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Prof. Hanyu GAO

Research Interests | Publications

Research Area

Machine Learning, Theory and Simulation, Numerical Optimization

Research Interests

Computer-aided Synthesis Planning, Process Simulation and Optimization, Kinetic Monte Carlo, Polymer Reaction Engineering, AI-driven Chemical Discovery

Recent Publications


  • Gao, Hao; Pauphilet, Jean; Struble, Thomas J.; Coley, Connor W.; Jensen, Klavs F., "Direct Optimization across Computer-Generated Reaction Networks Balances Materials Use and Feasibility of Synthesis Plans for Molecule Libraries", (2021)
  • Plehiers, Pieter P.; Coley, Connor W.; Gao, Hanyu; Vermeire, Florence H.; Dobbelaere, Maarten R.; Stevens, Christian V.; Van Geem, Kevin M.; Green, William H., "Artificial Intelligence for Computer-Aided Synthesis In Flow: Analysis and Selection of Reaction Components", (2020)
  • Gao, Hanyu; Coley, Connor W.; Struble, Thomas J.; Li, Linyan; Qian, Yujie; Green, William H.; Jensen, Klavs F., "Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list", (2020)
  • Wang, Xiaoxue; Qian, Yujie; Gao, Hanyu; Coley, Connor W.; Mo, Yiming; Barzilay, Regina; Jensen, Klavs F., "Towards efficient discovery of green synthetic pathways with Monte Carlo tree search and reinforcement learning", (2020)
  • Coley, Connor W.; Thomas, Dale A. III; Lummiss, Justin A.M.; Jaworski, Jonathan N.; Breen, Christopher P.; Schultz, Victor; Hart, Travis; Fishman, Joshua S.; Rogers, Luke; Gao, Hanyu; Hicklin, Robert W.; Plehiers, Pieter P.; Byington, Joshua; Piotti, John S.; Green, William H.; Hart, A. John; Jamison, Timothy F.; Jensen, Klavs F., "A robotic platform for flow synthesis of organic compounds informed by AI planning", (2019)

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Recent Publications


  • Gao, H., Pauphilet J., Struble, T. J., Coley, C. W., Jensen, K. F. (2020). Direct optimization across computer generated reaction networks balances materials use and feasibility of synthesis plans for molecule libraries. submitted.

  • Wang, X., Qian, Y., Gao, H., Coley, C. W., Mo, Y., Barzilay R., Jensen, K. F. (2020). Towards Efficient Discovery of Green Synthesis Pathways with Monte Carlo Tree Search and Reinforcement Learning. Chemical Science, Accepted.

  • Plehiers, P. P., Coley, C. W., Gao H., Vermeire F. H., Dobbelaere M. R., Stevens C. V., Van Geem K. M., Green W. H. (2020). Artificial Intelligence for Computer-Aided Synthesis In Flow: Analysis and Selection of Reaction Components. Frontiers in Chemical Engineering, 2020, 5

  • Gao, H., Coley, C. W., Struble, T. J., Li, L., Qian, Y., Green, W. H., Jensen, K. F. (2020). Combining Retrosynthesis and Mixed-Integer Optimization for Predicting the Minimum Chemical Inventory Needed to Realize a WHO Essential Medicines List. React. Chem. Eng., 5, 367-376.

  • Coley, C. W., Thomas D., Lummiss, J., Jaworski, J. Rogers, L. Schultz, V., Fishmann J., Breen, C., Hart, T., Gao, H., Hicklin, R., Plehiers, P., Piotti, J., Green, W. H., Hart, J., Jamison, T. F., Jensen, K. F. (2019). A Robotic Platform for Flow Synthesis of Organic Compounds Informed by AI Planning. Science, vol. 365(6453), eaax1566.

  • Gao, H., Struble, T. J., Coley, C. W., Green, W. H., Jensen, K. F. (2018). Using Machine Learning to Predict Suitable Conditions for Organic Reactions. ACS Central Science, 4.11, 1465-1476. (Highlighted by Science, https://science.sciencemag.org/content/362/6420/1260.2)

  • Gao, H., Waechter, A., Konstantinov, I. A., Arturo, S. G., Broadbelt, L. J. (2018). Application and Comparison of Derivative-free Optimization Algorithms to Control and Optimize Free Radical Polymerization Simulated Using the Kinetic Monte Carlo Method. Computers & Chemical Engineering, vol. 108, 268-275.

  • Gao, H., Konstantinov, I. A., Arturo, S. G., Broadbelt, L. J. (2017). On the Modeling of Number and Weight Average Molecular Weight of Polymers. Chemical Engineering Journal, vol. 327, 906-913.

  • Gao, H., Konstantinov, I. A., Arturo, S. G., Broadbelt, L. J. (2016). Acceleration of Kinetic Monte Carlo Simulations for Free Radical Copolymerization: a Hybrid Approach with Scaling of Kinetic Parameters. AIChE Journal, vol. 63(9), 4013-4021.

  • Zhang, G., Zhang, L., Gao, H.; Konstantinov, I. A., Arturo, S. G., Yu, D., Torkelson, J. M., Broadbelt, L. J. (2016). A Combined Computational and Experimental Study of Copolymerization Propagation Kinetics for 1-Ethylcyclopentyl Methacrylate and Methyl Methacrylate. Macromol. Theory Simul., vol. 25(3), 263-273

  • Gao, H., Oakley, L. H., Konstantinov, I. A., Arturo, S. G., Broadbelt, L. J. (2015). Acceleration of Kinetic Monte Carlo Method for the Simulations of Free Radical Copolymerization through Scaling. Industrial & Engineering Chemistry Research, vol. 54 (48), 11975-11985. (Selected as the ACS Editor’s Choice for October 26th, 2015)

  • Regatte, V. R., Gao, H., Konstantinov, I. A., Arturo, S. G., Broadbelt, L. J. (2014). Design of Copolymers Based on Sequence Distribution for a Targeted Molecular Weight and Conversion. Macromol. Theory Simul., vol. 23 (9), 564-574.

  • Leperi, K., Gao, H., Snurr, R.Q., You, F. (2014). Modeling and Optimization of a Two-stage MOF-based Pressure/vacuum Swing Adsorption Process Coupled with Material Selection. Proceedings of the 17th Conference on Process Integration, Modelling and Optimization for Energy Saving and Pollution Reduction (PRES). Chemical Engineering Transactions, 39, 277-282

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