Michael Tynes

  • Program Year: 1
  • Academic Institution: University of Chicago
  • Field of Study: Computer Science
  • Academic Advisor: Ian Foster
  • Practicum(s): Practicum Not Yet Completed
  • Degree(s):
    M.S. Data Science, Fordham University, 2020; B.S. Psychology, Fordham University, 2017
  • Personal URL: http://miketynes.github.io

Publications

[1] Tynes, M., Gao, W., Burrill, D.J. Batista, E.R., Perez, D., Yang, P., and Lubbers, N. "Pairwise difference regression for uncertainty quantification and candidate selection." Journal of Chemical Information and Modelling. 61, 8, 3846–3857 (2021). (2019 IF: 4.5) https://doi.org/10.1021/acs.jcim.1c00670

[2] Schrier, J., Tynes, M., and Cain, L. "Determining the Activity Series with the Fewest Experiments using Sorting Algorithms" Journal of Chemical Education. 98, 5, 1653–1658 (2021). (2019 IF: 1.7) https://doi.org/10.1021/acs.jchemed.1c00043

[3] Yip, T., Smith, P., Tynes, M., Mirpuri, S., Weems, A., and Cheon, Y. M. "Discrimination and hair cortisol concentration among asian, latinx and white young adults." Comprehensive Psychoneuroendocrinology. 6, 100047 (2021). (2019 IF: 4.7) https://doi.org/10.1016/j.cpnec.2021.100047

[4] Pendleton, I.M., Caucci, M.K., Tynes, M., Dharna, A., Nellikkal M.A., Li, Z., Chan E.M., Norquist, A.J., and Schrier, J. "Can Machines “Learn” Halide Perovskite Crystal Formation without Accurate Physicochemical Features?" Journal of Physical Chemistry C. 124, 25, 13982–13992 (2020). (2019 IF: 4.2)
https://doi.org/10.1021/acs.jpcc.0c01726

[5] Jones, L., Tynes, M., and Smith, P. "Prediction of models for ordered solvent in macromolecular structures by a classifier based upon resolution-independent projections of local feature data." Acta Crystallographica Section D: Structural
Biology. 75, 8, 696-717 (2019). (2019 IF: 7.7) https://doi.org/10.1107/S2059798319008933

[6] Zheng, W., Tynes, M., Gorelick, H., Mao, Y., Cheng, L., and Hou, Y. "FlowCon: Elastic Flow Configuration for Containerized Deep Learning Applications." Proceedings of the 48th International Conference on Parallel Processing Article 87, 1-10 (2019). (Conference Acceptance Rate: 20%) https://doi.org/10.1145/3337821.3337868
[1] Tynes, M. and Schrier, J. "How to GET novel perovskites: using the ESCALATE open source laboratory automation tool’s REST API to drive the discovery of materials" A Virtual Workshop on Autonomous Discovery in Science and Engineering. Center for Advanced Mathematics for Energy Research Applications (CAMERA), Lawrence Berkeley National Laboratory. Berkeley, CA. April 21, 2021. Video: https://drive.google.com/file/d/1XTu3hEmgquJtT8BBBaHQr02MtBgV4tUC/view

[2] Tynes, M., Hoyt, L., and Smith, P. "Testing the convergence of biological indices of chronic stress: hair and diurnal cortisol." Presentation delivered at The National Council of Undergraduate Research. Memphis, TN. April 7, 2017
[1] Tynes, M. and Schrier, J. "Tensor factorization for automated materials discovery based on data from failed experiments." Poster presented at AI and Tensor Factorizations for Physical, Chemical, and Biological Systems. Center for Nonlinear Studies (CNLS), Los Alamos National Laboratory. Santa Fe, NM. September 18, 2019.

[2] Tynes, M. Akhter, F., Sullivan, M., Yip, T., Smith, P. "Hair Cortisol Analysis as a Measure of Discrimination-Associated Chronic Stress." Poster presented at The Biennial meeting of the American Psychological Association, Division 45 Palo Alto, CA. July 7, 2016.

Awards

LANL Seaborg Fellowship, 2021-2022: Award to support interpretable machine learning for autonomous discovery in Actinide science (~25% acceptance)

LANL ISTI Fellowship, 2021-2022: Award to support development of software infrastructure for autonomous discovery in laboratory science at LANL

LANL SPOT Award, 2021: Recognition of distinguished performance in research.

LANL CNLS Fellowship, 2020-2021: Award to support the development of Pairwise Difference Regression (PADRE)

Fordham GSAS Graduate Research Fellowship, 2019-2020: Funding to support development of tensor factorization based reaction recommendation systems in chemical science. Funded by Fordham GSAS and the DARPA SD2 program (PI: Joshua Schrier).

Fordham Centennial Graduate Research Fellowship, 2018-2019: Funding from Fordham GSAS granted to the top 10% of students admitted to the MSDS program

Fordham Senior Leadership Award, 2017: Awarded each year to six to eight seniors who exhibit the ability to lead, organize, empower and inspire fellow students.

Fordham James C. Higgins Memorial Award in Psychology, 2017: One of three named awards given annually to a graduating senior for distinguished performance and contributions to the department

Fordham Undergraduate Research Grant, Fall 2016: Continued research support from Fordham College at Rose Hill for hormone quantification pipeline development

Fordham Undergraduate Research Grant, Summer 2016: Initial research support from Fordham College at Rose Hill for hormone quantification pipeline development