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Slideshow

Tags: Colloquium Series

The Statistics Department hosts weekly colloquia on a variety of statistcal subjects, bringing in speakers from around the world.

The Interplay between Statistical Practice and Academic Research Abstract: In the statistics field, there is a strong symbiotic relationship between academics and industry. We will explore this relationship primarily from a practicing statisticians’ perspective and discuss the lessons learned on how to foster, grow and bridge the gap between statistical practice and academic research. Several problems encountered in industry that led to academic…
Deming and the Industries of Today Abstract: Dr. Deming was one of the foundational leaders in industrial statistics, with contributions to experimental design, sampling, and process control. More importantly, he changed the culture of business leadership in two nations, and implicitly, around the world. But the industries of his day focused on manufacturing, while today’s industries reflect the knowledge economy. This talk asks the industrial…
SIMULATION GUIDED CLINICAL TRIAL DESIGN   Abstract: Simulation guided Clinical Trial Design is a framework for stimulating scientific dialogue between trial designer and clinical team with the final goal of developing the most appropriate design for the study. We create different “what-if” scenarios under different assumptions about the drug effect and simulate data from such scenarios and apply the design. We then see if under a scenario…
Inference of dynamic systems from noisy and sparse data via manifold-constrained Gaussian processes Abstract: Parameter estimation for nonlinear dynamic system models, represented by ordinary differential equations (ODEs) or partial differential equations (PDEs), using noisy and sparse experimental data is a vital task in many fields. We propose a fast and accurate method, manifold-constrained Gaussian process Inference, for this task. Our…
Functional Individualized Treatment Regimes with Imaging Features Abstract Precision medicine seeks to discover an optimal personalized treatment plan and thereby provide informed and principled decision support, based on the characteristics of individual patients. With recent advancements in medical imaging, it is crucial to incorporate patient-specific imaging features in the study of individualized treatment regimes. We propose a novel, data-…
Machine Learning for High-Risk Applications in Banking Renowned statistician George Box once famously stated, “All models are wrong, but some are useful.” In a world where machine learning increasingly automates important decisions about our lives, the consequences of model failures can be catastrophic. It’s critical to take deliberate steps to mitigate risk and avoid unintended harm. Evaluating the conceptual soundness of machine learning…
Do statisticians have labs? Introduction to the Precision Medicine Artificial Intelligence Lab (PHAIR) Event Slides Abstract: In this talk, I discuss a non-traditional approach to statistics training through the use of a virtual lab structure. For over a decade, the Precision Health Artificial Intelligence lab gradually evolved from an informal meeting for a few students engaged in similar research topics to a large virtual lab with about 30…
Approximation and Statistical Properties of Deep Neural Networks on Structured Data Abstract Deep neural networks have demonstrated remarkable generalization performance in high dimensional problems, e.g., image classification, where each image contains a large number of pixels. Such appealing performance contradicts a fundamental theoretical challenge – curse of data dimensionality. To explain this huge gap, we take the data intrinsic geometric…
When Will You Become the Best Reviewer of Your Own Papers? A Truthful Owner-Assisted Scoring Mechanism Zoom Info Link: https://zoom.us/j/93936847707?pwd=ZWFVRWlqL0x1bWxNM2xMQTczb3lPQT09 Meeting ID: 939 3684 7707 Passcode: 821272 Abstract In 2014, NeurIPS received 1,678 paper submissions, while this number increased to 10,411 in 2022, putting a tremendous strain on the peer review process. In this talk, we attempt to address this challenge…
Biography Dr. Nilanjan Chatterjee is a Bloomberg Distinguished Professor of Biostatistics and Genetic Epidemiology at Johns Hopkins University, with appointments in the Department of Biostatistics in the Bloomberg School of Public Health and in the Department of Oncology in the Sidney Kimmel Comprehensive Cancer Center in the Johns Hopkins School of Medicine. He was formerly…

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