Conferences

Upcoming Events

  1. CECAM – Density Functional Theory and Artificial Intelligence learning from each other, CECAM-HQ-EPFL, Lausanne, Switzerland, March 3–6, 2025.
  2. Plenary lecture at Modeling and Design of Molecular Materials 2025 (MDMM), Wroclaw, Poland, September 7–11, 2025.
  3. 3rd International Symposium on Machine Learning in Quantum Chemistry (SMLQC), the Strong Hall of the University of Tennessee campus, October 5–7, 2025.

Organized and tutorial workshops

Events as a co-organizer or scientific adviser or co-chair:

  1. Tutorial lecturer: Modern computational chemistry and AI with MLatom. 2024 Workshop on Applications of Machine Learning and Artificial Intelligence for Physics and Chemistry Problems. NCTS Physics Lecture Hall, 4th Floor, Cosmology Hall, NTU, Taipei, November 8–9, 2024.
  2. Tutorial lecturer: AI Computational Chemistry Workshop. Chiang Mai University, Thailand, November 4–5, 2024.
  3. Co-chairing. of Session on Machine learning and data-driven approaches. Lecture Universal and Updatable Artificial Intelligence-Enhanced Quantum Chemical Foundational Models. The 11th Congress of International Society of Theoretical Chemical Physics (ISTCP-2024), Qingdao, China, October 13–18, 2024.
  4. Lecturer (Lecture: ML potentials I & Tutorial: ML potentials): Machine Learning for Chemistry 2024, CZS Summer School 2024, Karlsruhe, Germany, September 9–13, 2024. (lectures | Jupyter notebooks)
  5. Co-organizer and lecturer at the XACSW-2024: Chemical Bonding and Al Molecular Simulations. Zhengzhou University, Zhengzhou, China, July 1–5, 2024.
  6. Lecturer in ML Chemical Physics Simulations Done Easy with MLatom@XACS. Aix Marseille University, Marseille, France, January 24, 2024.
  7. Lecturer in Practical introduction to machine learning in chemical physics with MLatom@XACS. Nicolaus Copernicus University, December 6, 2023.
  8. Co-organizer of International Symposium on Machine Learning in Quantum Chemistry 2023, Uppsala, Sweden, November 29–December 1, 2023.
  9. Co-organizer and lecturer at the Second Xiamen Atomistic Computing Suite Workshop, Xiamen, China, May 12–16, 2023.
  10. Scientific adviser for MLQCDyn. Paris, France, September 5–30, 2022.
  11. Co-organizer of CECAM school Machine Learning and Quantum Computing for Quantum Molecular Dynamics [MLQCDyn], Paris, France, September 5–9, 2022.
  12. Co-organizer and lecturer at the First Xiamen Atomistic Computing Suite Workshop, Xiamen, China, April 22–24, 2022.
  13. Co-organizer of International Symposium on Machine Learning in Quantum Chemistry, Xiamen, China, November 12–14, 2021.
  14. Co-sharing of Session on Machine learning and data-driven approaches in chemical physics. Lecture Quantum Chemistry Assisted by Machine Learning at 10th Triennial Congress of the International Society for Theoretical Chemical Physics, Tromsø, Norway, July 11–17, 2019.

