Plenary and Keynote Speakers

Dr. Miklos Csorgo
Carleton University, Canada
Plenary Speaker

Miklós Csörgő was born on March 12, 1932 in Egerfarmos. His parents’ names are Miklós and
Ilona (Veres). He married on August 10, 1957 (in Canada) to Anna Eszter (Tóth), and his children are Adria and Lilla.
After 5 years of primary school in Egerfarmos, he completed his secondary school studies in Mezőkövesd, at Szent László Grammar School, where he graduated in 1951. He continued his studies at the Karl Marx University of Economics in Budapest, where he graduated from the
statistics department in 1955 and became an assistant professor at the Department of Statistics.
He left Hungary in December 1956. He arrived in Canada on January 16, 1957, where he began studying mathematics at McGill University in Montreal in September 1957 and was within a year a graduate student. He received his Master of Arts (M.A.) degree in mathematics from
McGill University in 1961 and his doctorate in mathematics (Ph.D.) in 1963 as an NRC Canada Graduate Student Scholar. He continued his studies as a Postdoctoral Fellow and lecturer at Princeton University (1963-1965).
After two years at Princeton, he was appointed assistant professor at McGill University and associate professor in 1968. In 1972, he was appointed professor of mathematics and statistics at Carleton University in Ottawa, where he was a founding member (1982) and co-director of the Statistics and Probability Research Laboratory, which is now recognized as a world-renowned institute in these fields of research.
In 1969-1970, Miklós Csörgő was a visiting professor at the Mathematics Institute, University of Vienna, and in 1990-91 at the University of Utah. While in Vienna, he developed contacts with Hungarian mathematicians, first with Pál Révész at the Institute of Mathematical Research and then with others in the same place, with whom he has been working in close cooperation ever since, and later also with mathematicians from Szeged.
Miklós Csörgő’s work has, to date, been published in 156 scientific papers, including in many of the best international journals. He has also published five books. He was Associate Editor (1979-1981) of the Annals of Probability, a premier international journal, and for two years (1978-1980) was a Killam Senior Research Fellow, which is Canada’s highest national designation for basic research in the natural sciences. He was twice a Canada Council Fellow (1969-1970, 1976-1977).

Topic of Keynote: Estimating Means and Testing for a Change in their values via Virtual Resampling
Plenary Abstract

Dr. Sheng Li,
University of Virginia, USA
Plenary Speaker

Topic of Keynote:

Dr. Leonard Stefanski
North Carolina State University, USA
Plenary Speaker

Topic of Keynote:

Dr. Charles Bouveyron
Université Côte d'Azur, France
Keynote Speaker

Topic of Keynote:

Dr. Inge S. Helland
University of Oslo, Norway
Keynote Speaker

Dr, Inge Svein Helland is professor emeritus at the University of Oslo. He got his master’s degree in statistics from the University of Bergen in1973 and his Dr. Philos. degree from the University of Oso in 1980. He has been professor in statistics at the Agricultural University of Norway and at the University of Oslo. His research covers more than 100 publications, most of them in various areas in applied and theoretical statistics. During the last 10 years, he has worked with the foundation of quantum theory, which has resulted in 4 books and various articles in leading journals in theoretical physics.

Topic of Keynote: On Quantum Foundation, As Seen By A Statistician
Keynote Abstract

Dr. Jana Jureckova
Charles University, Cezh Republic
Keynote Speaker

Jana Jurečková is Professor Emerita of Charles University in Prague, Czech Republic, where she worked in Department of Probability and Mathematical Statistics. Besides that she works as a Senior Research Fellow in the Institute of Information Theory and Automation, the Czech Academy of Sciences, since 2018. She received PhD in 1977 and the degreee DrSc in 1984 in Charles University in Prague; and is a elected member of the Learned Society of the Czech Republic, of ISI, and Fellow of IMS. As a Visiting Professor she worked in Bordeaux and Toulouse (France), in Neuchatel (Switzerland), in Chapel Hill (NC, USA). Besides that she had an intensive cooperation in Brussels (Belgium), in Ottawa (Canada), in Urbana-Champaign (Illinois, USA), in Freiburg (Germany), and elsewhere.
Her Fields of Interest: Analytical Statistics, Probability, Estimation and Hypotheses Testing, Robust and Nonparametric Statistical Methods, Extreme Value Theory. In this area she was an Advisor of 13 PhD students, worked in editorial boards of statistical journals and contributed to organizations of conferences. She is a coauthor of 4 monographs and of more than 160 journal publications, rather frequently cited.

Topic of Keynote: Quantile Functionals as Measures of Social, Health and Technical Events
Keynote Abstract

Dr. Hong Pan
Simmons University, USA
Keynote Speaker

Hong Pan, a dedicated professional in data science and statistics, was born to a family of educators. He attended Shanghai Jiao Tong University, where he studied Biomedical Engineering, and then joined Purdue University in the U.S. for his PhD program in Electrical and Computer Engineering.
After obtaining his PhD, Hong first joined Cornell University Medical College as a faculty member, where he conducted and oversaw technical, analytic, and engineering aspects of human in vivo functional and molecular neuroimaging research and trained multidisciplinary students, research fellows, and clinician scientists; and then moved to Harvard Medical School as a faculty member where he further his invention to innovation technology transfer journey in data science applications for medical imaging.
For over 25 years, Hong has been a leader in data science efforts, serving as the subject matter expert on over 20 federal and institutional projects. His influence and impact in the field, particularly his expertise in AI/ML algorithms and advanced statistics, have been instrumental in developing statistical, data-driven diagnostic tools for guiding the treatment of brain disorders. He has created best practice approaches for optimized data acquisition, data science solutions for biomarker discovery, and automated analytics and informatics pipelines based on functional neuroimaging methodology. His work has resulted in 4 patents, a successful spin-out startup, and earned him the Mass General Brigham Excellence in Innovation Award twice and Brigham and Women’s Hospital’s Pillar Award in Research & Innovation, with over 60 journal publications, solidifying his professional standing in the field.
In 2023, Hong joined Simmons University, a women-focused liberal arts college in Boston, as a faculty member and started focusing on full-time teaching in statistics and data science.

Topic of Keynote: Data Science Practice in Biomedical Imaging: A Practitioner’s Experience Examples