Corey Oses
Materials Science and Engineering, Johns Hopkins UniversityWork Experience
Education
Department: Mechanical Engineering and Materials Science
Thesis: Machine learning, phase stability, and disorder with the Automatic Flow Framework for Materials Discovery
DukeSpace: link
Advisor: S. Curtarolo
Department: Applied and Engineering Physics
Thesis: Plume Propagation Simulation for Pulsed Laser Deposition
Advisor: J. Brock
Journal Publications
2024
Acta Materialia
Fermi energy engineering of enhanced plasticity in high-entropy carbides
Acta Mater. 276, 120117 (2024)
Authors: K. S. Vecchio, S. Curtarolo, K. Kaufmann, T. J. Harrington, C. Oses & C. Toher
DOI: 10.1016/j.actamat.2024.120117. [PDF]Digital Discovery
Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange
Digit. Discov. , 1509–1533 (2024)
Authors: M. L. Evans, J. Bergsma, A. Merkys, C. W. Andersen, O. B. Andersson, D. Beltrán, E. Blokhin, T. M. Boland, R. Castañeda Balderas, K. Choudhary, A. Díaz Díaz, R. Domínguez García, H. Eckert, K. Eimre, M. E. Fuentes-Montero, A. M. Krajewski, J. J. Mortensen, J. M. Nápoles-Duarte, J. Pietryga, J. Qi, F. d. J. Trejo Carrillo, A. Vaitkus, J. Yu, A. C. Zettel, P. Baptista de Castro, J. Carlsson, T. F. T. Cerqueira, S. Divilov, H. Hajiyani, F. Hanke, K. Jose, C. Oses, J. Riebesell, J. Schmidt, D. Winston, C. Xie, X. Yang, S. Bonella, S. Botti, S. Curtarolo, C. Draxl, L. E. Fuentes Cobas, A. Hospital, Z.-K. Liu, M. A. L. Marques, N. Marzari, A. J. Morris, S. P. Ong, M. Orozco, K. A. Persson, K. S. Thygesen, C. Wolverton, M. Scheidgen, C. Toher, G. J. Conduit, G. Pizzi, S. Gražulis, G.-M. Rignanese & R. Armiento
DOI: 10.1039/D4DD00039K. [PDF]Nature
Disordered enthalpy-entropy descriptor for high-entropy ceramics discovery
Nature 625, 66–73 (2024)
Authors: S. Divilov†, H. Eckert†, D. Hicks†, C. Oses†, C. Toher†, R. Friedrich, M. Esters, M. J. Mehl, A. C. Zettel, Y. Lederer, E. Zurek, J.-P. Maria, D. W. Brenner, X. Campilongo, S. Filipović, W. G. Fahrenholtz, C. J. Ryan, C. M. DeSalle, R. J. Crealese, D. E. Wolfe, A. Calzolari & S. Curtarolo
† contributed equally
DOI: 10.1038/s41586-023-06786-y. [PDF]Nature Communications
Materials Design for Hypersonics
Nat. Commun. 15, 3328 (2024)
Authors: A. B. Peters, D. Zhang, S. Chen, C. Ott, C. Oses, S. Curtarolo, I. McCue, T. Pollock & S. E. Prameela
- This paper was selected for Editors' Highlight by Springer Nature (2024).
2023
Materialia
Influence of Processing on the Microstructural Evolution and Multiscale Hardness in Titanium Carbonitrides (TiCN) Produced via Field Assisted Sintering Technology
Materialia 27, 101682 (2023)
Authors: D. E. Wolfe, C. M. DeSalle, C. J. Ryan, R. E. Slapikas, R. T. Sweny, R. J. Crealese, P. A. Kolonin, S. P. Stepanoff, A. Haque, S. Divilov, H. Eckert, C. Oses, M. Esters, D. W. Brenner, W. G. Fahrenholtz, J.-P. Maria, C. Toher, E. Zurek & S. Curtarolo
DOI: 10.1016/j.mtla.2023.101682. [PDF]Computational Materials Science
aflow++: a C++ framework for autonomous materials design
Comput. Mater. Sci. 217, 111889 (2023)
Authors: C. Oses, M. Esters, D. Hicks, S. Divilov, H. Eckert, R. Friedrich, M. J. Mehl, A. Smolyanyuk, X. Campilongo, A. van de Walle, J. Schroers, A. G. Kusne, I. Takeuchi, E. Zurek, M. Buongiorno Nardelli, M. Fornari, Y. Lederer, O. Levy, C. Toher & S. Curtarolo
- This paper was selected for Editor's Choice by Elsevier (2022).
