Exploring Spatial Phenomenon with Geovisual Analytics
Ross Maciejewski, School of Computing, Informatics & Decision Systems Engineering, Director of the Homeland Security Center for Accelerating Operational Efficiency (CAOE), Arizona State University
10AM (PST), Wednesday, November 4, 2020
Abstract: From smart phones to fitness trackers to sensor enabled buildings, data is currently being collected at an unprecedented rate. Now, more than ever, data exists that can be used to gain insight into how policy decisions can impact our daily lives. For example, one can imagine using data to inform decisions on resource allocations for emergency response or diet and activity patterns could be used to provide recommendations for improving an individual's overall health and well-being. Underlying all of this data are measurements with respect to space and time, and geographical visual analytics tools and techniques have become a prominent means of modeling and conveying spatiotemporal patterns to novices and experts alike. In this talk, I will explore how advances in Artificial Intelligence and Machine Learning have helped drive a new wave of spatial data collection, modeling and simulation, and how teaming human and machine intelligence is leading to exciting new challenges and opportunities for geovisual analytics.
Biography: Ross Maciejewski is an Associate Professor at Arizona State University in the School of Computing, Informatics & Decision Systems Engineering and Director of the Center for Accelerating Operational Efficiency (CAOE) - a Department of Homeland Security Center of Excellence. His primary research interests are in the areas of visual analytics, explainable AI and decision making. Professor Maciejewski is a recipient of an NSF CAREER Award (2014) and was named a Fulton Faculty Exemplar (2017) and Global Security Fellow at Arizona State. His work has been recognized through a variety of awards at the IEEE Visual Analytics Contest (2010, 2013, 2015), a best paper award in EuroVis 2017, and a CHI Honorable Mention Award in 2018.
What's next in AI - Fluid Intelligence
Aya Soffer, Vice President of AI Technologies for IBM Research, Haifa Research Lab, Haifa, ISRAEL
10AM (PST), Thursday, November 5, 2020
Abstract: Today's AI is mostly narrow. While many AI models deliver value in specific, well-defined situations, applying those same models to new challenges requires an immense amount of new data and training. Enterprises need AI that is fluid and adaptable, capable of applying knowledge acquired for one purpose to new domains and challenges. They need AI that can combine different forms of knowledge, unpack causal relationships, and learn new things on its own. We call this fluid intelligence. In this talk I will provide an overview of several research directions that we are exploring in IBM towards fluid intelligence. These include neuro-symbolic techniques that combine deep learning with more traditional AI techniques such as symbolic reasoning; Efforts in NLP that can extract meaning from complex documents; AI engineering, tools and capabilities that simplify and automate key tasks like data preparation, training and lifecycle management; and innovation in the area of secure, trustedAI, with work focused on explainability, fairness, and bias reduction. I will provide examples focusing on Geo-Spatial applications of AI.
Biography: Dr. Aya Soffer is Vice President of AI Technologies for the IBM Research AI organization focusing on natural language understanding and conversational systems. In this role Dr. Soffer is responsible for setting the strategy and working with IBM scientists around the world to shape their ideas into new AI technology, and with IBM's product groups and customers to drive Research innovation into the market. In her 20 years at IBM, Dr. Soffer has led several strategic initiatives that grew into successful IBM products and solutions in the Big Data and AI space. These include the original Watson system and more recently Project Debater. Dr. Soffer received her MS and PhD degrees in computer science from the University of Maryland at College Park. Before joining IBM in 1999, she was a research scientist at Goddard space flight center, where she worked on digital libraries for earth science data. Dr. Soffer has published over 50 papers in refereed journals and conferences and filed over 15 patents. She has additionally served on program committees, as track chair, and given keynotes in many leading conferences including a TED Talk at TEDMED 2014.