Plenary & Invited Lectures and Talks

  1. Invited speaker: AI-enhanced computational chemistry via better software, ML, DFT and semi-empirical methods. 2024 Workshop on Applications of Machine Learning and Artificial Intelligence for Physics and Chemistry Problems. NCTS Physics Lecture Hall, 4th Floor, Cosmology Hall, NTU, Taipei, November 8–9, 2024.
  2. Keynote speaker. Universal and Updatable Artificial Intelligence-Enhanced Quantum Chemical Foundational Models. Session 7: Computational Materials Science and Condensed Matter, Modeling and Simulations, Data-driven Material Modeling, and Artificial Intelligence at SMARTMAT@2024, November 5–8, 2024, at The Empress Convention Center in Chiang Mai, Thailand.
  3. Development of efficient machine learning-based methods for atomistic simulations using our package MLatom. Thailand-Japan Symposium for Chemistry, Chiang Mai University, Thailand, November 3, 2024.
  4. Invited lecture. Practically useful machine learning for nonadiabatic and quantum dynamics and spectra simulations. Dynamics, Spectroscopy, Machine Learning (DSML-24), Hangzhou, China, October 6–9, 2024.
  5. Machine learning for nonadiabatic and quantum dynamics. MolSSI workshop: “Machine-Learning in Quantum and Nonadiabatic Dynamics“, hybrid, August 15–16, 2024. (abstract | slides | video)
  6. Platform for AI-Enhanced Computational Chemistry Simulations and Workflows: MLatom@XACS. The 34th Chinese Chemical Society Congress, Guangdong, China, June 15–18, 2024.
  7. AI-Enhanced Computational Chemistry Simulations and Workflows. The 2024 International Symposium on Computational Molecular Science and Machine Learning, Shanghai, China, June 28–July 1, 2024.
  8. AI simulations in chemical compound space. Chemical Compound Space Conference (CCSC2024), Heidelberg, Germany, May 21–24, 2024.
  9. From fast potentials for dynamics to learning dynamics. Machine Learning in Chemical and Materials Sciences 2024. Virtual, May 20–23, 2024.
  10. Pavlo O. Dral. Extending the time and system-size scales of accurate quantum chemical calculations with MLatom@XACS. Workshop “HPC for quantum chemistry”, Aix-Marseille University, April 15, 2024. (virtual talk)
  11. Pavlo O. Dral. Towards more accessible excited-state simulations with AI. “Virtual International Seminar on Theory Advancement” (VISTA), Seminar 65. (video and abstract)
  12. Pavlo O. Dral. AI-enhanced chemical physics simulations. Session D60: Machine Learning of Molecules and Materials: Chemical Space and Dynamics. APS March Meeting. 2024 meeting, Minneapolis, USA, March 4–8, 2024. (online lectures for attendees)
  13. Pavlo O. Dral. AI-enhanced computational chemistry for routine high-accuracy and fast simulations. MLChem2024. Workshop on Machine Learning for Chemistry, Aix Marseille University, Marseille, France, January 24, 2024.
  14. Pavlo O. Dral. Towards practical AI-enhanced computational chemistry. The Path of Quantum Chemistry into the 21st Century: Symposium Celebrating Prof. Roland Lindh’s 65th Birthday, ETH Zürich, Switzerland, January 16–18, 2024.
  15. Pavlo O. Dral. AI-enhanced computational chemistry. Nicolaus Copernicus University, December 7, 2023.
  16. Pavlo O. Dral. 10-year journey from proof-of-concept to advanced AI models revamping chemical research. University Erlangen-Nuremberg, December 4, 2023.
  17. Pavlo O. Dral. Towards practical AI-enhanced computational chemistry. International Symposium on Machine Learning in Quantum Chemistry 2023, Uppsala, Sweden, November 29–December 1, 2023.
  18. Pavlo O. Dral. Accelerating and improving quantum chemistry and dynamics with artificial intelligence. Seminar on Challenges and Opportunities of Theoretical and Computational Chemistry in the New Era (SCO-TCCNE). Hanzhong, China, August 3–7, 2023.
  19. Pavlo O. Dral. 10-year journey from proof-of-concept to advanced AI models revamping chemical research. Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr, Germany, July 3, 2023.
  20. Invited contribution: Pavlo O. Dral. Accelerating and improving quantum chemistry and dynamics with artificial intelligence. The 17th International Congress of Quantum Chemistry. Bratislava, Slovakia, June 26–July 1, 2023. (slides)
  21. Pavlo O. Dral. Making quantum chemistry more accessible with machine learning. The 11th OpenMolcas Developers Meeting, Bologna, Italy, June 13–16, 2023.
  22. Pedagogical lecture: Pavlo O. Dral. Practical Introduction to Artificial Intelligence in Quantum Chemistry. 3rd Quantum International Frontiers 2023: Density and Density Matrix-driven Electronic Structure Methods. Łódź, Poland, June 21–24, 2023.
