Academic Activities
Conference Organization
10/2024 Scientific Committee: The 45th Midwest Probability Colloquium, Chicago.
07/2024 Invited Session Organizer and Chair: The 7th International Conference on Econometrics and Statistics (EcoSta 2024), Beijing.
06/2024 Invited IMS Session Organizer and Chair: 2024 WNAR/IMS/Graybill Annual Meeting, Colorado.
07/2023 Invited Session Organizer and Chair: The 64th International Statistical Institute (ISI) World Statistics Congress, Ottawa.
10/2022 Invited Session Chair: Conference on Advances in Data Science: Theory, Methods and Computation, Texas A&M Univ.
06/2022 Invited Session Organizer and Chair: Institute of Mathematical Statistics (IMS) Annual Meeting, London
08/2021 Invited IMS Session Organizer and Chair: Joint Statistical Meetings (JSM) / Institute of Mathematical Statistics (IMS) Annual Meeting, Seattle
11/2018 Session Chair: Data Science in Finance, INFORMS Annual Meeting, Phoenix
Talks and Special Lectures
10/2025 Invited session of the 65th ISI World Statistics Congress 2025, The Hague, Netherlands.
TBA
08/2024 Special (invited) session of Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (2024 MCQMC), University of Waterloo, Canada.
On the Convergence of MCMCs with Quantum Speedup
07/2024 Invited speaker, Summer School Series on Mathematical Statistics and Machine Learning, Vietnam Institute for Advanced Study in Mathematics (VIASM), Hanoi, Vietnam.
Variable Target Markov Random Field Scalable Particle Filter
07/2024 Invited session of the 7th International Conference on Econometrics and Statistics (EcoSta 2024), Beijing.
Variable Target Scalable Particle Filter
07/2024 Invited speaker, 2024 International Conference for Statistics and Data Science, Taiwan.
Advancements in Online Learning for High-Dimensional Spatiotemporal Models
06/2024 Invited session, Eastern Asia Chapter of International Society for Bayesian Analysis (EAC-ISBA) conference 2024, Education University of Hong Kong
Variable Target Scalable Particle Filter
06/2024 Invited IMS session of 2024 WNAR/IMS/Graybill Annual Meeting, Fort Collins, Colorado.
Variable Target Scalable Particle Filter
05/2024 Los Alamos National Laboratory Robotics & Automation Workshop, TAMU.
Iterated Block Particle Filter for High-dimensional Tracking and Inferences
04/2024 Department Seminar, Department of Information Systems and Statistics, Zicklin School of Business, Baruch College, City University of New York.
Variable Target Scalable Particle Filter
04/2024 Smith Colloquium, Department of Mathematics, University of Kansas.
Variable Target Scalable Particle Filter
03/2024 Invited Panelist for the one-hour panel, 2024 Annual Seminar on Stochastic Processes, Rice University.
Panel discussion for beginning researchers
01/2024 Invited session of the 6th IMS Asia Pacific Rim Meeting (IMS-APRM), Melbourne, Australia.
Variable Target Scalable Particle Filter
10/2023 Colloquium, Department of Mathematics and Statistics, Bowling Green State University
Feature selection in multivariate time series modeling: From Gaussian to non-Gaussian
10/2023 Institute Seminar, Institute for Quantum Science & Engineering, TAMU
Bayesian sparse principal component analysis
06/2023 Invited session of EAC-ISBA 2023, Qingdao, China.
Convergence of Dirichlet Forms for MCMC Optimal Scaling with General Target Distributions on Large Graphs
02/2023 Virtual Time Series Seminar, founded by Majid Al-Sadoon, Adriana Cornea-Madeira, Dimitris Korobilis, Alessandra Luati, Geert Mesters, Michele Piffer, and Abderrahim Taamouti.
High-dimensional parameter learning over non-linear and non-Gaussian time series models
02/2023 Mathematical Physics and Harmonic Analysis Seminar, Dept. of Math, Texas A&M Univ.
Mosco Convergence of Dirichlet Forms on Machine Learning Gibbs Measures
12/2022 Infectious Disease Modeling Seminar, Mailman School of Public Health, Columbia Univ.
Metapopulation modeling and inference for scientific discovery
11/2022 Probability and Statistics Seminar, Department of Mathematics & Statistics, Boston Univ.
Convergence of Dirichlet Forms for MCMC Optimal Scaling with General Target Distributions on Large Graphs
09/2022 Stat-Cafe student seminar, Texas A&M Univ.
High dimensional Machine Learning and its Applications in Finance
06/2022 Invited Scientific Committee session of IMS annual meeting, London
High dimensional MCMC analysis: From diffusions to Dirichlet forms
06/2022 Selected talk (30 mins), Union College Mathematics Conference, New York.
Multivariate Hierarchical Path-dependent Stochastic Variational Inequalities
03/2022 Department Seminar, Department of Statistics, University of British Columbia.
Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality
02/2022 Department Colloquium, Department of Integrated Systems Engineering, Ohio State University.
