On 6 May, another “IST Distinguished Lecture” will take place with a panel of six distinguished speakers that will focus on the present and future of computing. What challenges does Computing face as a science and profession? How do Information Technology interfere with society, industry, and academia?

May 6, 2021, Thursday, 5pm/7pm – Online (via Twitch)

The panel will be broadcast via Twitch at: https://www.twitch.tv/ist_acm_ieee
Registered participants will be able to place questions via Discord, 

To register please access: https://www.eventbrite.com/e/acmieee-panel-on-the-future-of-computing-tickets-150952086755

 

Featuring six panelists (from left to right): Gabriele Kotsis, Forrest Shul, Barbara Liskov, Moshe Vardi, Nuria Oliver, and Ricardo Baeza-Yates.

Gabriele Kotsis is Full Professor in Computer Science and President of the ACM. She has received her Ph.D. from the University of Vienna in 1995, honored with the Heinz Zemanek Ph.D. award. After visiting professor positions at the Business Schools in Vienna and Copenhagen in 2001/2002, she joined Johannes Kepler University Linz as head of the Department of Telecooperation. Her scientific contributions include seminal work in the field of workload characterization for parallel and distributed systems and in performance management of computer systems with a specific focus on ubiquitous computing environments and cooperative systems. In 2014, Kotsis has been recognized as ACM Distinguished Scientist for her scientific contributions. From 2003 to 2007 she was President of the Austrian Computer Society, from 2007 to 2015 Vice-Rector for Research at JKU. Gabriele has been JKU´s representative (2016-2018) and National Coordinator (since 2019) for Austria in the ASEA-UNINET academic research network.

Dr. Forrest Shull leads the Defense Software Acquisition Policy Research initiative at the Carnegie Mellon University Software Engineering Institute (SEI). He directs the SEI technical response to the Department of Defense (DoD) in support of several important activities, including Congressionally mandated initiatives, to improve acquisition by incorporating modern software development practices. This work culminated in the development of the Department’s first software-specific acquisition policy in 2020, which is supporting rapid and iterative delivery of software capabilities to the operational environment to meet the highest priority user needs. Shull joined SEI after 15 years at Fraunhofer USA, a nonprofit research and technology transfer organization, where he established and was director of the Measurement and Knowledge Management Division. He has been a lead researcher on projects for the DoD, the NASA Office of Safety and Mission Assurance (OSMA), the NASA Safety Center, the Defense Advanced Research Projects Agency (DARPA), the National Science Foundation, and commercial companies. His research work for NASA won a Group Achievement Award “in recognition of the significant impact on NASA software products and for advancing the state-of-the-art of the software industry.” He is the author of over 100 peer-reviewed publications. Shull is the current president of the Institute of Electrical and Electronics Engineers (IEEE) Computer Society. He has served on the Society’s Board of Governors and Executive Committee since 2015. In these roles, he has led and been a key participant in initiatives aimed at instituting more data-driven decision-making and transforming the Society to better address the current needs of its members. From 2011 to 2014, he served as Editor in Chief of IEEE Software, the premier publication for bridging software research and practice, during which time he oversaw the launch of a new digital edition of the magazine and broadened the magazine’s reach into multimedia.

Barbara Liskov is an Institute Professor at MIT. She is widely recognized for her work in programming languages, programming methodology, and distributed systems. Liskov’s work in programming methodology led to the invention of the notion of data abstraction, which is an important underpinning of how software systems are organized today. She and her group designed and implemented CLU, the first programming language to support data abstraction. She defined the meaning of behavioral subtyping, another fundamental concept for object-oriented programming; her definition is often referred to as the Liskov Substitution Principle (LSP). Her research in distributed systems includes work on online storage systems that provide confidentiality and integrity for the stored information and the development of two replication techniques that are in wide use today. The first, Viewstamped Replication, ensures correct behavior when computers fail by crashing. The second, PBFT (Practical Byzantine Fault Tolerance) ensures correct behavior when computers and the network fail arbitrarily. Her current research includes work on techniques for implementing databases on multicore machines to achieve good scalability and performance, investigation of new directions for programming languages, and support for online deals. Liskov is a member of the National Academy of Engineering, the National Academy of Sciences, the National Inventors Hall of Fame, and the Massachusetts Academy of Sciences. She is a fellow of the American Academy of Arts and Sciences and the Association for Computing Machinery, and a charter fellow of the National Academy of Inventors. She received the ACM Turing Award in 2009, the IEEE Von Neumann medal in 2004, the IEEE Pioneer Award in 2018, a lifetime achievement award from the Society of Women Engineers in 1996, the ACM SIGPLAN Programming Language Achievement Award in 2008, the ACM Sigops Hall of fame award in 2012, and the Stanford Hero of Engineering award in 2019.

Moshe Y. Vardi is University Professor and the George Distinguished Service Professor in Computational Engineering at Rice University. He is the recipient of several awards, including the ACM SIGACT Goedel Prize, the ACM Kanellakis Award, the ACM SIGMOD Codd Award, the Blaise Pascal Medal, the IEEE Computer Society Goode Award, and the EATCS Distinguished Achievements Award. He is the author and co-author of over 650 papers, as well as two books. He is a fellow of several societies, and a member of several academies, including the US National Academy of Engineering and National Academy of Science. He holds seven honorary doctorates. He is a Senior Editor of the Communications of the ACM, the premier publication in computing.

Nuria Oliver holds a PhD from MIT, is an IEEE Fellow, ACM Fellow, EurAI Fellow, Member of the Spanish Royal Academy of Engineering, Member of SIGCHI Academy, member of Academia Europaea, Spanish National Computer Science Award (Angela Ruiz Robles category), MIT TR100 (today TR35) Young Innovator Award, 2019 Data Scientist of the Year in Europe, 2020 Data Scientist of the Year by ESRI, Commissioner to the President of the Valencian Government on AI Strategy and Data Science against COVID-19, Cofounder, and Vicepresident of ELLIS, Cofounder of the ELLIS Alicante Unit Foundation, Chief Data Scientist at Data-Pop Alliance. She is the winner of the 500k XPRIZE Pandemic Response Challenge.

Ricardo Baeza-Yates is Head of Research at the Institute for Experiential AI of Northeastern University. He is also a part-time professor at Universitat Pompeu Fabra in Barcelona and Universidad de Chile in Santiago. Before, he was VP of Research at Yahoo Labs, based in Barcelona, Spain, and later in Sunnyvale, California, from 2006 to 2016. He is co-author of the best-seller Modern Information Retrieval textbook published by Addison-Wesley in 1999 and 2011 (2nd ed) that won the ASIST 2012 Book of the Year award. From 2002 to 2004 he was elected to the Board of Governors of the IEEE Computer Society and between 2012 and 2016 was elected for the ACM Council. Since 2010 is a founding member of the Chilean Academy of Engineering. In 2009 he was named ACM Fellow and in 2011 IEEE Fellow, among other awards and distinctions. He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989, and his areas of expertise are web search and data mining, information retrieval, bias on AI, data science, and algorithms in general.