Presentations

Selected talks, invited lectures, and research presentations

Talks

  1. Seminar Talk. From Measure Theory to Machine Learning: Product Coefficients for LiDAR Data. CUNY Graduate Center (Speaker Series), New York, NY. (Oct 17, 2025)
  2. Invited colloquium. Enhancing Machine Learning with Mathematics: Better Mapping of the World. Department of Mathematics, Kasetsart University, Bangkok, Thailand. (Jan 22, 2025)
  3. Invited lecture. Engineering Features for Machine Learning on Multi-Class 3D Point Clouds. Ninth International Conference on Data Management, Analytics and Innovation (ICDMAI 2025), Kolkata, India. (Jan 18, 2025)
  4. Contributed talk. Enhancing 3D Point Cloud Classification with Measure-Theoretic Features: Integrating Product Coefficients into LiDAR Analysis. Ninth International Conference on Data Management, Analytics and Innovation (ICDMAI 2025), Kolkata, India. (Jan 18, 2025)
  5. Invited. Product Coefficients for Feature Engineering for ML Classification in Remote Sensing Data. Seminario Internacional de Matemáticas. (Nov 29, 2024)
  6. Invited lecture. Measure Theory and Machine Learning in Remote Sensing Data. Mathematical Sciences Lecture Series, Rhode Island College. (Sep 19, 2024)
  7. Invited seminar talk. Measure Theory Quantities Applied to Machine Learning in LiDAR. Department of Mathematics Seminar, Colgate University. (Mar 7, 2024)
  8. Invited. Product Coefficients: Mathematical Quantities Improving Machine Learning Frameworks. Northwest Undergraduate Mathematics Symposium. (Nov 11, 2023)
  9. Invited. Product Coefficients: Mathematical Quantities Improving Machine Learning Frameworks. Math Circles, Brigham Young University. (Nov 8, 2023)
  10. Invited seminar talk. Product Coefficients for Machine Learning on Multi-Class 3D Point Clouds. Analysis Seminar, University of Rochester. (Oct 13, 2023)
  11. Invited tutorial. Using Machine Learning Techniques to Explore and Analyze LiDAR 3D Point Clouds. AMIGAs Tutorial 3, IPAM. (Jul 12, 2023)
  12. Contributed. Product Coefficients in Machine Learning in LiDAR. The MAA Annual Meeting of the Metropolitan New York Section, Pace University. (Apr 29, 2023)
  13. Workshop talk. City Tech–BYU Workshop (Part I). New York City College of Technology (CUNY), Brooklyn, NY. (Apr 4, 2023)
  14. Invited. How Math Can Help in Machine Learning for LiDAR 3D Point Clouds. The MAA Annual Meeting of the Metropolitan New York Section. (May 1, 2022)
  15. Contributed. Machine Learning in LiDAR 3D Point Clouds. AMS Special Session on Mathematical Tools for Computer Vision Problems, II, Joint Mathematics Meetings. (Apr 6, 2022)
    (co-author: Randy Paffenroth, Worcester Polytechnic Institute)
  16. Colloquium. Classification Frameworks Comparison on 3D Point Clouds. Department of Mathematics and Computer Science Colloquium, Queensborough Community College (CUNY), Bayside, NY. (Feb 16, 2022)
    (co-author: Randy Paffenroth, Worcester Polytechnic Institute)
  17. Conference presentation. Classification Frameworks Comparison on 3D Point Clouds. IEEE High Performance Extreme Computing Conference (HPEC 2021). (2021)
    (co-author: Randy Paffenroth)
  18. Invited lectures. Two invited lectures, REU summer program “STEM for All”, University of Rochester, Rochester, NY. (2021)
  19. Invited. Deep Learning in LiDAR and How Mathematical Ideas Can Help Us in Machine Learning. Mathematics Graduate Student Seminar, California State University Channel Islands, Camarillo, CA. (2019)
  20. Postdoc/graduate seminar. Deep Learning in LiDAR and How Mathematical Ideas Can Help Us in Machine Learning. ICERM Graduate Student and Postdoc Seminar, ICERM (Brown University), Providence, RI. (2019)
  21. Invited short research talk. Machine Learning Research in Geospatial Data. Algebraic Vision Research Cluster, ICERM (Brown University), Providence, RI. (2019)
  22. Invited. Deep Learning in LiDAR and How Mathematical Ideas Can Help Us in Machine Learning. Mathematics and Computer Science Colloquium, University of Dallas, Irving, TX. (2019)
  23. Invited. Deep Learning in LiDAR and How Mathematical Ideas Can Help Us in Machine Learning. Mathematics Department Colloquium, California Polytechnic State University, San Luis Obispo, CA. (2019)
