Welcome to the
Waller Lab

Projects

what we are working on

Mentor

Reaction Discovery Framework

Q|R

Quantum Refinement

Robogenica

Robotic Chemistry Platform

Jacob

Just a collection of benchmarks

Yoink

Adaptive multiscale methods

Decider

Decision Support System

Swy

Hybrid Metaheuristic Optimizer

Chem Preview

Molecular Augmented Reality

Reaktor

Tabu-based Reaction Prediction

The Team

Mark P. Waller

Sydney, Australia

Present Members

Suzanne Mcananama-Brereton

PhD Student

Min Zheng

PhD Student

Marwin Segler

PhD Student

Lum Wang

M.Sc. Student

Ruiqin Xu

PhD Student

Yanting Xu

PhD Student

Wensong Wang

M.Sc. Student

Chong Shu

M.Sc. Student

Zhenlong Gong

M.Sc. Student

Mingzhu Sheng

M.Sc. Student

Past Members

Dr. Jack Yang

Postdoctoral Fellow

Dr. Jissy Kurriappan

Postdoctoral Fellow

Dr. Sateesh Bandaru

Postdoctoral Fellow

Sadhana Kumbhar

PhD Student

Thomas Dresselhaus

M.Sc. Student

Frank Fischer

Diploma Student

Research Visitors

Saibal Jana

Swapnil Wagle

Anurag Sharma

Surajit Nandi

Siladitya Padhi

Aditya Chattopadhyay

Latest Publications



  • Planning chemical syntheses with deep neural networks and symbolic AI

    Marwin H. S. Segler, Mike Preuss, Mark P. Waller
  • Yoink: an interaction-based partitioning API

    Min Zheng, Mark P. Waller

    Journal of Computational Chemistry, DOI: 10.1002/jcc.25146
    https://doi.org/10.1002/jcc.25146/full
    2018

  • Rational density functional selection using game theory

    Suzanne R. McAnanama-Brereton, Mark P. Waller

    J. Chem. Inf. Model., 2018, 58, 61–67
    https://doi.org//10.1021/acs.jcim.7b00542
    2018

  • Solving the scalability issue in quantum-based refinement: Q|R#1

    Min Zheng, Nigel W. Moriarty, Yangting Xu, Jeffrey Reimers, Pavel Afonine, and Mark P. Waller

    Acta Crystallographica Section D
    https://doi.org/10.1107/S2059798317016746.
    2017, D73

  • Learning to Plan Chemical Syntheses

    Marwin H. S. Segler, Mike Preuss, Mark P. Waller

    arXiv
    arXiv:1708.04202
    2017

  • Modelling Chemical Reasoning to Predict and Invent Reactions

    Marwin H. S. Segler, Mark P. Waller
    Chemistry - A European Journal, 2017,

    http://dx.doi.org/10.1002/chem.201604556
    2017.

  • Towards ‘AlphaChem’: Chemical Synthesis Planning with Tree Search and Deep Neural Network Policies

    Marwin H. S. Segler, Mike Preuss, Mark P. Waller
  • A Tabu-search Based Strategy for Modeling Molecular Aggregates and Binary Reactions

    Surajit Nandi, Suzanne R. McAnanama-Brereton, Mark P. Waller, Anakuthil Anoop

    Computational and Theoretical Chemistry
    http://doi.org/10.1016/j.comptc.2017.03.040
    2017

  • Generating Focussed Molecule Libraries for Drug Discovery with Recurrent Neural Networks

    Marwin H.S. Segler, Thierry Kogej, Christian Tyrchan, Mark P. Waller
  • Neural-Symbolic Machine Learning for Retrosynthesis and Reaction Prediction

    Marwin H.S. Segler, Mark P. Waller

    Chemistry - A European Journal, 2017,
    http://dx.doi.org/10.1002/chem.201605499.
    2017,23,1-7

  • ChemPreview: Towards an Augmented Reality-based Molecular Interface

    Min Zheng, Mark P. Waller

    Journal of Molecular Graphics and Modelling
    http://doi.org/10.1016/j.jmgm.2017.01.019
    2017,73,18-23.

  • Q|R: Quantum-based Refinement

    Min Zheng, Jeffrey Reimers, Mark P. Waller and Pavel Afonine

    Acta Crystallographica Section D
    https://doi.org/10.1107/S2059798316019847
    2017, D73, 45-52

  • A Hybrid Dimer Swarm Optimizer

    Jack Yang, Mark P. Waller

    Computational and Theoretical Chemistry
    http://doi.org/10.1016/j.comptc.2016.12.019
    2017, 1102,98-104