Computational Materials Science
aflow.org: a web ecosystem of databases, software and tools
Comput. Mater. Sci. 216, 111808 (2023)
Authors: M. Esters, C. Oses, S. Divilov, H. Eckert, R. Friedrich, D. Hicks, M. J. Mehl, F. Rose, A. Smolyanyuk, A. Calzolari, X. Campilongo, C. Toher & S. Curtarolo
DOI: 10.1016/j.commatsci.2022.111808. [PDF]Acta Materialia
QH-POCC: taming tiling entropy in thermal expansion calculations of disordered materials
Acta Mater. 245, 118594 (2023)
Authors: M. Esters†, A. Smolyanyuk†, C. Oses, D. Hicks, S. Divilov, H. Eckert, X. Campilongo, C. Toher & S. Curtarolo
† contributed equally
DOI: 10.1016/j.actamat.2022.118594. [PDF]2022
Nature Communications
Plasmonic high-entropy carbides
Nat. Commun. 13, 5993 (2022)
Authors: A. Calzolari, C. Oses, C. Toher, M. Esters, X. Campilongo, S. P. Stepanoff, D. E. Wolfe & S. Curtarolo
DOI: 10.1038/s41467-022-33497-1. [PDF]Angewandte Chemie
The Microscopic Diamond Anvil Cell: Stabilization of Superhard, Superconducting Carbon Allotropes at Ambient Pressure
Angew. Chem. 61(32), e202205129 (2022)
Authors: X. Wang, D. M. Proserpio, C. Oses, C. Toher, S. Curtarolo & E. Zurek
DOI: 10.1002/anie.202205129. [PDF]Electronic Structure
Roadmap on Machine Learning in Electronic Structure
Electron. Struct. 4(2), 023004 (2022)
Authors: H. J. Kulik, T. Hammerschmidt, J. Schmidt, S. Botti, M. A. L. Marques, M. Boley, M. Scheffler, M. Todorović, P. Rinke, C. Oses, A. Smolyanyuk, S. Curtarolo, A. Tkatchenko, A. P. Bartók, S. Manzhos, M. Ihara, T. Carrington, J. Behler, O. Isayev, M. Veit, A. Grisafi, J. Nigam, M. Ceriotti, K. T. Schütt, J. Westermayr, M. Gastegger, R. J. Maurer, B. Kalita, K. Burke, R. Nagai, R. Akashi, O. Sugino, J. Hermann, F. Noé, S. Pilati, C. Draxl, M. Kuban, S. Rigamonti, M. Scheidgen, M. Esters, D. Hicks, C. Toher, P. V. Balachandran, I. Tamblyn, S. Whitelam, C. Bellinger & L. M. Ghiringhelli
DOI: 10.1088/2516-1075/ac572f. [PDF]Frontiers in Physics
Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping
Front. Phys. 10, 815863 (2022)
Authors: A. G. Kusne, A. McDannald, B. DeCost, C. Oses, C. Toher, S. Curtarolo, A. Mehta & I. Takeuchi
DOI: 10.3389/fphy.2022.815863. [PDF]MRS Bulletin
High-entropy ceramics: Propelling applications through disorder
MRS Bull. 47, 194–202 (2022)
Authors: C. Toher, C. Oses, M. Esters, D. Hicks, G. N. Kotsonis, C. M. Rost, D. W. Brenner, J.-P. Maria & S. Curtarolo
DOI: 10.1557/s43577-022-00281-x. [PDF]2021
Nature Communications
Settling the matter of the role of vibrations in the stability of high-entropy carbides
Nat. Commun. 12, 5747 (2021)
Authors: M. Esters, C. Oses, D. Hicks, M. J. Mehl, M. Jahnátek, M. D. Hossain, J.-P. Maria, D. W. Brenner, C. Toher & S. Curtarolo
- This paper was selected for Editors' Highlight by Springer Nature (2021).