High-dimensional Parameter Learning over General Graphical State Space Models: Beating the Curse of Dimensionality
01/2022 Department Seminar, Department of Statistics, University of Wisconsin, Madison.
High-dimensional Parameter Learning over General Graphical State Space Models: Beating the Curse of Dimensionality
01/2022 Department Colloquium, Department of Mathematics, The Ohio State University.
Machine learning high-dimensional volatilities over large financial systems
01/2022 Department Colloquium, Department of Mathematics, University of Florida.
High-dimensional Parameter Learning over General Graphical State Space Models: Beating the Curse of Dimensionality
01/2022 Department Seminar, Department of Mathematical Sciences, New Jersey Institute of Technology.
High-dimensional Parameter Learning over General Graphical State Space Models: Beating the Curse of Dimensionality
12/2021 Financial/Actuarial Mathematics Seminar, Department of Mathematics, University of Michigan, Ann Arbor.
High-dimensional Generalized Stochastic Volatility Models
11/2021 Department Seminar, Department of Statistics, University of Michigan, Ann Arbor.
High-dimensional Parameter Learning over General Graphical State Space Models: Beating the Curse of Dimensionality
11/2021 Student Seminar, Department of Statistics, University of Michigan, Ann Arbor.
Feature selection in multivariate time series modeling: From Gaussian to non-Gaussian
09/2020 Department of Statistics and Probability Colloquium, Michigan State University.
Probabilistic machine learning in multivariate time series forecasting
03/2020 2020 Seminar on Stochastic Processes (SSP), Michigan State University.
Bayesian Phylogenetic Inference of Stochastic Block Models on Infinite Trees
11/2019 The 18th Northeast Probability Seminar, CUNY Graduate Center.
Simultaneous Two-dimensional Continuous-time Markov Chain Approximation of Two-dimensional Fully Coupled Markov Diffusion Processes
11/2019 Invited Presentation by Mercedes Pascual at the Department of Ecology and Evolution, Univ. of Chicago.
Scaleable Monte Carlo Adjusted Profile Likelihood Estimation
06/2019 Applied Mathematics: The Next 50 Years (Conference for the 50th anniversary of Applied Mathematics), UW Seattle.
Continuous Time Markov Chain Approximation Technique and its Applications
05/2019 31st Cumberland Conference on Combinatorics, Graph Theory and Computing, University of Central Florida.
The non-tightness of the reconstruction threshold of a 4 states symmetric model with different in-community and out-community mutations
11/2018 9th Western Conference on Mathematical Finance (Theme: FinTech), USC.
Bayesian Machine Learning in Finance
11/2018 INFORMS 2018 Annual Meeting in Phoenix (Session: Data Science in Finance), AZ.
Multivariate Bayesian Structural Time Series Model
09/2018 Math Seminar, The Graduate Center, CUNY.
Mathematical Analysis of Neural Network
05/2018 2018 Seminar on Stochastic Processes (SSP), ICERM, Brown University
Some Results of Mean Field Games on the Erdos-Renyi Random Graph
05/2018 Applied Math Seminar, Univ. of Washington, Seattle.
Multivariate Bayesian Structural Time Series Model and its Applications on Finance
04/2018 Finger Lakes Probability Seminar, University of Rochester.
Large Degree Asymptotics and the Reconstruction Threshold of Multiple Mutations Channel
04/2018 Math Seminar, The Graduate Center, CUNY. (Invited)
Multivariate Bayesian Structural Time Series Model
04/2018 Math Seminar, Farmingdale State College, SUNY. (Invited)
Financial Machine Learning != Machine Learning on Finance: Challenges & Strategies
03/2018 11th Women in Mathematics in Southern California Symposium, Pepperdine University
Weakly Interacting Particle Systems on Random Graphs (LLN, CLT, LDP)
03/2018 Department service talk to new Ph.D. and M.S. students, UCSB
Data Science on Finance
02/2018 Special Topics in Financial Mathematics, UCSB
Axiomatic Construction of Marginals: Stieltjes Moment Problem
11/2017 Northeast Probability Seminar, Columbia University
The Tightness of the Kesten-Stigum Reconstruction Bound of Symmetric Model with Multiple Mutations
08/2017 Mean Field Games (Poster Session), IPAM, UCLA
Reconstruction on d-ary Tree with Application on Social Network
06/2017 Robust Methods in Probability & Finance, ICERM, Brown University
Uncertain Volatility Models with Stochastic Bounds
05/2017 Mathematical Finance, Probability, and Partial Differential Equations Conference, Rutgers University
Uncertain Volatility Models with Stochastic Bounds
03/2017 QCC Department Seminar, City University of New York
Uncertain Volatility Models with Stochastic Bounds
2016-2017 PSTAT Fractional Brownian Motion Group Meeting, UCSB
Stochastic Control with Path-Dependent Controls
Volatility is Rough
10/2016-12/2016 Special Topics in Financial Mathematics, UCSB
Uncertain Volatility Models Simulation
Uncertain Volatility Models