  24. Research group presentation. Deep Learning in LiDAR and How Mathematical Ideas Can Help Us in Machine Learning. Data Science Research Group, Worcester Polytechnic Institute, Worcester, MA. (2019)
  25. Invited. Deep Learning in LiDAR and How Measure Theory Can Help Us in Machine Learning. Denksport Series, Worcester Polytechnic Institute, Worcester, MA. (2019)
  26. Contributed. Deep Learning for Classification of 3D Point Cloud LiDAR (joint with R. Paffenroth). SIAM Annual Meeting, Portland, OR. (Jun 11, 2018)
  27. Contributed. Deep Learning in 3D Point Cloud LiDAR Data. Advancing Women’s Impact in Mathematics Symposium, New England (AWIMS), Worcester, MA. (2018)
  28. Research group presentation. Analysis of Simulated Crowd Flow Exit Data: The Deep Learning Approach. Data Science Research Group, Worcester Polytechnic Institute, Worcester, MA. (2018)
  29. Progress report presentation. Project 2: Representation of Data as Multi-Scale Features and Measures. Women in Data Science and Mathematics Research Collaboration Workshop (WiSDM), ICERM, Providence, RI. (Jul 17–21, 2017)
  30. Invited. Evolution of Phase Transitions in Methane Hydrate. Schlumberger Research Center, Cambridge, MA. (Jun 8, 2017)
  31. Talk. Mathematical Treatments and Simulation of a Methane Hydrate Model. Applied Math Days 2017, Rensselaer Polytechnic Institute, Troy, NY. (Apr 8, 2017)
  32. Talk. Numerical Approximations for Methane Hydrate Models. Women’s Intellectual Research Symposium (New England), Brown University, Providence, RI. (Mar 4, 2017)
  33. Seminar. A Consequence of the Absence of the Dunford-Pettis Property in Orlicz Spaces. Analysis and PDE Seminar, Worcester Polytechnic Institute, Worcester, MA. (Dec 6, 2016)
  34. Seminar. Numerical Approximation for a Model of Methane Hydrates. Numerical Analysis Seminar, Worcester Polytechnic Institute, Worcester, MA. (Dec 2, 2016)
  35. Colloquium. Hybrid Modeling and Analysis of Multicomponent Adsorption with Applications to Coalbed Methane. Worcester Polytechnic Institute, Worcester, MA. (Nov 4, 2016)
  36. Talk. Analysis and Numerical Approximations for Kinetic Adsorption Models. Finite Element Circus, Worcester Polytechnic Institute, Worcester, MA. (Oct 14–15, 2016)
  37. Seminar. New Stability Framework for Kinetic Systems. Applied Mathematics and Computation Seminar, Oregon State University, Corvallis, OR. (Nov 3, 2015)
  38. Conference talk. Analysis and Numerical Approximation for Adsorption Models. SIAM Conference on Mathematical and Computational Issues in the Geosciences, Stanford University, Stanford, CA. (Jun 29, 2015)
  39. Invited. Analysis and Numerical Approximation for Adsorption Models. SIAM Conference on Computational Science and Engineering, Salt Lake City, UT. (Mar 15, 2015)
  40. Talk. Hyperbolic Systems for Adsorption. Cascade Computational and Applied Mathematics Seminar, Corvallis, OR. (Apr 5, 2014)
  41. Invited. Numerical Approximation for a Model of Methane Hydrates. Pacific Northwest Numerical Analysis Seminar, Seattle, WA. (Oct 19, 2013)
  42. Talk. Numerical Approximation for a Model of Methane Hydrates. Applied Mathematics and Computation Seminar, Oregon State University, Corvallis, OR. (Jun 7, 2013)
  43. Seminar Talk. Hyperbolic Systems for Adsorption (joint with M. Peszyñska). Applied Mathematics and Computation Seminar, Oregon State University, Corvallis, OR. (May 25, 2012)
  44. Seminar Talk. The Dunford-Pettis Theorem, Orlicz Spaces, and Related Topics. Probability Seminar, Oregon State University, Corvallis, OR. (Apr 6, 2010)
  45. Seminar Talk. On the Convergence in Mean of a Martingale Difference Sequence. Probability Seminar, Oregon State University, Corvallis, OR. (Apr 20, 2010)
  46. Seminar Talk. Uniform Integrability and the De La Vallée Poussin and Dunford-Pettis Theorems. Analysis Seminar, Bowling Green State University, Bowling Green, OH. (Mar 10, 2008)
  47. Conference talk. Non-complementarity of Orlicz Spaces in L1[0,1] and C[0,1]. XVII Jornadas Venezolanas de Matemáticas, Trujillo, Venezuela. (Mar 31–Apr 2, 2004)
  48. Seminar. Orlicz Spaces. Universidad de Los Andes, Mérida, Venezuela. (2003)
  49. Seminar. Topology in C[0,1]. Universidad de Los Andes, Mérida, Venezuela. (2003)