Advanced Materials
Entropy Landscaping of High-Entropy Carbides
Adv. Mater. 33(42), 2102904 (2021)
Authors: M. D. Hossain, T. Borman, C. Oses, M. Esters, C. Toher, L. Feng, A. Kumar, W. G. Fahrenholtz, S. Curtarolo, D. W. Brenner, J. M. LeBeau & J.-P. Maria
DOI: 10.1002/adma.202102904. [PDF]Scientific Data
OPTIMADE: an API for exchanging materials data
Sci. Data 8, 217 (2021)
Authors: C. W. Andersen†, R. Armiento†, E. Blokhin†, G. J. Conduit†, S. Dwaraknath†, M. L. Evans†, Á. Fekete†, A. Gopakumar†, S. Gražulis†, A. Merkys†, F. Mohamed†, C. Oses†, G. Pizzi†, G.-M. Rignanese†, M. Scheidgen†, L. Talirz†, C. Toher†, D. Winston†, R. Aversa, K. Choudhary, P. Colinet, S. Curtarolo, D. Di Stefano, C. Draxl, S. Er, M. Esters, M. Fornari, M. Giantomassi, M. Govoni, G. Hautier, V. Hegde, M. K. Horton, P. Huck, G. Huhs, J. Hummelshøj, A. Kariryaa, B. Kozinsky, S. Kumbhar, M. Liu, N. Marzari, A. J. Morris, A. Mostofi, K. A. Persson, G. Petretto, T. Purcell, F. Ricci, F. Rose, M. Scheffler, D. Speckhard, M. Uhrin, A. Vaitkus, P. Villars, D. Waroquiers, C. Wolverton, M. Wu & X. Yang
† contributed equally
DOI: 10.1038/s41597-021-00974-z. [PDF]Physical Review Materials
Automated coordination corrected enthalpies with AFLOW-CCE
Phys. Rev. Mater. 5, 043803 (2021)
Authors: R. Friedrich, M. Esters, C. Oses, S. Ki, M. J. Brenner, D. Hicks, M. J. Mehl, C. Toher & S. Curtarolo
DOI: 10.1103/PhysRevMaterials.5.043803. [PDF]Computational Materials Science
The AFLOW Library of Crystallographic Prototypes: Part 3
Comput. Mater. Sci. 199, 110450 (2021)
Authors: D. Hicks, M. J. Mehl, M. Esters, C. Oses, O. Levy, G. L. W. Hart, C. Toher & S. Curtarolo
DOI: 10.1016/j.commatsci.2021.110450.Physical Review Materials
Tin-pest problem as a test of density functionals using high-throughput calculations
Phys. Rev. Mater. 5, 083608 (2021)
Authors: M. J. Mehl, M. Ronquillo, D. Hicks, M. Esters, C. Oses, R. Friedrich, A. Smolyanyuk, E. Gossett, D. Finkenstadt & S. Curtarolo
DOI: 10.1103/PhysRevMaterials.5.083608. [PDF]Acta Materialia
Carbon Stoichiometry and Mechanical Properties of High Entropy Carbides
Acta Mater. 215, 117051 (2021)
Authors: M. D. Hossain†, T. Borman†, A. Kumar, X. Chen, A. Khosravani, S. R. Kalidindi, E. A. Paisley, M. Esters, C. Oses, C. Toher, S. Curtarolo, J. M. LeBeau, D. W. Brenner & J.-P. Maria
† contributed equally
DOI: 10.1016/j.actamat.2021.117051. [PDF]2020
Nature Communications
On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning
Nat. Commun. 11, 5966 (2020)
Authors: A. G. Kusne†, H. Yu†, C. Wu, H. Zhang, J. Hattrick-Simpers, B. DeCost, S. Sarker, C. Oses, C. Toher, S. Curtarolo, A. V. Davydov, R. Agarwal, L. A. Bendersky, M. Li, A. Mehta & I. Takeuchi
† contributed equally
DOI: 10.1038/s41467-020-19597-w. [PDF]npj Computational Materials
Discovery of novel high-entropy ceramics via machine learning
npj Comput. Mater. 6, 42 (2020)
Authors: K. Kaufmann, D. Maryanovsky, W. M. Mellor, C. Zhu, A. S. Rosengarten, T. J. Harrington, C. Oses, C. Toher, S. Curtarolo & K. S. Vecchio
DOI: 10.1038/s41524-020-0317-6. [PDF]Nature Reviews Materials
High-entropy ceramics
Nat. Rev. Mater. 5, 295–309 (2020)
Authors: C. Oses, C. Toher & S. Curtarolo
- This paper was highlighted as a "hot paper" by Web of Science (Clarivate Analytics) (November 16, 2021).
