K G, PSYCHOLOGY & SCIENTIFIC COMPUTING Bio: K is a 4th year PhD candidate in Psychology and Scientific Computing. He has a Bachelors and a Masters degree in Biomedical Engineering and a Masters in Psychology. He works in the multisensory perception lab with Dr. David Brang and studies how multisensory integration occurs in the human […]
This is the fifth workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is somewhat self-contained. The focus is on conceptual details that can provide sufficient preparation for applications, but we will also touch upon the technical […]
Software development and computer programming is increasingly a major part of scientific research. Projects can quickly grow, and it can be difficult to manage changes, especially if multiple programmers are editing the same project at once! This workshop will cover Git, a commonly-used tool for managing coding projects with multiple users, with features to make […]
PLASMA BASED ACCELERATION AND THE ROLE OF HIGH FIDELITY SIMULATIONS IN ITS DEVELOPMENT
ANNA REDGRAVE, GRADUATE STUDENT, ECOLOGY AND EVOLUTIONARY BIOLOGY & SCIENTIFIC COMPUTING Bio: Anna Redgrave began her science career as an undergrad, master's student, and lab technician studying developmental biology in zebrafish. She became fascinated by how complicated developmental systems are, and joined the Wittkopp lab at U-M for her PhD to investigate one mechanism of […]
Deep Neural Networks (DNNs) are used as a machine learning method for both regression and classification problems. Keras is a high-level, Python interface running on top of multiple neural network libraries, including the popular library TensorFlow. In this workshop, participants will learn how to quickly use the Keras interface to perform nonlinear regression and classification […]
This is the sixth workshop in a series of workshops we are offering this semester on the fundamentals of GIS. Each workshop covers one or two key elements of GIS and is self-contained. The focus is on conceptual details that can provide sufficient preparation for applications, but we will also touch upon the technical aspects. […]
A BAYESIAN APPROACH TO ARTIFICIAL NEURAL NETWORKS
VISHWAS GOEL, GRADUATE STUDENT, MATERIALS SCIENCE AND ENGINEERING & SCIENTIFIC COMPUTING Bio: Vishwas is a third year Ph.D. student in the Thornton group, Department of Materials Science and Engineering. His research involves the simulations of the continuum level or microstructure level electrochemical dynamics of energy conversion/storage devices such as batteries, fuel cells, etc. SIMULATION OF […]
PROBING THE CORES OF MASSIVE STARS THROUGH THEIR SURFACE