Presentation

I present my research in theoretical nuclear astrophysics at seminars, workshops, schools, and scientific conferences. My invited and contributed presentations are listed below.

Talks #

• 2026 Aug Invited – Low Energy Community Meeting, Argonne National Lab, IL
  Shaping the Third r-Process Peak: The Role of Nuclear data around the N=126 Shell Closure.
• 2026 May Invited – Astrophysics with Radioactive Nuclei, Traverse City, MI
  Shaping the Third r-Process Peak: The Role of Nuclear Masses around the N=126 Shell Closure.
• 2026 May Invited – Facility for Rare Isotope Beams (FRIB), East Lansing, MI
  Nuclear Masses in Astrophysics for the Next 25 Years.
• 2026 Mar Invited – Institute of Nuclear Theory (INT), Rising Researchers Seminar Series, Seattle, WA
  Neutron Economy and Freeze-out Dynamics in late time cold r-process.
• 2026 Feb Invited – Texas A&M University, College Station, TX
  From Mergers to Matter: Connecting Microscopic Nuclear Physics to Multi-Messenger Observations.
• 2025 Dec Invited – Michigan State University, East Lansing, MI
  From Nuclei to Stars: Connecting Nuclear Physics to Heavy Element Formation.
• 2025 Oct Invited – Division of Nuclear Physics (DNP), APS, Chicago, IL
  Machine Learning for the Properties of Exotic Nuclei
• 2025 Oct Invited – Division of Nuclear Physics (DNP), APS, Chicago, IL
  Machine Learning Nuclear Masses for the Astrophysical r-process
• 2025 Oct Invited – Triangle Nuclear Theory Colloquium, North Carolina State University, Raleigh, NC
  Bridging Nuclei and Stars: Constraining Nuclear Mass Models with the r-Process Observables
• 2025 Sep Invited – Astrophysics Chat, University of California, Berkeley, CA
  Heavy Element Formation: From Nuclear Properties to Astrophysical Observables
• 2025 July Invited – IReNA-UKAKUREN, Osaka Metropolitan University, Osaka, Japan
  Constraining Nuclear Mass Models with the r-Process Observables with multi-objective functions.
• 2025 July Contributed – GravNu, California State University, Fullerton, CA
  Constraining Nuclear Mass Models with the r-Process Observables with multi-objective functions.
• 2025 June Invited – Gordon Research Seminar, Colby-Sawyer College, New London, NH
  Constraining Nuclear Mass Models with the r-Process Observables with multi-objective functions.
• 2025 June Contributed – CeNAM, Ohio University, Athens, OH
  Constraining Nuclear Mass Models with the r-Process Observables with multi-objective functions.
• 2025 Apr Invited – Astrophysics Seminar, University of Notre Dame, South Bend, IN
  Bridging Nuclei and Stars: Constraining Nuclear Mass Models with the r-Process Observables.
• 2025 Mar Contributed – APS Global Physics Summit, Anaheim, CA
  Graph-based recursive relations for computing and analyzing r-process abundances.
• 2024 Jul Contributed – N3AS Summer School, Santa Cruz, CA
  Applying graph theory to r-process nucleosynthesis calculation.
• 2024 Jun Invited – N3AS Annual Meeting, Berkeley, CA
  GrRproc: A Graph-based Method to Calculate r-Process.
• 2024 Jun Contributed – CeNAM Frontier Meeting, South Bend, IN
  GrRproc: A Graph-based Method to Calculate r-Process.
• 2024 Jan Invited – Astrophysics Seminar, IHEP, Beijing, China
  An Introduction to Astrophysical r-Process.
• 2023 Nov Invited – N3AS Workshop, APS, Honolulu, HI
  GrRproc: A Graphic Way of Calculating the Abundances of Heavy Nuclei.
• 2023 Nov Contributed – DNP, APS, Honolulu, HI
  Atomic Mass with Machine Learning for Astrophysical r-Process.
• 2023 May Invited – Frontier Summer School, MSU, Lansing, MI
  Atomic Mass with Machine Learning for the Study of r-Process.
• 2023 May Contributed – CeNAM Frontier Meeting, MSU, Lansing, MI
  Machine Learning Nuclear Properties for the Rapid Neutron Capture Process.
• 2022 Oct Contributed – DNP, APS, New Orleans, LA
  Extrapolating Mixture Density Network Predictions: Application to the Astrophysical r-Process.
• 2022 Aug Invited – Center for Theoretical Astrophysics, Los Alamos, NM
  Nuclear Mass with Machine Learning and Application to the Astrophysical r-Process.
• 2022 Jul Contributed – Theoretical Division, Los Alamos, NM
  Nuclear Mass with Machine Learning and Application to the Astrophysical r-Process.
• 2022 Jul Contributed – Center for Nonlinear Studies, Los Alamos, NM
  Machine Learning for Nuclear Masses with a Probabilistic Neural Network.
• 2021 Oct Contributed – DNP, APS, Boston, MA
  Dependence of (n, γ)–(γ, n) Equilibrium r-Process Abundances on Nuclear Physics.