Public Services

• Introduction of AI and tensorflow 2.0
  DNN, CNN, RNN, ConvLSTM and U-Net. AI for Scientific Research.
  Boom-in Science Consulting. [Sep-Oct 2021]

• Introduction of AI and tensorflow 2.0
  DNN, CNN, RNN, ConvLSTM, U-Net and Reinforcement Learning (DQN, DDPG, REINFORCE).
  AIAI-2022 . (https://aiworkshop.kr/) [Jan 2022]

Invited Talks

• Kakao Enterprise, Virtual [Dec 2020]
  Physics-driven AI: Material and Climate AI

• School of Material Science and Engineering, Seoul National Univ. [Sep 2020]
  Optimizing 3D Molecular Structure using Reinforcement Learning

• School of Computer Science, Yeonsei Univ. [Apr 2020]
  How can AI enable Science?

• School of EECS, Ewha Woman's Univ., Virtua [Apr 2020]
  Tackling Hurricane Tracking using Deep Learning

• Spotlight talk at ICLR climate change workshop, Virtual [Apr 2020]
  Hurricane Nowcasting with Irregular Time-step using Neural-ODE and Video Prediction

• School of Environmental Studies, Seoul National Univ., Seoul, Korea [Aug 2019]
  Climate AI: Physics-based AI techniques tackling extreme climate analysis

• KSC tutorials, Seoul, Korea [Apr 2019]
  Build basic Deep Learning model using TensorFlow

• Spotlight talk at Women in Machine Learning, ECCV [Aug 2018]
  Tracking and Forecasting extreme climate events using computer vision techniques

• Spotlight talk at Climate Informatics workshop}, Boulder, Co, USA [Sep 2018]
  Tracking and Forecasting extreme climate events using AI

• ESGF Face to Face meeting}, San Francisco, CA, USA. [Dec 2017]
  Deep Learning Application for Community Machine Learning using ESGF

• Data Mining on Earth System Science in ICDM}, New Orleans, LA, USA [Dec 2017]
  Framework for Detection and Localization of Extreme Climate Event with Pixel Recursive Super Resolution

• The Korean Computer Scientists and Engineers Association in America (KOCSEA) Symposium}, Las Vegas, NV, USA [Nov 2017]
  Deep Learning Application for Climate Science

• Data Analytics Group Seminar in Center for Applied Scientific Computing at LLNL, Livermore, CA, USA [Oct 2017]
  Detection, Localization and Recursive Super Resolution of Climate Data using Deep Learning

• ESGF Proposal Review Meeting}, Washington D.C., USA [Jun 2017]
  Machine Learning for Earth System Grid Federation (ESGF)

• Uncertainty Quantification and Data-Driven Modeling, Austin, TX, USA[Mar 2017]
  Massive Scale Deep Learning for Predicting Extreme Climate Events

• US-Korea Conference (UKC), Dallas, TX, USA [Aug 2016]
  Monte-Carlo approach for simulate annealing and Applying high performance features using GPU

• NVIDIA GPU Technology Conference (GTC)}, San Jose, CA, USA [Apr 2016]
  Quantum Monte-Carlo Simulation implementing GPU

• The 56th Sanibel Symposium on Quantum Chemistry, Dynamics, Condensed Matter Physics, Grunswick, GA, USA [ Feb 2016]
  GPU-Accelerated Heisenberg Monte-Carlo Simulation

• Workshop on Social Recommender Systems at KDD, Sydney, Australia [Aug 2015]
  Personalized Academic Research Paper Recommendation System

• Korea Advanced Institute of Science and Technology (KAIST), Department of Physics, Daejeon, Korea [Dec 2014]
  Design Rules for Rare-earth Replacement Magnetic Materials: MnBi and MnSb Families

• Materials Research Society (MRS) Fall Meeting 2014, Boston, MA, USA [Nov 2014]
  Thermo-magnetic Properties of Rare-earth Replacement Magnetic Materials

• US-Korea Conference (UKC)}, San Francisco, CA, USA [Aug 2014]
  Computational Modeling of Thermo- magnetic Properties of Materials

• The 52nd Sanibel Symposium on Quantum Chemistry, Dynamics, Condensed Matter Physics, Grunswick, GA, USA [ Feb 2012]
  Thermo-magnetic Properties of MnBi and MnSb Binary Com- pounds with NiAs Structure

Grants and Awards

• 3rd Place Award [Dec 2020]
  Competition for a novel idea for post-COVID-19 era, Seoul City Forum

• AI for Earth Research Grant [Aug 2020]
  $10,000 USD that comes with Microsoft Azura Compute Grant for ``Hurricane Now-casting with irregular Time Steps using Neural ODE and Video Prediction''

• LDRD Grant [Sep 2019]

Served Co-PI role for an LDRD (Laboratory Directed Research and Development) research grant, Lawrence Livermore National Lab. (Around $1.4 M USD)

• R&D 100 Award [Oct 2017]
  Federal Laboratory Consortium (FLC) regional competition (as a member of ESGF team)

Services

• DOE BER Funding Panel Reviewer [July 2019, July 2020]
  Served as a panel reviewer for Biological \& Environmental Research (BER) project within the Department of Energy Office of Science

• Program Chair and Organizer

  • Data Mining on Earth System Science (DMESS) at ICDM 2018, 2019

  • Big Data in the Geosciences: New Approaches to Storage, Sharing, and Analysis at AGU 2018

• Paper Reviewer

  • Climate Informatics

  • DMESS workshop

  • ICLR Climate Change Workshop

  • ICDM

  • ICLR

  • CVPR

  • IEEE’s Transactions on Parallel and Distributed Systems.