apr. 2019: Congratulations to Dr. Minji Jeon for her first Nature series
   publication! (accepted to Nature Communications) 
   
   * Previously, Dr. Minji Jeon's team won 2nd place in the AstraZeneca Sanger
     Drug Synergy Prediction DREAM challenge (outperforming Stanford(6th),
     MIT(11th)).
   
   * Community assessment to advance computational prediction of cancer drug
     combinations in a pharmacogenomic screen is an overview paper for the DREAM
     challenge and is coauthored by top performing teams and organizers from
     AstraZeneca-Sanger. (bioarxiv)



 * Dec. 2018: Our DMIS team (Minji Jeon, Donghyeon Park, Jinhyuk Lee, Hwisang
   Jeon, Miyoung Ko, Sunkyu Kim, Yonghwa Choi) won 1st place in the
   Multi-targeting Drug DREAM Challenge. The team outperformed  multinational
   pharmaceutical firms such as Janssen Pharmaceutica. (Link1, Link2)
   
   * DMIS 연구팀, 다국적 제약사를 (얀센, 바이엘 등) 제치고 대회에서 우승!     연구팀은 신약 후보 물질을 발굴하는 모델을
     개발했고 AI로 선택한 물질의 가능성이 입증되어 대회 우승팀으로 선정되었다. (매일경제, 연합뉴스)



 * Dec. 2018: Predicting Multiple Demographic Attributes with Task Specific
   Embedding Transformation and Attention Network, co-first authored by Raehyun
   Kim and Hyunjae Kim, has been accepted as full paper by SDM19, one of the
   top-tier conferences in data-mining.

 * Nov. 2018: Buru Chang received the NAVER Ph.D Fellowship Award as he showed
   stellar performance with his papers.

 * Aug. 2018: Jinhyuk Lee's paper, Ranking Paragraphs for Improving Answer
   Recall in Open-Domain Question Answering, was accepted to EMNLP2018, one of
   the most renowned conferences in NLP field.



 * Aug. 2018: Learning User Preferences and Understanding Calendar Contexts for
   Event Scheduling (co-first authored by Donghyeon Kim and Jinhyuk Lee) got
   accepted by CIKM2018, which is one of the top-tier international conferences
   in Database/Data Mining/Information Retrieval field with 17% acceptance rate.



 * Jul. 2018: Buru Chang's paper, Content-Aware Point-of-Interest Embedding
   Model for Successive POI Recommendation, was accepted to IJCAI 2018, one of
   the top-tier conferences for general AI.



 * Nov. 2017: Our DMIS team (Sunkyu Kim, Heewon Lee, Keonwoo Kim, Hwisang Jeon,
   Minji Jeon, Yonghwa Choi, Daehan Kim) was awarded as the BEST performers of
   the NCI-CPTAC DREAM Proteogenomics Challenge, sponsored by the National
   Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC).
   This was the very first time that Korea team won the Challenge. (Link)
   
   * * UCLA: 3rd place
     
     * Stanford University: 13th place

 * * Nov. 2017: 고려대학교 강재우 교수 연구팀 - 암 환자의 단백질 활성도를 예측하는 NCI-CPTAC DREAM
     Proteogenomics Challenge에 참가하여 대회 역사상 한국팀 최초 우승! 해당 Challenge는 미국 국립 암 연구원의
     유전단백체 연구센터(NCI-CPTAC)가 주최하였다. (연합뉴스, 매일경제, 서울경제)



 * Aug. 2017: Jinhyuk Lee's paper, Name Nationality Classification with
   Recurrent Neural Network, got accepted for IJCAI 2017, one of the top-tier
   conferences for general AI.



 * Apr. 2017: Constructing and Evaluating a Novel Crowdsourcing-based
   Paraphrased Opinion Spam Dataset, co-first authored by Seongsoon Kim and
   Seongwoon Lee, has been accepted to WWW 2017, one of the top conferences for
   web.



 * Oct. 2016: Among 42 teams from different parts of the world, our DMIS team
   ranked 2nd place at the Disease Module Identification DREAM Challenge:
   Discover disease pathways in genomic networks. The goal is to systematically
   assess module identification methods on a panel of state-of-the-art genomic
   networks and to discover novel network pathways. 
   
   * Oct. 2016: 생물학적 네트워크에서 질병에 연관된 모듈을 발굴하는 Disease Module Identification DREAM
     Challenge: Discover disease pathways in genomic networks에 참여하여 전체 42팀 중
     종합성적 공동2위 달성! 



 * Mar. 2016: Our DMIS team won 2nd place at the AstraZeneca-Sanger Drug
   Combination Prediction DREAM Challenge, which is designed to predict
   synergistic drug combinations and to identify associated biomarkers. As the
   challenge was hosted by AstraZeneca, one of the top 10 pharmaceutical
   companies in the world, the DMIS team showed stellar performance in this
   grand competition, ranking 2nd place. (Link)
   
   * * Stanford University: 6th place 
     
     * MIT: 11th place

 * * Mar. 2016: 항암제 병합 치료 효능을 예측하는 The AstraZeneca-Sanger Drug Combination
     Prediction DREAM Challenge에 참여하여 전 세계 62팀 중 2위 입상! 해당 Challenge는 세계 10대
     제약회사 "AstraZeneca"가 주최하였으며 강재우 교수 연구팀은 Stanford University(6위), MIT(11위)를
     압도적으로 제치고 2위를 기록했다. (경향신문, 서울경제)


Address : Office 501B, Woojung Hall of Informatics, Korea University, 145
Anam-ro, Seongbuk-gu, Seoul, Republic of Korea 02841 Tel :
+82-2-3290-3566Copyright © 2019, By Data Mining & Information Systems
Laboratory, Department of Computer and Radio Communications, Korea University,
All Rights Reserved. 



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