10th Heidelberg Laureate Forum, 24—29 September

The 10th Heidelberg Laureate Forum will offer young researchers and other participants the opportunity to connect with scientific pioneers and learn how the laureates made it to the top of their fields as some of the brightest minds in mathematics and computer science come together for an unrestrained, interdisciplinary exchange. This compelling networking event combines scientific, social and outreach activities in a unique atmosphere, sustained by comprehensive exchange and scientific inspiration. 

Notable participants this year include 22 ACM Award recipients including ACM A.M. Turing Award recipients Bob Metcalfe, Jack Dongarra, Vinton Cerf, and Whit Diffie, as well as ACM Prize in Computing recipients Yael Tauman Kalai, Pieter Abbeel, and Shwetak N. Patel, among many others. While the 10th HLF is being held at its traditional home in Heidelberg, Germany, sessions will also be livestreamed on the HLF website.

Call for ACM Award Nominations

Each year, ACM recognizes technical and professional achievements within the computing and information technology community through its celebrated Awards Program. ACM welcomes nominations for candidates whose work exemplifies the best and most influential contributions to our community and society at large.

ACM seeks your help in expanding and diversifying the nomination pool for our ACM Awards. It is often the case that people wonder why a specific person who seems highly deserving has not received an ACM award. The common answer is that the person was never nominated.

Please take a moment to consider those people in your community who may be suitable for nomination. Refer to the award nominations page for links to individual award pages, where you will find nomination requirements, deadlines, and Award Subcommittee Members. Keep in mind ACM’s commitment to diversity, equity, and inclusion when nominating. While candidates for advanced member grades (Fellow or Distinguished Member) must be ACM members, candidates for ACM Awards do not need to be members to be nominated. Nominations for most awards are due December 15, 2023.

ACM ByteCast: Mor Peleg

In this episode of ACM ByteCast—part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast—hosts Sabrina Hsueh and Adela Grando welcome Mor Peleg, Professor of Information Systems at the University of Haifa and Founding Director and Head of its Data Science Research Center. 

Peleg shares how she arrived at the intersection of information systems and medicine after working in IT and completing her postdoctoral research at Stanford, and talks about her recent project, MobiGuide, which aims to narrow the gap between clinical guidance and patient needs by providing 24/7 decision support to patients and providers. She also shares advice for people (especially women) looking to work in interdisciplinary fields and emphasizes the importance of health equity and how AI can be employed in the service of detecting unfairness.

ACM ByteCast: Anima Anandkumar

In this episode of ACM ByteCast, Rashmi Mohan hosts Anima Anandkumar, a Bren Professor of Computing at California Institute of Technology (the youngest named Chair Professor at Caltech) and the Senior Director of AI Research at NVIDIA, where she leads a group developing the next generation of AI algorithms. Her work has spanned healthcare, robotics, and climate change modeling. She is the recipient of a Guggenheim Fellowship and an NSF Career Award, and was most recently named an ACM Fellow, among many other prestigious honors and recognitions. 

Anandkumar talks about growing up in a house where computer science was a way of life and family members who served as strong role models, shares her path in education and research at the highly selective IIT-Madras, emphasizes the importance of a strong background in math in her computing work, and reveals some of the breakthrough moments in her career. She also discusses topic modeling and reinforcement learning, what drives her interests, the possibilities of interdisciplinary collaboration, and the promise and challenges brought about by the age of generative AI.

Listen to ACM ByteCast interviews here, or wherever you get podcasts.

Featured ACM Member: Michael E. Caspersen

Michael E. Caspersen is the Managing Director of It-vest—an information technology educational and scientific network which connects three universities in western Denmark—and is Honorary Professor at Department of Computer Science at Aarhus University. He is also the recipient of the 2022 ACM Karl V. Karlstrom Outstanding Educator Award. Caspersen has authored more than 70 papers on various aspects of computing education, and his publications include a two-volume textbook on programming.

In his interview, he discusses starting It-vest, changes in the teaching of programming throughout his career, his work with work with ACM Europe, Informatics Europe, and the Informatics for All coalition, and more.

Read Caspersen’s interview here.

Featured ACM Member: Catherine Flick

Catherine Flick is a Reader in Computing and Social Responsibility at De Montfort University in Leicester, England. Her research interests have included ethics and video games, responsible research and innovation in technology, anonymous technologies, trusted computing, and informed consent in information technology (IT). Flick is Vice Chair and Code Outreach Coordinator for the ACM Committee on Professional Ethics (COPE). ACM COPE developed and continues to promulgate ACM’s Code of Ethics and Professional Conduct. The Code is designed to inspire and guide the ethical conduct of all computing professionals, including current and aspiring practitioners, instructors, students, influencers, and anyone who uses computing technology in an impactful way.

In her interview, she discusses how she became interested in ethics and social responsibility in computing, ACM COPE and working to update ACM’s Code of Ethics and Professional Conduct, mandating ethics courses for Computer Science majors, and more.

Read Flick’s interview here.

Featured ACM Member: Gonzalo Navarro

Gonzalo Navarro is a Professor at the University of Chile. His main research interests are in the design and analysis of algorithms and data structures. He has made important contributions in areas including compressed data structures, text search, graph databases, information retrieval, and metric databases. Navarro currently serves as Editor-in-Chief of the ACM Journal of Experimental Algorithmics (JEA) and is an Associate Editor of ACM Transactions on Algorithms (TALG). He also currently participates in Chile’s Center for Biotechnology and Bioengineering (CeBiB) and the Millennium Institute for Foundational Research on Data (IMFD). 

In his interview, he discusses how he became become interested in algorithms and data structures, his work and insights which have made important contributions to text search, offers advice for young computer scientists creating a productive career, and more.

Read Navarro’s interview here.

View on Demand – ACM TechTalk: Ethical and Responsible Large Language Models

In this episode of ACM TechTalk, “Ethical and Responsible Large Language Models: Challenges and Best Practices,Miquel Noguer i Alonso (Artificial Intelligence Finance Institute), Nicole Königstein (Quantmate), and moderator Angelica Lo Duca (IIT-CNR), explore the challenges and best practices for developing ethical and responsible Large Language Models (LLMs), the importance of transparency and explainability, showcasing methods such as attention visualization and model distillation that provide critical insights into model behavior, and address the control of generated content through techniques including reinforcement learning from human feedback (RLHF), token penalization, external moderation systems, and prompt engineering.

 Finally, they will tackle the issue of bias mitigation, emphasizing the need for transparency in the pre-training data used for these billion-parameter models, diverse and representative data, as well as pre-, in-, and post-processing techniques to ensure fairness in LLMs. 

Visit the TechTalks Archive for our full listing of past TechTalks.