  23. Pavlo O. Dral. Accelerating and improving quantum chemistry and dynamics with artificial intelligence​. Fourth Symposium for Young Scholars on Electronic Structure Theory and Methods, Changchun, China, April 21–24, 2023.
  24. Keynote lecture: Pavlo O. Dral. Accelerating and improving quantum chemistry and dynamics with artificial intelligence​. The 10th edition of the conference of the Asia Pacific Association of Theoretical and Computational Chemists (APATCC-10). International Centre for Interdisciplinary Science and Education (ICISE), Quy Nhon, Vietnam, February 19–23, 2023.
  25. Pavlo O. Dral. Accelerating and Improving Computational Chemistry with Artificial Intelligence/Machine Learning. Tuesday lectures @ AI4Research Uppsala University. Online (Zoom link: https://uu-se.zoom.us/j/64230133243), October 25, 2022. (video)
  26. Pavlo O. Dral. Accelerating and Improving Computational Chemistry with Artificial Intelligence/Machine Learning. The Warwick Centre for Predictive Modelling seminar series. Online, October 24, 2022.
  27. Pavlo O. Dral. Accelerating and Improving Computational Chemistry with Artificial Intelligence/Machine Learning. MLQCDyn. Paris, France, September 5–30, 2022.
  28. Michael Gastegger (on site) and Pavlo O. Dral (online). Lecture 5: ML molecular dynamics: ground state at CECAM school Machine Learning and Quantum Computing for Quantum Molecular Dynamics [MLQCDyn], Paris, France, September 5–9, 2022.
  29. Pavlo O. Dral (online) with Max Pinheiro Jr. on site. Practical session 3: First steps into ML at CECAM school Machine Learning and Quantum Computing for Quantum Molecular Dynamics [MLQCDyn], Paris, France, September 5–9, 2022. (tutorial)
  30. Pavlo O. Dral. Lecture 3: General introduction to ML at CECAM school Machine Learning and Quantum Computing for Quantum Molecular Dynamics [MLQCDyn], Paris, France, September 5–9, 2022. (slides)
  31. Pavlo O. Dral. Accelerating and Improving Computational Chemistry with Artificial Intelligence/Machine Learning. Artificial Intelligence/Machine Learning across the Chemical Sciences. A webinar organized by the International Younger Chemists Network (IYCN) and the International Union of Pure and Applied Chemistry (IUPAC), online, July 29, 2022.
  32. Pavlo O. Dral. Quantum Chemistry Assisted by Machine Learning. The 12th Triennial Congress of the World Association of Theoretical and Computational Chemists, “WATOC 2020”, Vancouver, Canada, July 3–8, 2022. Did not participate due to travel restrictions.
  33. Plenary lecture: Pavlo O. Dral. Accelerating and Improving Computational Chemistry with Artificial Intelligence/Machine Learning. ANSCSE25, the 25th International Annual Symposium on Computational Science and Engineering, Thailand, June 8–11, 2022. Online.
  34. Pavlo O. Dral. Quantum Chemistry Assisted by Machine Learning. Pacifichem 2020 (The 2020 International Chemical Congress of Pacific Basin Societies), Symposium 49: Innovative Computational Chemistry Powered by Big Data and Machine Learning, Honolulu, Hawaii, USA, December 15–20, 2021.
  35. Pavlo O. Dral. Machine Learning and Semiempirical Methods for Nonadiabatic Dynamics. Pacifichem 2020 (The 2020 International Chemical Congress of Pacific Basin Societies), Symposium 201: Modeling Exciton and Charge Dynamics in Molecules and Clusters Toward Optoelectronic Applications, Honolulu, Hawaii, USA, December 15–20, 2021.
  36. Pavlo O. Dral. Quantum Chemistry Assisted by Machine Learning. International Symposium on Machine Learning in Quantum Chemistry, Xiamen, China, November 12–14, 2021. (video)
  37. Plenary lecture: Pavlo O. Dral. Quantum Chemistry Assisted by Machine Learning. The XXI Brazilian Symposium on Theoretical Chemistry, online, November 8–12, 2021.
  38. Pavlo O. Dral. Quantum Chemistry Assisted by Machine Learning. Machine Learning and Informatics for Chemistry and Materials, Telluride Science Research Center, online, September 27–October 1, 2021.
  39. Pavlo O. Dral. Efficient excited-state simulations with machine learning and semiempirical methods. Workshop on Structure, Dynamics, Spectroscopy, Hangzhou Dianzi University, Hangzhou, July 1-4, 2021.
  40. Pavlo O. Dral. Quantum Chemistry Assisted by Machine Learning. The 32nd Chinese Chemical Society Congress, Zhuhai, Guangdong, China, April 19–22, 2021.
  41. Pavlo O. Dral. Quantum Chemistry Assisted by Machine Learning. TYC Symposium: Machine Learning: application to Chemical Reactions, Zoom https://ucl.zoom.us/j/96696928921?pwd=a3htRlVabGJhd3c3UnUzYWxCc3p3Zz09 (Meeting ID: 966 9692 8921, Passcode: TYCSymp), February 25, 2021.
