Chemistry Program

June 7th

  • Session Topic
  • 9:00-9:30
  • 9:30-10:00
  • 10:00-10:30
  • break
  • 11:00-11:30
  • 11:30-12:00
  • 12:00-12:30
  • 12:30-1:30 - lunch/posters
  • 1:30-2:30 - plenary
  • Session Topic
  • 2:30-3:00
  • 3:00-3:30
  • 3:30-4:00
  • break
  • 4:30-5:00
  • 5:00-5:30
  • 5:30-6:00

June 8th


Mojtaba Haghighatlari (Buffalo) – “Software development and its application for predicting optical properties in molecular sspace: ChemML program suite

Xi Chen (Brown) – “The application of machine learning in variational transition state theory

Derek Metcalf (MSU) – “Using Bayesian neural networks to understand uncertainty in model neural network chemistry predictions

Chen Qu (Emory) – “Assessing the Gaussian process approach in potential energy surface fitting

Mohammad Atif Afzal (Buffalo) – “Harnessing virtual high-throughput screening and machine learning for the discovery of novel high-refractive-index polymers

Holden Parks (CMU) – “Quantifying uncertainty in first-principles predictions of molecular vibrational frequencies with applications to machine learning

Haichen Li (CMU) – “Using deep reinformcement learning to guide chemical reactions

Michael Taylor (Pittsburgh) – “TBD”

Mariya Popova (UNC) – “De-novo drug design with deep reinforcement learning

Christopher Kotke (CMU) – “TBD”

Run Li (Florida State) – “WITHDRAWN- Development of complex v2RDM driven relativistic CASSCF methods”

Timothy Rose (CMU) – “Evolutionary niching in the GAtor genetic algorithym for molecular crystal structure prediction”

Xingyu Liu (CMU) – “Accelerate searching for singlet fission materials: Feature selection and model construction for GW+BSE method with SISSO”

Joon-Yong Lee (PNNL) – "Deep Learning Benchmark Data for de novo Peptide Sequencing"