ACM ByteCast is a podcast series in which hosts Rashmi Mohan and Jessica Bell interview researchers, practitioners and innovators who are at the intersection of computing research and practice. In each monthly episode, guests will share their experiences, the lessons they’ve learned, and their own visions for the future of computing. Listen wherever you get your podcasts.

In this episode of ACM ByteCast, host Juan Miguel de Joya is joined by 2026-2027 ACM Athena Lecturer Monika Henzinger, Professor and Vice-President of Technology Transfer at the Institute of Science and Technology Austria (ISTA). Her career spans some of the most important developments in modern computer science, from foundational work on dynamic graph algorithms to the early days of web search at AltaVista and Google. She was the first Director of Research at Google, where she contributed to the development of large-scale web search technologies, and a member of Research Staff at Digital Equipment Corporation’s Systems Research Center. An ACM and EATCS Fellow, she is also a member of the Academia Europaea, the German National Academy of Sciences Leopoldina, and the Austrian Academy of Sciences. Her honors include two ERC Advanced Grants, the Carus Medal of the Leopoldina, the Wittgenstein Award of the Austrian Science Fund, the European Young Investigator Award, and the NSF Career Award. She was recognized with the Athena Lecturer award for outstanding contributions to the fields of dynamic graph algorithms and web algorithms, and for dedicated mentoring and service to these communities. Monika discusses her CS journey, from her teenage fascination with astronomy to discovering programming and eventually specializing in algorithmic research. She introduces dynamic algorithms, which efficiently update solutions as systems change., with some real world examples. Monika also shares her work in web information retrieval and privacy, and stories from the early days of search engines like AltaVista and Google, which prompted research into scalable indexing and better-ranked results. She also connects her industry experience to developments in modern AI, and the importance of balancing ML with the reliability of traditional algorithms when predictions fail. Juan and Monika also touch on differential privacy and the need for governments to establish privacy and security standards, and the exciting promise of LLMs to improve algorithms.