  42. Pavlo O. Dral. Making quantum chemistry more efficient with semiempirical and machine learning approaches. The 2020 International Workshop on Frontiers of Theoretical and Computational Physics and Chemistry (WFTCPC’ 20), Shenzhen, Guangdong, China, December 4–7, 2020.
  43. Pavlo O. Dral. Machine Learning and Semiempirical Methods for Nonadiabatic Dynamics. The 11th Xiamen Workshop on Surface Chemistry: Excited-state Electronic Structure and Dynamics Theories of Complex Systems, Xiamen, China, December 11–14, 2019.
  44. Pavlo O. Dral. Machine Learning and Semiempirical Methods for Nonadiabatic Dynamics. International Conference on Theoretical and High Performance Computational Chemistry 2019 (CT-HPCC 2019), Guiyang, China, November 2–5, 2019.
  45. Invited talk and co-chairing: Pavlo O. Dral. Quantum Chemistry Assisted by Machine Learning. 10th Triennial Congress of the International Society for Theoretical Chemical Physics, Session on Machine learning and data-driven approaches in chemical physics, Tromsø, Norway, July 11–17, 2019. (abstract)
  46. Pavlo O. Dral, Xin Wu, Walter Thiel. ODMx: New Consistent and Robust Semiempirical Methods. Electronic Structure and Dynamics of Complex Systems, Beijing, China, April 25–30, 2019.
  47. Pavlo O. Dral, Xin Wu, Walter Thiel. The ODMx Methods: New Consistent Semiempirical Methods. Symposium in honor of Tim Clark’s 70th birthday, Erlangen, Germany, April 11, 2019.
  48. Pavlo O. Dral. Talk in the workshop: Accelerating Nonadiabatic Excited-State Dynamics with Machine Learning. Sackler-CECAM school and workshop on Frontiers in Molecular Dynamics: Machine Learning, Deep Learning and Coarse Graining, Tel Aviv, Israel, October 8–12, 2018.
  49. Pavlo O. Dral. Lecture in the school: ML Introduction, Kernel Ridge Regression (KRR). Sackler-CECAM school and workshop on Frontiers in Molecular Dynamics: Machine Learning, Deep Learning and Coarse Graining, Tel Aviv, Israel, October 8–12, 2018.
  50. Pavlo O. Dral. Lecture in the school: Machine Learning (ML) introduction. Sackler-CECAM school and workshop on Frontiers in Molecular Dynamics: Machine Learning, Deep Learning and Coarse Graining, Tel Aviv, Israel, October 8–12, 2018.
  51. Pavlo O. Dral, Machine Learning for Accelerating Quantum Chemical Simulations II. College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China, September 20, 2018.
  52. Pavlo O. Dral, Machine Learning for Accelerating Quantum Chemical Simulations. College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China, September 19, 2018.
  53. Pavlo O. Dral, Semiempirical Quantum Chemical Methods for Efficient Simulations. College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, China, September 18, 2018.
  54. Pavlo O. Dral, Semiempirical Quantum Chemical Methods: Developments and Validation. Weizmann Institute of Science, Rehovot, Israel, August 1, 2018.
  55. Pavlo O. Dral, Machine Learning and Semiempirical Quantum Chemical Methods with Improved Accuracy. Israel, Technion, Haifa, July 29, 2018
  56. Pavlo O. Dral, Machine Learning and Semiempirical Quantum Chemical Methods with Improved Accuracy. Israel, The Hebrew University of Jerusalem, Jerusalem, July 30, 2018
  57. Pavlo O. Dral, Machine Learning and Semiempirical Quantum Chemical Methods with Improved Accuracy. Israel, Tel-Aviv University, Tel Aviv, August 2, 2018.
  58. Pavlo O. Dral, From Semiempirical Quantum Chemical to Very Accurate Machine Learning Methods. Workshop: Modern Approaches to Coupling Scales In Materials Simulations: From Electronic Structure to Applications via Coarse Graining and Machine Learning, Lenggries, Germany, July 2–4, 2018.
  59. Pavlo O. Dral, Towards Reliable Machine Learning for Computational Chemistry and Perspectives for ML Excited-State Molecular Dynamics. Institut de Chimie Radicalaire – Aix Marseille University, Marseille, France, October 25, 2017. (abstract)
  60. Pavlo O. Dral, Reliable Machine Learning for Calculations of Potential Energy Surfaces. TROVE meeting, DESY, Hamburg, February 22, 2017.
  61. Pavlo O. Dral, Towards Reliable Machine Learning for Calculating Quantum Chemical Energies. Institut für Theoretische Chemie und Computerchemie, Heinrich-Heine Universität, Düsseldorf, January 19, 2017.
  62. Pavlo O. Dral, Fast Simulations of Excited States at Different Scales. Excited States Simulations: Bridging Scales workshop, Marseille, France, November 7–10, 2016. (abstract)

