Partha Roop - Episode 93

In this episode of ACM ByteCast, Rashmi Mohan hosts Co-Editor-in-Chief of ACM Books Partha Roop, Professor and Head of the Department of Electrical and Computer and Software Engineering at the University of Auckland (New Zealand), where he Precision Timed Systems research group. Partha's research interests are in safety of AI, ethical AI, and AI applications in cyber-physical systems in digital health, autonomous systems, and ML for real-time systems. His work has both academic and industrial uptake, including recent work on Logical Synchrony Networks with Google. He also co-founded the cloud services company APIMatic, a global leader on automatic SDK generation from APIs. Partha’s work on digital twins of human organs has influenced the work of major partners on this topic, including Mathworks. Partha discusses his accidental entry into CS and how he became interested in formal methods and safety-critical systems. He also talks about the development of reactive processors for predictable timing in safety-critical applications (such as medical devices and adaptive cruise control), and the principles of synchronous programming languages that enable correct-by-construction designs. He shares his entrepreneurial experiences, including the successful APIMatic venture for automated SDK generation. Partha also describes applying engineering methods to developing digital models of human organs to test medical devices such as pacemakers, and his current research on logical synchrony for large-scale distributed systems in collaboration with Google and an autonomous vehicle company. Throughout, he emphasizes mentorship, interdisciplinary collaboration, the need for formal methods in AI safety, and the importance of treating students as future peers while fostering foundational skills in an AI-driven educational landscape.

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.

In this episode of ACM ByteCast, our special guest host Scott Hanselman (of The Hanselminutes Podcast) welcomes 2025 ACM A.M. Turing Award recipients Charles H. Bennett, IBM Fellow at IBM Research and Gilles Brassard, Professor of Computer Science at Université de Montréal. Both are widely recognized as founders of quantum information science. Bennett is an American physicist whose research has shaped the foundations of quantum information science, quantum cryptography, and quantum teleportation, and who has played a central role in establishing quantum information science as a rigorous scientific discipline. Brassard is a Canadian computer scientist widely recognized as the first in the world to have delved into the uncharted territory of quantum information science. Their honors include the Wolf Prize in Physics, the Micius Quantum Prize, the BBVA Foundation Frontiers of Knowledge Award in Basic Sciences, and the Breakthrough Prize in Fundamental Physics. They are both members of the US National Academy of Sciences and the Royal Society, and Brassard is an Officer of the Order of Canada and of the Ordre national du Québec. In the interview, Charles and Gilles recount their chance meeting in Puerto Rico in 1979, which led to a remarkable and fruitful multidisciplinary collaboration. They highlight the role of serendipity in their own scientific discoveries and discuss how their once theoretical ideas became physical technologies, such as the first quantum-cryptography prototype, long-distance fiber experiments, satellite-based quantum key distribution, and rapid advances in quantum computing. They distinguish quantum cryptography from post-quantum cryptography and delve into the near-future implications of powerful quantum computers on information security.

In this episode, part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast, Sabrina Hsueh and Li Zhou host Haider Warraich, a Program Manager at the Advanced Research Projects Agency for Health (ARPA-H) and a practicing cardiologist at Boston Medical Center. At ARPA-H he leads the ADVOCATE program that supports the development, regulation, evaluation and deployment of Clinical Agentic AI to revolutionize care delivery for patients with chronic disease. Previously, he served at the U.S. Food and Drug Administration as a Senior Clinical Advisor for Chronic Disease to the FDA Commissioner, where he helped shape policy around drugs, devices, nutrition, digital health, and AI. Before that, Warraich was a faculty member at Harvard Medical School and Brigham and Women’s Hospital and Director of the Heart Failure Program, at the Veterans Affairs Health System in Boston. He is the author of more than 180 peer reviewed papers and several books. His writing has also appeared in The New York Times, The Guardian and The Atlantic. The episode explores how agentic AI can address critical gaps in chronic disease management, focusing on heart failure and cardiovascular health. Dr. Warraich shares insights from his transition through clinical practice, academic research, the FDA, and his current role at ARPA-H, notably the newly launched ADVOCATE program, an ARPA-H initiative designed to build, evaluate, and deploy FDA-ready, patient-facing agentic AI technologies to serve as clinician extenders. The discussion covers geographic access gaps in care, autonomous agents and “copilots,” the current state of AI evaluation, and extending the ADVOCATE program from heart failure to all chronic disease management.

