spring_2025

Alessandra R. Brazzale is an Associate Professor of Statistics in the
Department of Statistical Sciences at the University of Padova. Her research interests include parametric likelihood-based inference, higher-order asymptotics, small-sample inference, measurement error, and clustering, with applications spanning the life sciences and astro-physics.

Umberto Picchini is interested in Bayesian inference for stochastic modelling, stochastic differential equations, simulator-based methods for inference, applications in biology and medicine. He prefers music pre 2000s. He is a professor in Mathematical Statistics at Dept Mathematical Sciences in Göteborg.

Prior to his appointment at Victoria University of Wellington in February 2015, Budhi had spent nearly three years at Bank of America Corp. working as a Quant at the level of AVP. He was based mainly in Singapore with direct reporting line to the Head of Quantitative Risk Management Group at BofA HQ in Charlotte, North Carolina. He joined BofA soon after the completion of his PhD in Utrecht in January 2007. His area of research is predominantly on applied probability and stochastic systems towards applications in actuarial science, financial stochastics, optimal stopping and free-boundary problems in theoretical and applied finance, stochastic filtering and smoothing, estimation of Markov chains with covariates dependent transition intensity matrix and their general mixtures, maximum likelihood recursive estimation under incomplete information. He was a visiting scholar, among others, to NYU Stern in April-May 2025, September 2019; Mathematical Institute, University of Copenhagen in February 2020, IEOR Department of Columbia University in May 2014, DAAD visiting scholar to Mathematical Institute of Goethe University of Frankfurt in October-November 2013.

Carolina Euan is a Lecturer in Statistics at the Mathematics and Statistics Department, University of Lancaster. Her research interests include the development of new statistical methods for the analysis of complex time series and Spatio-temporal data. She has experience working with data analysis of ocean wave data, precipitation and drought events, and statistical models for particular matter concentrations.

Emmett B. Kendall is a fifth year PhD candidate in the Department of Statistics at North Carolina State University (NC State). He graduated from the University of Florida (UF) with a B.S. in Mathematics and a Minor in Statistics. 

His research interests include hidden Markov models, Bayesian inference, biomedical statistics, functional data analysis, multi-task learning and regression discontinuity designs. 

Paolo Giordani is a professor of Financial Econometrics at the Norwegian Business School in Oslo.

His main research interests are statistical machine learning, Bayesian inference, and volatility

Arnt-Børre Salberg is a Chief Research Scientist at the Norsk Regnesentral, affiliated with the Department of BAMJO (Image Analysis, Machine Learning and Earth Observation).  

His research primarily focuses on the developing deep learning, computer vision, and remote sensing methods to image data. This includes work on forest mapping and monitoring, marine science applications, coastal habitat mapping, foundation models, and analysis of data from various sensors like satellites, seismic, and marine echosounders.

Hélène Ruffieux is a Senior Research Fellow at the MRC Biostatistics Unit, University of Cambridge. She holds a PhD in Mathematics from EPFL, Switzerland. Her research interests broadly lie in the development of Bayesian methods and their application to open problems in biomedicine, with a focus on scalable hierarchical modelling approaches for variable selection, latent structure discovery and network estimation, in high-dimensional or temporal data settings.

The Tien Mai is currently a postdoc at FHI. He has held postdoc positions in statistics at NTNU (Trondheim) and in biostatistics at UiO (OCBE). His research spans statistics and machine learning, with a particular interest in PAC-Bayesian analysis. He holds a PhD in Statistics from CREST-ENSAE-ParisTech/Paris Saclay and University College Dublin.

Anders Kvellestad is a Researcher in theoretical physics at the Department of Physics and head of the GAMBIT Collaboration. His research focuses on how to test new theories against results from the Large Hadron Collider and other experiments, using both frequentist and Bayesian approaches, and the computational challenges related to this work. Anders completed his PhD at the University of Oslo in 2015 and has since held postdoctoral positions at Nordita (Stockholm), Imperial College London and UiO.

Since 2021 he has lead the GAMBIT Collaboration, an international collaboration of physicists working on global fit analyses. He is also part of the PLUMBIN’ project at UiO, which aims to develop new computational and statistical tools for particle physics and beyond.

Gunnar Taraldsen is professor at Department of Mathematical  Sciences, NTNU. His current research interest focusses on the foundational principles of statistical inference including quantum probability, artificial intelligence, and machine learning. The aim is to bridge foundations for statistical inferences, to facilitate objective and replicable scientific learning, and to develop analytic and computing methodologies for data analysis.

Earlier research includes quantum mechanics, mathematical physics, measure theory, probability, medical ultrasound, non-linear wave propagation, numerical acoustics, medical statistics, outdoors sound propagation, community noise annoyance, acoustic noise mapping, underwater localization, underwater wave propagation, and spherical microphone arrays.