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Recent Advances in Info-Metrics ResearchApril 8, 2021, 9:45 EDT: Virtual Workshop
Workshop Objectives and Topics
In honor of Shannon's 105 th Birthday, and in celebration of our recently edited book Advances in Info-Metrics: Information and Information Processing across Disciplines (Chen, Dunn, Golan, Ullah, OUP, 2021), we will have a one-day online workshop to discuss recent advances in info-metrics and information-theoretic inference. The workshop will focus on info-metrics in the 21st century: recent advances, open questions and directions for future research within an interdisciplinary perspective. The aims of the workshop are to provide a forum for the dissemination of new research in all areas of info-metrics and to stimulate discussion between researchers, and students, across fields. The workshop will consist of invited talks, papers’ presentations, a graduate student session, and a panel discussion.
Topics of interest include (but not limited to)
- Modeling and Inference
- Applied Info-Metrics Inference
- Philosophy of info-metrics
- Causal Inference and info-metrics
- AI, Machine Learning, Deep Learning and info-metrics
- Covid-19 and info-metrics
- Inequality and info-metrics
Program Committee
- Min Chen (Oxford U)
- Rossella Bernardini Papalia(U of Bologna)
- Amos Golan (American U) Co-Chair
- Nataly Kravchenko-Balasha (Hebrew U)
- Aman Ullah (UC Riverside) Co-Chair
Co-Sponsors
Endorsed By
Watch the 2021 Conference
Videos in this playlist
To play a specific video, use the playlist icon in the player or view each video on YouTube.
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AUcollege
Recent Advances in Info Metrics Research Opening Remarks
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AUcollege
Session I Deep Inference with Karl J Friston
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AUcollege
Session II Info Metrics Across Sciences
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AUcollege
Session III Information Processing in Cell Cell Communication
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AUcollege
Session IV Information Theoretic Econometrics, Statistics and Bayesian
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AUcollege
Session V Info Metrics in Data Science
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AUcollege
Session VI Info Metrics and AI Modeling
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AUcollege
Session VII Info Metrics in Action — Short Presentations
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AUcollege
Session VIII — Invited Veridical Data Science and AI with Bin Yu
Invited Speakers
Bin Yu (UC Berkeley)
Bin Yu is Chancellor's Distinguished Professor and Class of 1936 Second Chair in the departments of statistics and EECS at UC Berkeley. She leads the Yu Group which consists of 15-20 students and postdocs from Statistics and EECS. She was formally trained as a statistician, but her research extends beyond the realm of statistics. Together with her group, her work has leveraged new computational developments to solve important scientific problems by combining novel statistical machine learning approaches with the domain expertise of her many collaborators in neuroscience, genomics and precision medicine.
She and her team develop relevant theory to understand random forests and deep learning for insight into and guidance for practice.
She is a member of the US National Academy of Sciences and of the American Academy of Arts and Sciences. She is Past President of the Institute of Mathematical Statistics (IMS), Guggenheim Fellow, Tukey Memorial Lecturer of the Bernoulli Society, Rietz Lecturer of IMS, and a COPSS E.L. Scott prize winner.
She is serving on the editorial board of Proceedings of National Academy of Sciences (PNAS) and the scientific advisory committee of the UK Turing Institute for Data Science and AI.
Karl Friston (University College London)
Karl Friston is a theoretical neuroscientist and authority on brain imaging. He invented statistical parametric mapping (SPM), voxel-based morphometry (VBM) and dynamic causal modelling (DCM). These contributions were motivated by schizophrenia research and theoretical studies of value-learning, formulated as the dysconnection hypothesis of schizophrenia. Mathematical contributions include variational Laplacian procedures and generalized filtering for hierarchical Bayesian model inversion. Friston currently works on models of functional integration in the human brain and the principles that underlie neuronal interactions. His main contribution to theoretical neurobiology is a free-energy principle for action and perception (active inference).
Friston received the first Young Investigators Award in Human Brain Mapping (1996) and was elected a Fellow of the Academy of Medical Sciences (1999). In 2000 he was President of the international Organization of Human Brain Mapping. In 2003 he was awarded the Minerva Golden Brain Award and was elected a Fellow of the Royal Society in 2006. In 2008 he received a Medal, College de France and an Honorary Doctorate from the University of York in 2011. He became a Fellow of the Royal Society of Biology in 2012, received the Weldon Memorial prize and Medal in 2013 for contributions to mathematical biology and was elected as a member of EMBO (excellence in the life sciences) in 2014 and the Academia Europaea in (2015). He was the 2016 recipient of the Charles Branch Award for unparalleled breakthroughs in Brain Research and the Glass Brain Award, a lifetime achievement award in the field of human brain mapping. He holds Honorary Doctorates from the University of Zurich and Radboud University.