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  1. K. L. Saar, D. Fearon, COVID Moonshot Consortium, F. von Delft, J. D. Chodera, A. A. Lee, "Turning high-throughput structural biology into predictive inhibitor design", Proceedings of the National Academy of Sciences, in press (2023)

  2. R.-R. Griffiths*, J. L. Greenfield*, A. R. Thawani*, A. R. Jamasb, H. B. Moss, A. Bourached, P. Jones, W. McCorkindale, A. A. Aldrick, M. J. Fuchter, A. A. Lee, "Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes", Chemical Science, 13, 13541 (2022) 

  3. P. K. Jones, U. Stimming, A. A. Lee, "Impedance-based forecasting of lithium-ion battery performance amid uneven usage", Nature Communications, 13 (1), 4806 (2022)

  4. R. E. A. Goodall, A. S. Parackal, F. A. Faber, R. Armiento, A. A. Lee, "Rapid discovery of stable materials by coordinate-free coarse graining", Science Advances, Science Advances 8 (30), eabn4117 (2022)

  5. A. Jose, D. Guest, R. LeGay, G. J. Tizzard, S. J. Coles, M. Derveni, E. Wright, L. Marrison, A. A. Lee, A. Morris, M. Robinson, F. von Delft, D. Fearon, L. Koekemoer, T. Matviuk, A. Aimon, C. J. Schofield, T. R. Malla, N. London, B. W. Greenland, M. C. Bagley, J. Spencer, Covid Moonshot Consortium, "Expanding the Repertoire of Low‐Molecular‐Weight Pentafluorosulfanyl‐Substituted Scaffolds", ChemMedChem, 17, e202100641(2022)

  6. S. Ackloo, R. Al-Awar, R. E. Amaro, C. H. Arrowsmith, H. Azevedo, R. A. Batey, Y. Bengio, U. AK Betz, C.G Bologa, J. D. Chodera, W. D. Cornell, I. Dunham, G. F. Ecker, K. Edfeldt, A. M. Edwards, M. K. Gilson, C. R. Gordijo, G. Hessler, A. Hillisch, A. Hogner, J. J. Irwin, J. M. Jansen, D. Kuhn, A. R. Leach, A. A. Lee, U. Lessel, M. R. Morgan, J. Moult, I. Muegge, T. I. Oprea, B. G. Perry, P. Riley, S. AL Rousseaux, K. Singh Saikatendu, V. Santhakumar, M. Schapira, C. Scholten, M. H. Todd, M. Vedadi, A. Volkamer, T. M Willson, "CACHE (Critical Assessment of Computational Hit-finding Experiments): A public–private partnership benchmarking initiative to enable the development of computational methods for hit-finding", Nat Rev Chem 6, 287–295 (2022)

  7. Z. Li, H. Bretscher, Y. Zhang, G. Delport, J. Xiao, A. A. Lee, S. D. Stranks, A. Rao, "Mechanistic insight into the chemical treatments of monolayer transition metal disulfides for photoluminescence enhancement", Nature Communications, 12, 6044 (2021)

  8. R-R Griffiths, A. A. Aldrick, M. Garcia-Ortegon, V. R. Lalchand, A. A. Lee, “Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation", Machine Learning: Science and Technology, Machine Learning: Science and Technology, 3, 015004 (2022)

  9. R. E. A. Goodall, B. Zhu, J. L MacManus-Driscoll, A. A. Lee, “Materials Informatics Reveals Unexplored Structure Space in Cuprate Superconductors”, Advanced Functional Materials, Advanced Functional Materials, 31, 2104696 (2021)

  10. R. E. A. Goodall, A. A. Lee, “Data-driven approximations to the bridge function yield improved closures for the Ornstein-Zernike equation”, Soft Matter, 17, 5393 (2021)

  11. A. Morris, W. McCorkindale, The COVID Moonshot Consortium, N. Drayman, J. D. Chodera, S. Tay, N. London, A. A. Lee, “Discovery of SARS-CoV-2 main protease inhibitors using a synthesis-directed de novo design model”, Chemical Communications, 57, 5909 (2021)

  12. K. L. Saar, A. S. Morgunov, R. Qi, W. E. Arter, G. Krainer, A. A. Lee, T. P. J. Knowles, “Learning the molecular grammar of protein condensate formation from sequence determinants and embeddings”, Proceedings of the National Academy of Sciences, 118, 15, e2019053118 (2021)

  13. P. K. Jones, F. Coupette, A. Härtel, A. A. Lee, “Bayesian unsupervised learning reveals hidden structure in concentrated electrolytes”, Journal of Chemical Physics, 154, 134902 (2021)

  14. D. P. Kovacs, W. McCorkindale, A. A. Lee, “Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias”, Nature Communications, 12, 1695 (2021)

