Welcome to Big Data & Deep Learning Systems Lab

In Big Data & Deep Learning Systems Lab, we investigate programmability, scalability, fault tolerance, manageability, and performance of big data & deep learning systems. We study improving existing big data systems such as Hadoop or Pregel, as well as deep learning systems such as Tensorflow or PyTorch. We investigate various trade-offs (such as performance and accuracy) in existing systems. We also work on security aspect of deep learning models and systems. Besides these areas, we collaborate with Stanford MobiSocial Group to study innovative platform for Internet of Things. See Research Page for the (partial) list of research projects.

Research Topics include  (연구 주제):
  • Large-Scale Machine Learning (Deep Learning) System    대용량 기계학습 (딥 러닝) 시스템
  • Big Data Systems    빅 데이터 시스템
  • Big Data Mining and Analysis    빅 데이터 분석
  • Graph Analytics    그래프 분석 (소셜 네트워크, 게놈 네트워크, 시멘틱 웹)
  • Keunhak Lim has his poster paper accepted in SOSP, a premier conference on computer systems. Congrats!
  • Junghoon Kim enters the Nanyang Technological University, Singapore as a PhD student in CS department. NTU is a top university in Singapore. Congrats!
  • Prof. Seo serves as a Program Committeemember in CIKM 2017. CIKM is a premier conference for the discussion of research on the management of knowledge, information, and data.
  •  We have openings for Undergrad(intern)/MS/PhD students and postdocs. If you are interested, please contact Prof. Seo (lastname firstname @ hanyang.ac.kr [seojiwon])

My talk at Hadoop Summit ‎‎‎‎‎‎‎(in collaboration with Hortonworks)‎‎‎‎‎‎‎ 빅데이터 관련 산업계 최고 학회인 하둡 서밋 발표내용 (호톤웍스와 협업)