In this episode, part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast, Sabrina Hsueh hosts engineer and entrepreneur Lucy Guo, co-founder of the infrastructure and software company Scale.AI and founder of Passes, a creator monetization and social media platform. Scale.AI, the data-labeling platform that industrialized human-in-the-loop infrastructure for generative AI and robotics, was acquired by Meta in 2025, making Guo the youngest self-made female billionaire at that time. In the past, she also helped develop Snap Maps as a product designer at Snap and founded Backend Capital, a venture capital firm that primarily funded early-stage engineering startups. Lucy describes her evolution from a childhood hacker into a technology entrepreneur. She stresses a persistent “builder-first,” nimble mindset, the power of surrounding yourself with ambitious peers, solving problems you personally face, and the enduring importance of high-quality data evaluation (especially in high-stakes fields like medicine and clinical trials). She talks about the challenge of pivoting from enterprise data infrastructure to consumer tech, the rising role of female founders and investors enabled by micro-funds; how AI tools are democratizing product-building and design; and her investment focus. Lucy also shares advice for college students and other young builders looking to create a positive and lasting impact.

In this episode of ACM ByteCast, host Juan Miguel de Joya welcomes 2025 ACM Luiz André Barroso Award recipient Ricardo Baeza-Yates, the Search Chief Scientist at You.com, holding part-time professor appointments at KTH Royal Institute of Technology (Sweden), Universitat Pompeu Fabra (Spain), and Universidad de Chile. The award recognizes his pioneering contributions to algorithms and information retrieval as well as his leadership in fostering a vibrant transnational research community across Latin America. Baeza-Yates is widely regarded as one of the world’s foremost researchers in information retrieval, celebrated especially for pioneering innovative data structures that have shaped the field. His work has produced influential algorithms for string searching and fuzzy matching, including the well-known Shift-Or algorithm. As a practitioner, Baeza-Yates served as VP of Research for Yahoo Labs, secured 14 patents, and co-founded several startups in Chile and Spain, including Theodora AI, devoted to mitigating technological bias. Among his honors, he received the CLEI Distinction for Contributions to Computing in Latin America in 2009, the Spanish “Ángela Ruiz Robles” Award for research excellence and entrepreneurship in applied computing in 2018, the 2024 Chilean National Prize for Applied Sciences and Technology, and the first Merit Award from the Chilean Computing Science Society in 2025. Ricardo is a member of Academia Europaea, and a Fellow of ACM and IEEE. He is the co-author of Modern Information Retrieval, which became the field's most cited textbook. Ricardo shares his unconventional path into computing, from influential teachers to his discovery of the mathematical and logical beauty of algorithms. He discusses his current research, which focuses on evaluating AI by examining failures, harm, and risk rather than simply measuring success, since errors can have profound consequences in fields like medicine and law, where users may not have the expertise to recognize errors. He advocates for combining reliable search with AI to provide AI agents with accurate, trustworthy information. The conversation also explores the limitations and social consequences of increasingly replacing traditional search with AI-generated responses, including the risk of "cognitive offloading." Ricardo also shares his views on how AI is shifting computer science, offers advice for future AI developers, highlighting ACM’s principles for responsible computing, and advocates for more inclusion of Latin American perspectives in computing and AI.

In this episode of ACM ByteCast, our special guest host Scott Hanselman (of The Hanselminutes Podcast) welcomes ACM Queue Editorial Board member Kelly Shortridge, Chief Product Officer at Fastly, where she previously served as VP of Security Products. Shortridge is the author of Security Chaos Engineering: Sustaining Resilience in Software and Systems (O'Reilly). An accomplished product executive, software innovator, and internationally recognized technical expert on resilience in complex systems, she is known for the application of behavioral economics, resilience, and DevOps principles to cybersecurity, and modernizing security programs. In the Kelly explains that security chaos engineering is really about resilience engineering—building systems that can recover quickly from inevitable failures. She makes an argument that organizations should prioritize adaptability, redundancy, and recovery over prevention, and encourages greater collaboration between security and platform engineering teams. The wide-ranging conversation covers “metrics theater,” the cost-resilience tradeoff, why software has unique advantages for simulation that we're not leveraging, and where LLMs fit (and don't fit) in security workflows.

