./news

  • Oct 2025: Our invited session proposal for JSM 2026, Deep learning for statistical inference on spatial data, has been accepted!
  • Sep 2025: Preprint on causal spatial quantile regression, led by Yan Gong, is now on ArXiv. link
  • Apr 2025: Jordan Richards and I have a new preprint on arXiv for bulk-and-tail estimation using a novel framework, extremal semi-parametric quantile regression. link
  • Feb 2025: Paper on estimating limit sets for tail inference on bivariate data has been accepted for publication in Bayesian Analysis. link
  • Feb 2025: Our topic contributed session proposal for JSM 2025 - Collaborative Strategies for Predicting and Measuring Uncertainty associated with Weather and Climate Extremes, has been accepted.
  • Jan 2025: Paper on prescribed burning decision making has been accepted for publication in Ecological Informatics. link
  • Oct 2024: Our ongoing work on Stochastic gradient MCMC for Gaussian process inference on massive geostatistical data (led by Mohamed Abba), has been accepted at the Bayesian Decision-making and Uncertainty: from probabilistic and spatiotemporal modeling to sequential experiment design! link
  • Aug 2024: I’ve joined the Department of Mathematical Sciences, University of Arkansas, as a tenure-track Assistant Professor.
  • Jun 2024: Preprint with Callum and Jordan - ‘Deep Learning of Multivariate Extremes via a Geometric Representation’ - out now on arXiv! link
  • Apr 2024: Research visit to TU Dresden with Jordan Richards, hosted by Callum Murphy-Barltrop, to work on high-dim geometric extremes’ modeling.
  • Nov 2023: Our invited session proposal for JSM 2024 - Amortized learning for environmental data using neural networks - has been accepted.
  • Nov 2023: Paper on modeling extremal streamflow using deep learning has been accepted for publication in the Annals of Applied Statistics. link
  • Aug 2023: I was a participant at the ForceSMIP Hackathon at NCAR (Boulder, CO).
  • Aug 2023: Co-organized oral session at the Ecological Society of America (ESA 2023) Annual Meeting, Portland, on The Future of Fire: sociocultural and biophysical contexts for fire stewardship under climate change. [Recording]
  • Aug 2023: Organized topic contributed sesion at JSM 2023, Toronto, on Advances in computational methods for large spatial data.
  • Jun 2023: Organized invited session at IISA 2023, Golden (CO), on Methods and computing for large spatial data.

./presentations & guest lectures

  • Oct 2025: Short course on AI for statistical analysis at UMBC.
  • Oct 2025: Statistics Colloquium speaker at the University of Maryland, Baltimore County, MD. Vecchia approximated density regression for spatial models with intractable likelihoods.
  • Oct 2025: Invited talk at the Workshop on Neural Simulation-based inference at the Carnegie Mellon University, PA. Vecchia approximated density regression for spatial models with intractable likelihoods.
  • Sep 2025: Invited session at the 2025 Southeast CASC Regional Science Symposium. An RxFire optimization tool for climate-informed decision making.
  • Jun 2025: Invited session at the Contemporary Advances in Statistics of Extremes workshop, Missouri. Semi-parametric bulk and tail regression using spline-based neural networks.
  • Jun 2025: Short course at the Contemporary Advances in Statistics of Extremes workshop, Missouri. AI and extremes (with Jordan Richards and Likun Zhang).
  • Jun 2025: Invited session at EVA 2025, UNC Chapel hill. Semiparametric Estimation of the Shape of the Limiting Bivariate Point Cloud.
  • Mar 2025: Guest lecture for Applied Spatial Statistics, Mizzou, Computational methods for large spatial data. [Slides] [workbook]
  • Nov 2024: Poster at the CASC Futures Forum, San Diego, A spatiotemporal optimization engine for RxFire in the Southeast US.
  • Nov 2024: Talk at the Extremes2024 workshop held at the Colorado School of Mines, A geometric representation of multivariate extremes and its use in environmental modeling.
  • Aug 2024: Guest instructor for NASA ARSET training. Drought monitoring, prediction, and projection using NASA earth system data. [webpage]
  • Jun 2024: Talk at the Southeast Climate Adaptation Science Center science seminar. A spatiotemporal recommendation engine for RxFire in the Southeast US. [Slides][Recording]
  • Sep 2023: Talk at the Extreme Disturbances and Climate Change in the Southeast US workshop. The Future of Fire. [Slides][Recording]
  • Aug 2023: Talk at JSM 2023, Toronto. Topic contributed session on The IMSI Confronting Global Climate Change Program. [Slides]
  • Jun 2023: Talk at IISA 2023, Golden (CO). Invited session on Advances in Extreme Value Analysis.
  • Jun 2023: Talk at the ICSA Applied Statistics Symposium, Ann Arbor (MI). Invited session on New developments in spatial extremes modeling.
  • May 2023: Poster at the 2023 Clemson Climate Extremes Workshop, Clemson University. [Poster]
  • Mar 2023: Guest lecture for Spatial statistics and image analysis (STAT 625), UMBC, The Vecchia approximation for large spatial data. [Slides]
  • Mar 2023: Bayesian bootcamp (with Eric Yanchenko) for the Astrostatistics interest group, NCSU, 2023. [Slides]
  • Dec 2022: Talk for invited session at CMStatistics 2022, London. [Slides]
  • Dec 2022: Guest lecture for Bayesian inference (ST 740), NCSU. Variational Bayes for latent variable models. [Slides]
  • Oct 2022: Talk at the Climate and Weather Extremes workshop, Institute of Mathematical and Statistical Innovation (IMSI). [Recording]
  • Aug 2022: Talk for topic contributed session, JSM 2022, Washington DC