2019
Acta Materialia
Metallic glasses for biodegradable implants
Acta Mater. 176, 297–305 (2019)
Authors: D. C. Ford, D. Hicks, C. Oses, C. Toher & S. Curtarolo
DOI: 10.1016/j.actamat.2019.07.008. [PDF]npj Computational Materials
Predicting Superhard Materials via a Machine Learning Informed Evolutionary Structure Search
npj Comput. Mater. 5, 89 (2019)
Authors: P. Avery, X. Wang, C. Oses, E. Gossett, D. M. Proserpio, C. Toher, S. Curtarolo & E. Zurek
DOI: 10.1038/s41524-019-0226-8. [PDF]npj Computational Materials
Unavoidable disorder and entropy in multi-component systems
npj Comput. Mater. 5, 69 (2019)
npj Computational Materials
Coordination corrected ab initio formation enthalpies
npj Comput. Mater. 5, 59 (2019)
Authors: R. Friedrich, D. Usanmaz, C. Oses, A. R. Supka, M. Fornari, M. Buongiorno Nardelli, C. Toher & S. Curtarolo
DOI: 10.1038/s41524-019-0192-1. [PDF]Physical Review Materials
AFLOW-QHA3P: Robust and automated method to compute thermodynamic properties of solids
Phys. Rev. Mater. 3, 073801 (2019)
Authors: P. Nath, D. Usanmaz, D. Hicks, C. Oses, M. Fornari, M. Buongiorno Nardelli, C. Toher & S. Curtarolo
DOI: 10.1103/PhysRevMaterials.3.073801. [PDF]2018
Journal of Chemical Information and Modeling
AFLOW-CHULL: Cloud-oriented platform for autonomous phase stability analysis
J. Chem. Inf. Model. 58(12), 2477–2490 (2018)
Authors: C. Oses, E. Gossett, D. Hicks, F. Rose, M. J. Mehl, E. Perim, I. Takeuchi, S. Sanvito, M. Scheffler, Y. Lederer, O. Levy, C. Toher & S. Curtarolo
DOI: 10.1021/acs.jcim.8b00393. [PDF]MRS Bulletin
Data-driven design of inorganic materials with the Automatic Flow Framework for Materials Discovery
MRS Bull. 43(9), 670–675 (2018)
Nature Communications
High-entropy high-hardness metal carbides discovered by entropy descriptors
Nat. Commun. 9, 4980 (2018)
Authors: P. Sarker†, T. J. Harrington†, C. Toher, C. Oses, M. Samiee, J.-P. Maria, D. W. Brenner, K. S. Vecchio & S. Curtarolo
† contributed equally
DOI: 10.1038/s41467-018-07160-7. [PDF]npj Computational Materials
Machine learning modeling of superconducting critical temperature
npj Comput. Mater. 4, 29 (2018)
Authors: V. Stanev, C. Oses, A. G. Kusne, E. Rodriguez, J. Paglione, S. Curtarolo & I. Takeuchi
DOI: 10.1038/s41524-018-0085-8. [PDF]Computational Materials Science
AFLOW-ML: A RESTful API for machine-learning prediction of materials properties
Comput. Mater. Sci. 152, 134–145 (2018)
Authors: E. Gossett, C. Toher, C. Oses, O. Isayev, F. Legrain, F. Rose, E. Zurek, J. Carrete, N. Mingo, A. Tropsha & S. Curtarolo
- This paper was selected for Editor's Choice by Elsevier (2018).