Talks

See above the list of invited lectures and talks. Here only contributed talks are listed.

  1. Pavlo O. Dral. Enabling accurate, fast, and out-of-the-box simulations of organic compounds with artificial intelligence. The 16th International Symposium for Chinese Organic Chemists (ISCOC), Beijing, China, August 28–30, 2023.
  2. Pavlo O. Dral. Quantum Chemistry Assisted by Machine Learning. The 2nd Quantum International Frontiers, Shanghai, China, November 18–22, 2019.
  3. Pavlo O. Dral, Towards Reliable Machine Learning for Computational Chemistry. 8th Young Chemists’ Symposium Ruhr 2017, Mülheim an der Ruhr, Germany, October 12, 2017.
  4. Pavlo O. Dral, Walter Thiel, Towards Next-Generation Semiempirical QM Methods and Reliable Machine Learning-Based Techniques. The 11th European Conference on Theoretical and Computational Chemistry, Barcelona, Spain, September 4–7, 2017.
  5. Pavlo O. Dral, Alec Owens, Walter Thiel, Reliable Machine Learning for Calculating Quantum Mechanical Energies. The 53rd Symposium on Theoretical Chemistry “Big Data in Chemistry: From Molecular Structure to Condensed Phase Dynamics” (STC 2017), Basel, Switzerland, August 21–25, 2017. (abstract)
  6. Pavlo O. Dral, Machine Learning for Predicting Accurate Quantum Chemical Energies. 2016 AIChE Annual Meeting, San Francisco, USA, November 13–18, 2016. (abstract)
  7. Pavlo O. Dral, Walter Thiel, The Quest for Accurate Semiempirical Methods. The 29th Molecular Modeling Workshop 2015, Erlangen, Germany, March 9–11, 2015; p. 33. (abstract)
  8. Pavlo O. Dral, Timothy Clark, UNO–CAS Calculations of Band Gaps of Carbon Systems. Klausurtagung des SFB 953, Bad Staffelstein, Germany, April 27–29, 2012.
  9. Pavlo O. Dral, Timothy Clark, Application of Semiempirical UNO–CI and CI Methods in Nanoelectronics. The 26th Molecular Modelling Workshop, Erlangen, Germany, March 12–14, 2012; p. 39. (abstract)
  10. Pavlo O. Dral, Timothy Clark, Modeling Molecular Electronic Properties with Semiempirical UNO–CAS. The 25th Molecular Modelling Workshop, Erlangen, Germany, April 4–6, 2011; p. 25. (abstract)
  11. Pavlo O. Dral, Tatyana E. Shubina, Andreas Hirsch, Timothy Clark, Hydrogenation of Fullerene C60: A Theoretical Investigation. The 13th JungChemikerForum Spring Symposium, Erlangen, Germany, March 23–26, 2011; p. 36.
  12. Pavlo O. Dral, Andrey A. Fokin, Theoretical Modeling of Alkane C-H Substitutions with Nitronium Cation Complexes. The 2nd International (4th All-Ukrainian) Theoretical and Practical Conference of Students, Postgraduates and Young Scientists in Chemistry and Chemical Technology, Kiev, Ukraine, April 22–24, 2009; p. 58.
  13. Pavlo O. Dral, Andrey A. Fokin, Quantum-Mechanical Computations of Alkane Nitrolysis. The 1st International (3rd All-Ukrainian) Theoretical and Practical Conference of Students, Postgraduates and Young Scientists in Chemistry and Chemical Technology, Kiev, Ukraine, April 23–25, 2008.
  14. Pavlo O. Dral, Quantum-Mechanical Computations of Alkane Nitrolysis. Innovation in Science and Technology, Kiev, Ukraine, March 25, 2008; p. 156.