  15. S. A. Malik, R. E. A. Goodall, A. A. Lee, “Predicting the Outcomes of Material Syntheses with Deep Learning”, Chemistry of Materials, 33, 616 (2021)

  16. R. E. A. Goodall, A.A. Lee, “Predicting materials properties without crystal structure: deep representation learning from stoichiometry”, Nature Communications, 11, 6280 (2020) 

  17. T. J. Wills, D. A. Polshakov, M. C. Robinson, A. A. Lee, "Impact of Chemist-In-The-Loop Molecular Representations on Machine Learning Outcomes", Journal of Chemical Information and Modelling, Journal of Chemical Information and Modelling, 60, 4449 (2020)

  18. P. Verpoort, A. A. Lee, D. J. Wales, "Archetypal landscapes for deep neural networks", Proceedings of the National Academy of Sciences, https://doi.org/10.1073/pnas.1919995117 (2020)

  19. J. Chodera*, A. A. Lee*, N. London*, F. von Delft*, "Crowdsourcing drug discovery for pandemics", Nature Chemistry, 12, 581 (2020)

  20. S. Becker, Y. Zhang, A. A. Lee, "Geometry of energy landscapes and the optimizability of deep neural networks", Physical Review Letters, 124, 108301 (2020)

  21. S. Chitturi, P. Verpoort, A. A. Lee, D. Wales, "Perspective: New Insights From Loss Function Landscapes of Neural Networks", Machine Learning: Science and Technology, 1, 023002 (2020)

  22. Y. Zhang, Q. Tang, Y. Zhang, J. Wang, U. Stimming, A. A. Lee, “Identifying degradation patterns of Li-ion batteries from impedance spectroscopy using machine learning”, Nature Communications, 11, 1706 (2020)

  23. V. Spandan, D. Putt, R. Ostilla-Mónico, A. A. Lee, “Fluctuation-induced forces in homogeneous isotropic turbulence”, Science Advances, 6, 14, eaba0461 (2020)

  24. M. C. Robinson, R. C. Glen, A. A. Lee, “Validating the Validation: Reanalyzing a large-scale comparison of Deep Learning and Machine Learning models for bioactivity prediction”, Journal of Computer-Aided Molecular Design, 34, 717 (2020)

  25. A. A Lee, Q. Yang, V. Sresht, P. Bolgar, X. Hou, J. Klug-McLeod and C. Butler, “Molecular Transformer unifies reaction prediction and retrosynthesis across pharma chemical space”, Chemical Communications, 55, 12152 (2019)

  26. P. Schwaller, T. Laino, T. Gaudin, P. Bolgar, C. Bekas, A. A. Lee, “Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Prediction”, ACS Central Science, 5, 1572 (2019)

  27. Y. Zhang, A. A. Lee, "Bayesian semi-supervised learning for uncertainty-calibrated prediction of molecular properties and active learning", Chemical Science, 10, 8154 (2019)  

  28. A. A. Lee, Q. Yang, A. Bassyouni, C. R. Butler, X. Hou, S. Jenkinson, D. A. Price, “Ligand biological activity predicted by cleaning positive and negative chemical correlations”, Proceedings of the National Academy of Sciences, 116, 3373 (2019)

  29. F. Coupette, A. A. Lee, A. Härtel, "Screening length in ionic liquids", Physical Review Letters, 121, 075501 (2018)

  30. Y. Zhang, A. M. Saxe, M. S. Advani, A. A. Lee, "Energy-entropy competition and the effectiveness of stochastic gradient descent in machine learning", Molecular Physics, 116, 3124 (2018)  

  31. A. A. Lee, J.-P. Hansen, O. Bernard and B. Rotenberg, "Casimir force in dense confined electrolytes", Molecular Physics, 116, 3147 (2018)  

  32. A. A. Lee*, S. V. Kostinski* and M. P. Brenner, "Controlling Polyelectrolyte Adsorption onto Carbon Nanotubes by Tuning Ion-image Interactions", Journal of Physical Chemistry B, 122, 1545 (2018) 

  33. A. A. Lee, M. P. Brenner and L. J. Colwell, "Optimal design of experiments by combining coarse and fine measurements", Physical Review Letters, 119, 208101 (2017)

  34. A. A. Lee, D. Vella, J. S. Wettlaufer, "Fluctuation Spectra and Force Generation in Non-equilibrium Systems", Proceedings of the National Academy of Sciences, 114, 9255 (2017)

  35. A. A. Lee, C. S. Perez-Martinez, A. M. Smith and S. Perkin, "Scaling Analysis of the Screening Length in Concentrated Electrolytes", Physical Review Letters, 119, 26002 (2017)

  36. H. Tanaka, A. A. Lee and M. P. Brenner, "Hot particles attract in a cold bath", Physical Review Fluids, 2, 43103 (2017)

  37. A. M. Smith, A. A. Lee and S. Perkin, "Switching the structural force in ionic liquid-solvent mixtures by varying composition", Physical Review Letters, 118, 96002 (2017)