Posters

  1. The Neighbor Matrix: Feature Engineering and Dimension Reduction to Improve Machine Learning in 3D Point Clouds. 22nd Annual Poster Session, New York City College of Technology (CUNY). (Nov 21, 2024)
  2. The Neighbor Matrix: Feature Engineering and Dimension Reduction to Improve ML in 3D Point Clouds (with Randy Paffenroth). 22nd Annual Poster Session. (Nov 16, 2023)
  3. Product Coefficients on Dyadic Sets Applied to 3D Point Clouds (with Rasika Karkare). 21st Annual Poster Session. (Nov 16, 2023)
  4. Heuristic Framework for Multi-Scale Testing of the Multi-Manifold Hypothesis on 3D LiDAR Point Clouds (with Karamatou Yacoubou Djima, Linda Ness, and Melanie Weber). 20th Annual Poster Session. Award: Top 3 Best Poster. (Nov 27, 2022)
  5. Mathematical Treatment and Simulation for a Methane Hydrate Model. Modern Advances in Computational and Applied Mathematics (workshop honoring Charles L. Epstein and Leslie Greengard), Yale University, New Haven, CT. (Jun 9–10, 2017)
  6. Mathematical Treatment and Simulation for Methane Hydrate Models. High Performance Computing Days 2017, University of Massachusetts Dartmouth, North Dartmouth, MA. (May 25, 2017)
  7. Mathematical Treatment and Simulation for Methane Hydrate Models. Frontiers in Applied and Computational Mathematics, Brown University, Providence, RI. (Jan 4–6, 2017)
  8. Hybrid Modeling and Analysis of Multicomponent Adsorption with Applications to Coalbed Methane. Blackwell-Tapia Conference and Award Ceremony, University of Tennessee, Knoxville, TN. (Oct 28–30, 2016)
  9. Systems of Conservation Laws for Thermodynamically Consistent Adsorption. Workshop for Women in Math Sciences, SAMSI, Research Triangle Park, NC. (Apr 6–8, 2016)
  10. Systems of Conservation Laws for Thermodynamically Consistent Adsorption with Subscale Diffusion and Memory Terms. Department of Mathematics, University of Padova; SIAM Geosciences, Padova, Italy. (Jun 17–20, 2013)
  11. Systems of Conservation Laws for Thermodynamically Consistent Adsorption with Sub-scale Diffusion (joint with M. Peszyñska). SIAM Annual Meeting, Minneapolis, MN. (Jul 9–13, 2012)