Big Data Lab @ Inha Univ
"AI For Good"
OUR Mission: Make AI More EFFICIENT, Scalable & ACCESSIBLE
Our group aims to develop machine learning (ML) technologies over Big Data. Our research interests encompass the general areas of machine learning, data mining, databases, and theoretical algorithms.
Basically, we focus on advancing the efficiency, scalability, and accessibility of every cycle of ML over Big Data mostly by designing intelligent learning algorithms that can efficiently train or analyze the vast amounts of data. In the academic perspective, we always pursue research of the highest quality in theory as well as in practice, and attempt to publish solid papers in top-tier venues in the field of big data and machine learning, including ICML, NeurIPS, ICLR, AAAI, KDD, ICDM, SIGMOD, VLDB, ICDE, etc. For more top-tier conferences and journals, please refer to the following Google Scholar pages: Artificial Intelligence, Data Mining & Analysis, and Databases & Information Systems.
LATEST NEWS
[Apr 2024] A paper has been accepted in CoLLAs 2024, a rising conference in continual learning.
Our paper, "Replaying with Realistic Latent Vectors in Generative Continual Learning," (1st author: Hyemin Jeong, MS alumnus) has been accepted for the CoLLAs 2024 conference, which is a rapidly evolving conference in the specific field of Continual Learning. Congratulations to Hyemin!
[Dec 2023] Yunseok won an Outstanding Papers Award at KSC 2023.
Yunseok Oh (MS Student) won an Outstanding Papers Award (우수논문상) at the KSC 2023 conference in the field of AI for our paper, "Efficient Prompt Learning Method in Blurry Class Incremental Learning Environment (Blurry 클래스 증분 학습 환경에서의 효율적인 프롬프트 학습 방법)." Congratulations to Yunseok!
[Dec 2023] Two papers have been accepted in AAAI 2024, a top-tier conference in the field of AI.
For AAAI 2024, the following two papers are accepted within our lab.
"Recall-Oriented Continual Learning with Generative Adversarial Meta-Model" (1st author: Haneol Kang, MS alumnus)
"Teacher as a Lenient Expert: Teacher-Agnostic Data-Free Knowledge Distillation" (1st author: Hyunjune Shin, MS candidate)
Congratulations to Haneol and Hyunjune!
[Dec 2022] Hyemin won an Outstanding Papers Award at KSC 2022.
Hyemin Jeong (MS Student) won an Outstanding Papers Award (우수논문상) at the KSC 2022 conference in the field of AI for our paper, "GAN Continual Learning with Latent Vector Rehearsal (잠재벡터 저장을 통한 GAN 지속학습)." Congratulations to Hyemin!
[Nov 2022] A paper has been accepted in AAAI 2023, a top-tier conference in the field of AI.
Our paper, "Better Generalized Few-Shot Learning Even Without Base Data," (1st author: Seongwoong Kim, MS alumnus) has been accepted for the AAAI 2023 conference, which is a top-tier conference in the filed of AI. This is the second time (first time also from our lab) at Inha University an MS student's work has been accepted for AAAI. Congratulations to Seongwoong!
Vacancies
We are seeking highly talented and motivated individuals to join our research group as MS or PhD students. If you are interested in working with us on cutting-edge research in the field of Big Data & Machine Learning, please email Prof. Choi your CV, transcript, and hopefully a short statement of your research interests.
Please note that we are only able to offer BS internship opportunities to individuals who will be joining us as graduate students.
빅데이터 연구실에서는 석사과정, 박사과정 학생을 모집하고 있습니다. 대학원 진학 및 연구실에 대해서 관심이 있는 학생들은 dchoi@inha.ac.kr로 CV와 간단한 연구(학업)계획서를 첨부해서 이메일을 보내기 바랍니다. 학부연구생은 대학원 진학 예정자만 가능하니 참고하기 바랍니다.