Speakers

Plenary/Invited speakers and talks in DCTMD2024:

(The list is consistently updated and please click the name for the speaker’s bio and the title of talk for the abstract if available.)

Plenary speakers:

* Roberto Car, Princeton University, USA

* Yanming Ma, Jilin University, China

* Berend Smit, Swiss Federal Institute of Technology in Lausanne (EPFL, Switzerland)

 -Talk: Data Science to Optimize Metal-Organic Frameworks for Carbon Capture Applications

* Chris Wolverton, Northwestern University, USA

* Lucas Foppa, Fritz Haber Institute (FHI) of the Max Planck Society, Germany

     -Talk: Describing Materials Properties and Functions via the “Materials Genes” Concept

* Xiaonan Wang, Tsinghua University, China

      -Talk: AI Foundation models and Active Learning for Materials Discovery and Process Design

Invited speakers:

* T. Daniel Crawford, Virginia Tech, USA

 -Talk: The Molecular Sciences Software Institute

* Jun Jiang, University of Science and Technology of China, China

* Alexandre Tkatchenko, Luxembourg University, Luxembourg

      -Talk: Accurate and efficient biomolecular dynamics enabled by machine-learned force fields

* Yuanyuan Zhou, Technical University of Denmark (DTU), Denmark

   -Talk: AI-accelerated grand-canonical method for surface processes

* Linfeng Zhang, DP Technology, China

* Junfeng Qiao, Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland

      -Talk: The Electronic-Structure Genome of Inorganic Crystals

* Yong Xu, Tsinghua University, China

      -Talk: First-principles artificial intelligence

* Runhai Ouyang, Shanghai University, China

      -Talk: Symbolic Regression in Materials Informatics: Applications and Challenges

* Taylor Sparks, The University of Utah, USA

      -Talk: What do we mean by new? Quantifying structural uniqueness in the era of generative crystal structure prediction

* Lauren Takahashi, Hokkaido University, Japan

      -Talk: Ontology and the role of semantics in the development of knowledge-based materials databases

* Timon Rabczuk, The Bauhaus-Universität Weimar, Germany

* Xiaoying Zhuang, Leibniz University Hannover, Germany

      -Talk: Machine learning based multiscale exploration and characterization of 2D materials

* Zhipan Liu, Fudan University, China

* Carla Verdi, The University of Queensland, Australia

      -Talk: Accurate materials modeling by machine learning and beyond DFT methods

* Sergey V. Levchenko, Skolkovo Institute of Science and Technology (Skotech), Russia

 -Talk: Finding Descriptors of Catalytic Properties from Data for Catalyst Design with the Help of Artificial Intelligence

* Turab Lookman, AiMaterials Research LLC, USA

      -Talk: Guiding the next experiment: Bayesian Global Optimization versus Reinforcement Learning

* Annette Trunscke, Fritz Haber Institute (FHI) of the Max Planck Society, Germany

      -Talk: Creating Synergies between Experimental and Computational Approaches in Advanced Materials Design: Importance and Challenges of Clean Data

* Keisuke Takahashi, Hokkaidao University, Japan

* Rampi Ramprasad, Georgia Tech, USA

 - Talk: Polymer Informatics: Algorithmic Advances & Materials Design

* Lixue Cheng, Microsoft Research AI for Science Lab

    - Talk: Recent advances in Deep QMC developments and its molecular property calculations

* Jungho Shin, Korea Research Institute of Chemical Technology, Korea

* Yangshuai Wang, Department of Mathematics, National University of Singapore, Singapore

- Talk: Advancing Molecular Simulations with Machine-Learned Interatomic Potentials

* Hongxia Hao, Microsoft Research AI for Science

- Talk: AI4Materials: From Simulation to Generation

* Kangming Li, Acceleration Consortium, University of Toronto, Canada

- Talk: Unexpected Failure and Success in Data-Driven Materials Science

* Lei Zhang, Nanjing University of Information Science and Technology, Nanjing, China

- Talk: Language Data-Driven Machine Learning Design of New Materials

* Lei Shen, National University of Singapore, Singapore

  - Talk: Scalable Crystal Structure Relaxation Using an Iteration-free Deep Generative Model with Uncertainty Quantification

* Xin Chen, Suzhou Laboratory, Suzhou, China

- Talk: A Large Multi-Modality Model for Chemistry and Materials Science

* Yousung Jung, Seoul National University, Korea

- Talk: “Data-Enabled Synthesis Predictions for Molecules and Materials”

Contributed speakers:

* Zhenpeng Yao, Shanghai Jiaotong University, China

- Talk: From computational screening to the synthesis of a promising OER catalyst

* Han Wang, Institute of Applied Physics and Computational Mathematics, Beijing, China

- Talk: Simulating the Microscopic World: From Schrödinger Equation to Large Atomic Models

* Jiong Yang, Shanghai University, Shanghai, China

- Talk: HH130: A Standardized Dataset for Universal Machine Learning Force Field and the Applications in the Thermal Transport of Half-Heusler Thermoelectrics

* Guangcun Shan, Beihang University, Beijing, China

- Talk: Progress in Machine Learning Studies for High-Entropy Alloys

* Jun Liu, Beijing University of Chemical Technology, Beijing, China

    - Talk: Computational modeling and simulation of molecular design and property prediction of novel elastomer materials

* Bastien F. Grosso, University of Birmingham, United Kingdom

   - Talk: From imaginary phonons to a universal interatomic potential: the case of BiFeO3

* Xiankang Tang, TU Darmstadt, Germany

   - Talk: Bayesian Optimization for High-Resolution Transmission Electron Microscopy

* Chunxia Chi, Nankai University, Tianjin, China

   - Talk: Anisotropic materials with abnormal Poisson’s ratios and acoustic velocities

* Huazhang Zhang, University of Liège, Belgium

   - Talk: Effective lattice potentials of perovskite oxides derived from elaborately designed training dataset

* Wenkai Ning, Shanghai University, Shanghai, China.

   - Talk: Extraction of data from publications empowered by Kolmogorov-Arnold Networks

* Akhil S. Nair, Fritz Haber Institute of the Max-Planck-Gesellschaft, Germany

   - Talk: AI-driven Workflow for Identifying Stable Oxides for Electrocatalysis

* Yunwei Zhang, Sun Yat-sen University, Guangzhou, China

   - Talk: Battery prognosis from impedance spectroscopy using machine learning

…More speakers will be added soon…