Acta Crystallographica Section A
AFLOW-SYM: platform for the complete, automatic and self-consistent symmetry analysis of crystals
Acta Cryst. A 74, 184–203 (2018)
Authors: D. Hicks, C. Oses, E. Gossett, G. Gomez, R. H. Taylor, C. Toher, M. J. Mehl, O. Levy & S. Curtarolo
DOI: 10.1107/S2053273318003066. [PDF]2017
Inorganic Chemistry
The structure and composition statistics of 6A binary and ternary structures
Inorg. Chem. 57(2), 653–667 (2017)
Authors: A. Hever, C. Oses, S. Curtarolo, O. Levy & A. Natan
DOI: 10.1021/acs.inorgchem.7b02462. [PDF]Computational Materials Science
AFLUX: The LUX materials search API for the AFLOW data repositories
Comput. Mater. Sci. 137, 362–370 (2017)
Authors: F. Rose, C. Toher, E. Gossett, C. Oses, M. Buongiorno Nardelli, M. Fornari & S. Curtarolo
- This paper was selected for Editor's Choice by Elsevier (2017).
Nature Communications
Universal Fragment Descriptors for Predicting Properties of Inorganic Crystals
Nat. Commun. 8, 15679 (2017)
Authors: O. Isayev†, C. Oses†, C. Toher, E. Gossett, S. Curtarolo & A. Tropsha
† contributed equally
DOI: 10.1038/ncomms15679. [PDF]Physical Review Materials
Combining the AFLOW GIBBS and elastic libraries to efficiently and robustly screening thermomechanical properties of solids
Phys. Rev. Mater. 1, 015401 (2017)
Authors: C. Toher, C. Oses, J. J. Plata, D. Hicks, F. Rose, O. Levy, M. de Jong, M. Asta, M. Fornari, M. Buongiorno Nardelli & S. Curtarolo
DOI: 10.1103/PhysRevMaterials.1.015401. [PDF]Acta Materialia
A Computational High-Throughput Search for New Ternary Superalloys
Acta Mater. 122, 438–447 (2017)
Authors: C. Nyshadham, C. Oses, J. E. Hansen, I. Takeuchi, S. Curtarolo & G. L. W. Hart
DOI: 10.1016/j.actamat.2016.09.017. [PDF]Science Advances
Accelerated Discovery of New Magnets in the Heusler Alloy Family
Sci. Adv. 3(4), e1602241 (2017)
Authors: S. Sanvito, C. Oses, J. Xue, A. Tiwari, M. Žic, T. Archer, P. Tozman, M. Venkatesan, J. M. D. Coey & S. Curtarolo
DOI: 10.1126/sciadv.1602241. [PDF]2016
Physical Review X
High-Throughput Computation of Thermal Conductivity of High-Temperature Solid Phases: The Case of Oxide and Fluoride Perovskites
Phys. Rev. X 6(4), 041061 (2016)
Authors: A. van Roekeghem, J. Carrete, C. Oses, S. Curtarolo & N. Mingo
DOI: 10.1103/PhysRevX.6.041061. [PDF]Chemistry of Materials
Modeling Off-Stoichiometry Materials with a High-Throughput Ab-Initio Approach
Chem. Mater. 28(18), 6484–6492 (2016)
2015
Computational Materials Science
The AFLOW Standard for High-Throughput Materials Science Calculations
Comput. Mater. Sci. 108A, 233–238 (2015)
Authors: C. E. Calderon, J. J. Plata, C. Toher, C. Oses, O. Levy, M. Fornari, A. Natan, M. J. Mehl, G. L. W. Hart, M. Buongiorno Nardelli & S. Curtarolo
- This paper was selected for Editor's Choice by Elsevier (2015).