In this episode of ACM ByteCast, Rashmi Mohan hosts 2025 ACM Fellow Cynthia Rudin, the Gilbert, Louis, and Edward Lehrman Distinguished Professor of Computer Science, Electrical and Computer Engineering, Statistical Science, Mathematics, and Biostatistics and Bioinformatics at Duke University, where she leads the Interpretable Machine Learning Lab. Her lab, which seeks to design predictive ML models that people can understand, focuses on areas including healthcare, criminal justice, and energy reliability. Among her honors, she has received the Squirrel Award for Artificial Intelligence from the Association for the Advancement of Artificial Intelligence (AAAI), as well as the IJCAI John McCarthy Award. Rudin was recently named an ACM Fellow for contributions to and leadership in interpretable machine learning and societal applications. In the interview, Cynthia clarifies the crucial distinction between "interpretable" and “explainable" AI and makes the argument that true interpretability is foundational to trustworthy, ethical AI. She shares her extensive field experience collaborating with Con Edison engineers on power grid maintenance, neurologists on medical diagnostics, and the Cambridge Police Department on crime series detection, countering the widespread industry myth that AI performance must be sacrificed for transparency. She describes an innovative paradigm her lab developed to solve the "interaction bottleneck" between data scientists and domain experts, leveraging "Rashomon sets" to generate millions of equally accurate models simultaneously, using human-computer interaction (HCI) tools to create visual, encyclopedia-like interfaces.

In this episode of ACM ByteCast, our special guest host Scott Hanselman (of The Hanselminutes Podcast) welcomes ACM Fellow Eric Allman, a foundational figure of the early Internet as the developer of Sendmail and its precursor Delivermail (for the original ARPANET) in the late 1970s at UC Berkeley. Sendmail is the mail transfer agent that powered a large portion of global email infrastructure through the formative years of the network and helped shape how messages move across the web. Allman is also an ACM Distinguished Engineer and was inducted into the Internet Hall of Fame in 2014. The conversation explores the origins of Internet email, the messy realities of building software that must operate at planetary scale, and what lessons today’s engineers can learn from the systems and design decisions that quietly underpin modern computing. Eric shares his work at UC Berkeley spanning a variety of domains, from user interfaces to neural networks. He and Scott touch on current AI capabilities, including their personal experiments in assistive coding with current models such as Claude, and discuss into the programming languages Python, C#, TypeScript, and JavaScript. Eric also shares candid thoughts on letting go of computing after retirement.

In this episode of ACM ByteCast, Rashmi Mohan hosts 2024 ACM/AAAI Allen Newell Award recipient Peter Stone, Professor at the University of Texas at Austin and Chief Scientist at Sony AI. He received the award for significant contributions to the theory and practice of AI, especially in reinforcement learning (RL), multiagent systems, transfer learning, and intelligent robotics. As a leading figure in AI research, Stone has fundamentally advanced how autonomous agents learn, plan, and collaborate. His groundbreaking work on RL algorithms has enabled robots to acquire skills through experience. He is an ACM, AAAI, AAAS, and IEEE Fellow, an Alfred P. Sloan Research Fellow, and a Fulbright Scholar. At UT Austin, he is the founder and director of the Learning Agents Research Group (LARG) within the Artificial Intelligence Laboratory, as well as Founding Director of Texas Robotics. In the past, he also worked at AT&T Labs - Research and co-founded Cogitai, Inc. (acquired by Sony). Peter explores the intersection of professional research and personal passion, detailing how his lifelong love for soccer fueled his involvement in RoboCup, where he aims to develop humanoid robots capable of competing at a World Cup level by 2050. The conversation highlights his leadership as the Chief Scientist of Sony AI, focusing on landmark projects like GT Sophy, an AI that mastered the complexities of Gran Turismo, and the development of FHIBE, an ethically sourced dataset designed to mitigate bias in machine learning. Throughout the interview, Stone emphasizes the importance of ad hoc teamwork—the ability of autonomous agents to collaborate on the fly with unfamiliar partners. He also shares his passion for undergraduate research and advocacy for AI education at all levels.