  38. A. A. Lee, C. S. Perez-Martinez, A. M. Smith, S. Perkin, "Underscreening in concentrated electrolytes", Faraday Discussions, 199, 239 (2017)

  39. R. Ostilla-Monico, A. A. Lee, "Controlling turbulent drag across electrolytes using electric fields", Faraday Discussions, 199, 159 (2017)

  40. M. A. Gebbie, A. M. Smith, H. A. Dobbs, A. A. Lee, G. Warr, X. Banquy, M. Valtiner, M. W. Rutland, J. N. Israelachvili, S. Perkin and R. Atkin, "Long range electrostatic forces in ionic liquids", Chemical Communications, 53, 1214 (2017)

  41. A. A. Lee, M. P. Brenner and L. J. Colwell, "Predicting Protein-Ligand Affinity with a Random Matrix Framework", Proceedings of the National Academy of Sciences, 113, 13564 (2016)

  42. A. A. Lee, "Microscopic Mechanism of Thermomolecular Orientation and Polarization", Soft Matter, 12, 8661 (2016)

  43. A. A. Lee and S. Perkin, "Ion−Image Interactions and Phase Transition at Electrolyte−Metal Interfaces", Journal of Physical Chemistry Letters, 7, 2753 (2016)

  44. A. A. Lee, D. Vella, A. Goriely and S. Kondrat, "Capacitance-Power-Hysteresis Trillemma in Nanoporous Supercapacitors", Physical Review X, 6, 21034 (2016)

  45. A. M. Smith, A. A. Lee and S. Perkin, "The Electrostatic Screening Length in Concentrated Electrolytes Increases with Concentration", Journal of Physical Chemistry Letters, 7, 2157 (2016)

  46. A. A. Lee, D. Vella and A. Goriely, "Quantum Capacitance Modifies Interionic Interactions in Semiconducting Nanopores", Europhysics Letters, 113, 38005 (2016) 

  47. A. A. Lee, A. Muench,  E. Suli, “Sharp Interface Limits of the Cahn-Hilliard Equation with Degenerate Mobility”, SIAM Journal of Applied Mathematics, 76, 433 (2016)

  48. A. A. Lee, M. Senior, M. I. Wallace, T. E. Woolley and I. M Griffiths, "Dissecting the Self-Assembly Kinetics of Multimeric Pore-forming Toxins", Journal of the Royal Society Interface, 13, 20150762 (2016)

  49. A. A. Lee, C. Le Gouellec and D. Vella, “The Role of Extensibility in the Birth of a Ruck in a Rug”, Extreme Mechanics Letters, 5, 81 (2015)

  50. A. A. Lee, S. Kondrat, D. Vella and A. Goriely, "Dynamics of Ion Transport in Ionic Liquids", Physical Review Letters, 115, 106101 (2015)

  51. A. A. Lee, A. Muench and E. Suli, “Degenerate Mobilities in Phase Field Models are Insufficient to Capture Surface Diffusion”, Applied Physics Letters, 107, 81603 (2015)

  52. A. A. Lee, D. Vella, S. Perkin and A. Goriely, "Are Room Temperature Ionic Liquids Dilute Electrolytes", Journal of Physical Chemistry Letters, 6, 159 (2014) 

  53. A. A. Lee, D. Vella, S. Perkin and A. Goriely, "Unravelling Nanoconfined Films of Ionic Liquids", Journal of Chemical Physics, 141, 94904 (2014) 

  54. A. A. Lee, S. Kondrat and A. A. Kornyshev, “Single-file Charge Storage in Conducting Nanopores”, Physical Review Letters, 113, 48701 (2014)

  55. A. A. Lee, S. Kondrat, G. Oshanin and A. A. Kornyshev, “Charging Dynamics of Supercapacitors with Narrow Cylindrical Nanopores”, Nanotechnology, 25, 315401 (2014)

  56. A. A. Lee, J. C. S. Lau, T. Biskup, D. R. Kattnig and P. J. Hore, "Alternative radical pairs for cryptochrome-based magnetoreception", Journal of the Royal Society Interface, 11, 20131063 (2014)

  57. A. A. Lee, R. H. Colby and A. A. Kornyshev, “Statics and dynamics of electroactuation with single-charge-carrier ionomers.”, Journal of Physics: Condensed Matter, 25, 082203 (2013)

  58. A. A. Lee, R. H. Colby and A. A. Kornyshev, “Electroactuation with Single Charge Carrier Ionomers: The Roles of Electrostatic Pressure and Steric Strain”, Soft Matter, 9, 3767 (2013)

  59. C. C. Rochester, A. A. Lee, G. Pruessner and A. A. Kornyshev, " Interionic interactions in conducting nanoconfinement", ChemPhysChem, 14, 4121 (2013)

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