Chemistry of Materials
Materials Cartography: Representing and Mining Materials Space Using Structural and Electronic Fingerprints
Chem. Mater. 27(3), 735–743 (2015)
Authors: O. Isayev, D. Fourches, E. N. Muratov, C. Oses, K. M. Rasch, A. Tropsha & S. Curtarolo
- This paper was one of the top 10 most highly downloaded papers for the month of January 2015 by the American Chemical Society (2015).
- This paper was selected for Editors' Choice by the American Chemical Society (2015).
Book Publications
2019
Automated computation of materials properties
Materials Informatics: Methods, Tools and Applications, Ch. 7
2018
Machine learning and high-throughput approaches to magnetism
Handbook of Materials Modeling. Volume 2 Applications: Current and Emerging Materials
Authors: S. Sanvito, M. Žic, J. Nelson, T. Archer, C. Oses & S. Curtarolo
DOI: 10.1007/978-3-319-50257-1_108-1. [PDF]The AFLOW Fleet for Materials Discovery
Handbook of Materials Modeling. Volume 1 Methods: Theory and Modeling
Authors: C. Toher, C. Oses, D. Hicks, E. Gossett, F. Rose, P. Nath, D. Usanmaz, D. C. Ford, E. Perim, C. E. Calderon, J. J. Plata, Y. Lederer, M. Jahnátek, W. Setyawan, S. Wang, J. Xue, K. M. Rasch, R. V. Chepulskii, R. H. Taylor, G. Gomez, H. Shi, A. R. Supka, R. Al Rahal Al Orabi, P. Gopal, F. T. Cerasoli, L. Liyanage, H. Wang, I. Siloi, L. A. Agapito, C. Nyshadham, G. L. W. Hart, J. Carrete, F. Legrain, N. Mingo, E. Zurek, O. Isayev, A. Tropsha, S. Sanvito, R. M. Hanson, I. Takeuchi, M. J. Mehl, A. N. Kolmogorov, K. Yang, P. D'Amico, A. Calzolari, M. Costa, R. De Gennaro, M. Buongiorno Nardelli, M. Fornari, O. Levy & S. Curtarolo
DOI: 10.1007/978-3-319-42913-7_63-2. [PDF]Teaching Experience
EN.500.113: Gateway Computing: Python, Johns Hopkins University
EN.510.666: Introduction to Computational Materials Modeling, Johns Hopkins University
ME 555: Applications of Artificial Intelligence in Materials, Duke University Department of Mechanical Engineering and Materials Science
ME 555: Computational Materials Science by Examples and Applications, Duke University Department of Mechanical Engineering and Materials Science
ME 221: Structure and Properties of Solids, Duke University Department of Mechanical Engineering and Materials Science
- Best Teaching Assistant Award, August 14, 2015
Service
Data-Driven Materials Modeling Workshop
Co-Organizers: B. Bukowski & T. Curk
- Organizer and Presenter at Johns Hopkins University, Baltimore, Maryland — May 29–31, 2024.
- Data-Driven Thermodynamic Modeling for Materials Discovery recording: youtu.be/kZj3zQkBAKg
Foundations to Futures: Materials Data and AI
Co-Chairs: D. Audus & F. Sen
Conference Co-Chair at the Materials Research Data Alliance (MaRDA) 2024 Annual Meeting, Baltimore, Maryland — February 20–22, 2024.
Focus Session: Computational Design, Understanding and Discovery of Novel Materials
Co-Chairs: E. Jankowski, R. Sundararaman & D. Usanmaz
Session Chair for the March Meeting of the American Physical Society, Minneapolis, Minnesota — March 3–8, 2024.
AI, Data Science — Developing the Role for Sustainable Energy in Hopkins' Expansion and Vision
Co-Chair: P. Clancy
Session Co-Chair at the ROSEI 2024 Summit, Baltimore, Maryland — January 17, 2024.
AFLOW School: Integrated infrastructure for computational materials discovery
Co-Organizers: C. Toher, D. Hicks, M. Esters, R. Friedrich, E. Gossett, A. Smolyanyuk, H. Eckert, S. Divilov, F. Rose, M. J. Brenner & S. Curtarolo
Presenter for the Machine Learning for Materials Research Bootcamp of the University of Maryland/NIST/MRS, College Park, Maryland — August 10, 2023.
