BEN SHNEIDERMAN is an Emeritus Distinguished University Professor in the Department of Computer Science, Founding Director (1983-2000) of the Human-Computer Interaction Laboratory, and a Member of the UM Institute for Advanced Computer Studies (UMIACS) at the University of Maryland. He is a Fellow of the AAAS, ACM, IEEE, NAI, and the Visualization Academy and a Member of the U.S. National Academy of Engineering, in recognition of his pioneering contributions to human-omputer interaction and information visualization. His widely-used contributions include the clickable highlighted web-links, high-precision touchscreen keyboards for mobile devices, and tagging for photos. Shneiderman’s information visualization innovations include dynamic query sliders for Spotfire, development of treemaps for viewing hierarchical data, novel network visualizations for NodeXL, and event sequence analysis for electronic health records. Ben is the lead author of Designing the User Interface: Strategies for Effective Human-Computer Interaction (6th ed., 2016). He co-authored Readings in Information Visualization: Using Vision to Think (1999) and Analyzing Social Media Networks with NodeXL (2nd edition, 2019). His book Leonardo’s Laptop (MIT Press) won the IEEE book award for Distinguished Literary Contribution. The New ABCs of Research: Achieving Breakthrough Collaborations (Oxford, 2016) describes how research can produce higher impacts. His forthcoming book on Human-Centered AI, will be published by Oxford University Press in January 2022.
Nisha Talagala is the CEO and founder of AIClub.World. Nisha has significant experience in bringing AI Literacy to individuals from students to professionals. Previously, Nisha co-founded ParallelM which pioneered the MLOps practice of managing Machine Learning in production for enterprises – acquired by DataRobot. Nisha is a recognized leader in the operational machine learning space, having also driven the USENIX Operational ML Conference, the first industry/academic conference on production AI/ML. Nisha was previously a Fellow at SanDisk and Fellow/Lead Architect at Fusion-io, where she worked on innovation in non-volatile memory technologies and applications. Nisha has more than 20 years of expertise in enterprise software development, distributed systems, technical strategy, and product leadership. She has worked as technology lead for server flash at Intel – where she led server platform non-volatile memory technology development, storage-memory convergence, and partnerships. Prior to Intel, Nisha was the CTO of Gear6, where she designed and built clustered computing caches for high-performance I/O environments. Nisha earned her Ph.D. at UC Berkeley where she did research on clusters and distributed systems. Nisha holds 73 patents in distributed systems and software, over 25 refereed research publications, is a frequent speaker at industry and academic events, and is a contributing writer to Forbes and other publications.
Q. Vera Liao is a Research Staff Member in IBM T.J. Watson Research Center, working in the “Trusted AI” area. Her research background is in human-computer interaction (HCI), with current focuses on human-AI interaction, explainable AI, and conversational agents. Her work received multiple awards at ACM CHI and IUI. She was awarded IBM Outstanding Research Accomplishments for contributions to IBM’s Watson Assistant and Trusted AI toolkits. She serves on the Editorial Board of International Journal of Human-Computer Studies (IJHCS) and ACM Transactions on Interactive Intelligent Systems (TiiS). She received a Ph.D. in Computer Science and a M.S. in Human Factors from University of Illinois at Urbana-Champaign, and a bachelor’s degree in Industrial Engineering from Tsinghua University.
Arif Wider is a professor of software engineering at HTW Berlin and a principal technology consultant with ThoughtWorks Germany, where he served as Head of Data & AI before moving back to academia. As a vital part of research, teaching, and consulting, he is passionate about distilling and distributing great ideas and concepts that emerge in the software engineering community. Arif is a frequent speaker at conferences and loves to bring together people with diverse areas of expertise such as data scientists and developers.
Danilo Sato is the Head of Data & AI Services at ThoughtWorks UK. His 20 years technology career combines experiences leading accounts and teams with a breadth of technical expertise in many areas of architecture and engineering: software, data, infrastructure, and machine learning. He is the author of DevOps in Practices: Reliable and Automated Software Delivery, a member of ThoughtWorks’ Technology Advisory Board and Office of the CTO, and is an experienced international conference speaker.
Yingnong Dang is a Principal Data Scientist Manager in Microsoft Azure. Yingnong’s research focus is AIOps and its industrial adoption, specifically, building analytics and ML solutions for improving cloud infrastructure availability, performance, and efficiency, boosting engineering productivity, and increasing customer satisfaction. Yingnong has been advocating the importance of AIOps to cloud computing and digital transformation in industry and academia in the past few years, e.g., his ICSE technical briefing, AI NextCon’ 19. Yingnong and the team have a close partnership with Microsoft Research and academia. Before joining Azure in December 2013, Yingnong was a researcher in Microsoft Research Asia lab, with research areas including software analytics, data visualization, data mining, and human-computer interaction. As a researcher, he has transferred various technologies to Microsoft product teams including code clone analysis, crash dump analysis, performance trace analysis, etc. He owns 45+ U.S. patents. He has published papers in top conferences including ICSE, FSE, VLDB, USENIX ATC, OSDI, and NSDI.
Grace Lewisis a Principal Researcher and the lead for the Tactical and AI-Enabled Systems (TAS) Initiative at the Carnegie Mellon Software Engineering Institute (SEI). She is a Principal Investigator for two projects in the growing field of software engineering for machine-learning (ML) systems: “Characterizing and Detecting Mismatch in ML-Enabled Systems” and “Predicting Inference Degradation in Production ML Systems.” Her current areas of expertise and interest include software engineering for AI/ML systems, software architecture (in particular the development of software architecture practices for systems that integrate emerging technologies), edge computing, and software engineering in society. Grace holds a B.Sc. in Software Systems Engineering and a Post-Graduate Specialization in Business Administration from Icesi University in Cali, Colombia; a Master in Software Engineering from Carnegie Mellon University; and a Ph.D. in Computer Science from Vrije Universiteit Amsterdam. Grace is an IEEE Senior Member and very active in IEEE Computer Society committees and conferences. She is currently the VP for the IEEE Computer Society Technical & Conference Activities (T&C) Board, Member of the Board of Governors, Member of the Diversity and Inclusion (D&I) Committee, Alternate Representative for IEEE-CS on the ABET CSAB Board of Directors, as well as an ABET Evaluator for Computer Science undergraduate programs. .