- Organizer and Presenter at Johns Hopkins University, Baltimore, Maryland — September 21, 2022.
- Introduction and AFLOW-ML: Machine Learning recording: youtu.be/Xj5BGuFC9ew
Presenter for the Machine Learning for Materials Research Bootcamp of the University of Maryland/NIST/MRS, College Park, Maryland — August 11, 2022.
Co-Organizer and Presenter at the East African Institute for Fundamental Research, University of Rwanda, Kigali, Rwanda — February 21–24, 2022.
- Co-Organizer and Presenter at the Technische Universität (TU) Dresden and Helmholtz-Zentrum Dresden-Rossendorf — September 6–10, 2021.
- Introduction to Density Functional Theory and VASP recording: youtu.be/_RsQH3TY7kI
- AFLOW-CHULL: Thermodynamics recording: youtu.be/zcY7gTZIB-Y
- AFLOW-POCC: Disorder recording: youtu.be/lcDSYiF4AS4
- Co-Organizer and Presenter at the University of Virginia, Charlottesville, Virginia — August 17, 2021.
- AFLOW-CHULL and AFLOW-CCE: Thermodynamics recording: youtu.be/cLhOcN1sQ7M
- Presenter for the Machine Learning for Materials Research Bootcamp of the University of Maryland/NIST, College Park, Maryland — July 29, 2021.
- AFLOW-ML: Machine Learning recording: youtu.be/uFQ-lyTaxCc
- Co-Organizer and Presenter at Texas A&M University, College Station, Texas — July 12–15, 2021.
- Introduction to Density Functional Theory and VASP recording: youtu.be/KXnJGdVgosA
- AFLOW-CHULL and AFLOW-CCE: Thermodynamics recording: youtu.be/ElaniAcrbhU
- AFLOW-POCC: Disorder recording: youtu.be/D_cfHIlpBiA
Session Chair for the Virtual Spring Meeting of the Materials Research Society — April 17, 2021.
- Presenter for the Materials 4.0 Summer School 2020 at the Dresden Center for Computational Materials Science (DCMS), Technische Universität (TU) Dresden — August 18, 2020.
- AFLOW-CHULL: Thermodynamics recording: youtu.be/ncm356YNBVc
- Presenter for the Machine Learning for Materials Research Bootcamp & Workshop on Machine Learning Microscopy Data of the University of Maryland/NIST, College Park, Maryland — July 23, 2020.
- AFLOW-ML: Machine Learning recording: youtu.be/x2qeBtOXues
- Co-Organizer and Presenter at Texas A&M University, College Station, Texas — June 16–18, 2020.
- Introduction to Density Functional Theory and VASP recording: youtu.be/ChySAfo2w7g
- AFLOW-CHULL: Thermodynamics recording: youtu.be/9Sa8D4inJ5w
- AFLOW-POCC: Disorder recording: youtu.be/xr-mU-1ShQQ
Presenter for the Machine Learning for Materials Research Bootcamp & Workshop on Autonomous Materials Research of the University of Maryland/NIST, College Park, Maryland — August 05, 2019.
Co-Organizer and Presenter at the University of Pennsylvania, Philadelphia, Pennsylvania — May 03, 2019.
Co-Organizer and Presenter at the North Carolina State University, Raleigh, North Carolina — March 12, 2019.
Co-Organizer and Presenter at Carnegie Mellon University, Pittsburgh, Pennsylvania — January 21, 2019.
Presenter for the Machine Learning for Materials Research Bootcamp & Workshop on Machine Learning Quantum Materials of the University of Maryland/NIST/Moore Foundation, Institute for Bioscience & Biotechnology Research in Gaithersburg, Maryland — August 02, 2018.
Press and News Releases
- This press release is featured on Phys.org, ScienceDaily, SciTechDaily, and Tribonet.
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- This press release is featured on AAAS EurekAlert!, Phys.org, and ScienceDaily.
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Honors and Awards
- Published in the past two years and received enough citations in July/August 2021 to place it in the top 0.1% of papers in the academic field of Materials Science
- Awarded by Peter Meinig (Past Chairman of the Board of Trustees at Cornell University)