Osbert Bastani is an Associate Professor at the Department of Computer and Information Science, University of Pennsylvania, leading the trustml@Penn research group. He is affiliated with the ASSET , PRECISE , and PRiML centers, and the PLClub research group. His research focuses on Trustworthy Neurosymbolic Systems , Synthesizing Neurosymbolic Programs , and Machine Learning for Programmer Productivity , with applications in verification, fairness, and human-AI collaboration. He received the NSF CAREER Award in 2023. His recent publications (2024-2025) emphasize AI Safety , LLM Robustness , and Algorithmic Fairness , including work on adversarial robustness, conformal prediction, and program synthesis. Students he has advised include Sagnik Anupam, Stephen Mell, Jason Ma, Shuo Li, and others. Awards: NSF CAREER Award (2023)
Richard M. Murray is the Thomas E. and Doris Everhart Professor of Control and Dynamical Systems and Bioengineering at the California Institute of Technology (Caltech). He holds a B.S. from Caltech (1985), M.S. from UC Berkeley (1988), and Ph.D. from UC Berkeley (1990). He has served in academic roles from Assistant Professor (1991–1997) to his current endowed professorship. He chaired the Engineering and Applied Science division (2000–2005) and Biology and Biological Engineering (2020–2024). His research focuses on feedback control in biological and autonomous systems, synthetic cells, and networked control systems. Collaborators include experts in robotics, synthetic biology, and systems biology. Key awards include the IEEE Control Systems Award and election to the National Academy of Engineering. His educational contributions span courses on control systems, robotics, and bioengineering. Current research projects include the Developer Cell initiative (Sloan Foundation), layered testing for autonomous systems (AFOSR), and microbiome-based environmental solutions (CHARMME, ARO). He advises numerous graduate students and postdocs, with notable alumni in academia and industry. Labs include facilities in Keck and Steele laboratories at Caltech. His work bridges control theory, synthetic biology, and autonomous systems to address societal challenges like environmental monitoring and safe autonomy.
Adriana Tapus is a Full Professor at ENSTA Paris, affiliated with Institut Polytechnique de Paris, leading the Autonomous Systems and Robotics Laboratory (SAR) within the Computer Science and Systems Engineering Unit (U2IS). She holds an HDR (Habilitation) and a PhD from EPFL, Switzerland, with postdoctoral experience at USC. Her research focuses on socially assistive robotics, human-robot interaction (HRI), and personalized therapy for individuals with physical/cognitive impairments. She directs the IP Paris Doctoral School and coordinates national/international projects like the EU-funded ENRICHME and SWEET. Education: PhD in Mobile Robotics, EPFL (2005) Habilitation (HDR), ENSTA Paris (2011) M.S. Computer Science, University Joseph Fourier Engineer, Politehnica University of Bucharest Research Interests: Tapus pioneers socially assistive robotics, integrating machine learning, human modeling, and multimodal communication (verbal/non-verbal/para-verbal). Her work addresses adaptive therapies for vulnerable populations using robotics, physiological data interpretation, and context-aware interaction. Key themes include: Human-robot cooperation and trust Emotion recognition and expression Personalized rehabilitation systems AI ethics and human-centered design Publications: Over 150 articles, with recent work exploring humor in HRI, teleoperation trust models, and cross-cultural intelligent vehicles. Notable 2025 contributions include studies on robot laughter efficacy and multimodal facial expression frameworks. Awards: 2025: 4 IROS papers accepted 2016: 25 Women in Robotics recognition 2010: Romanian Academy Award Multiple conference best paper awards (RO-MAN, ICRA, etc.) Advising & Grants: Supervised over 20 PhD students and led projects like EU Horizon 2020 ENRICHME. Current students focus on teleoperation dynamics, robot humor, and haptic interfaces. Active in editorial roles (IJSR, THRI) and conference organization (HRI General Chair 2019). Labs/Teams: Founder of RoboticsByDesign lab and co-initiator of the Hi! Paris interdisciplinary AI center. The SAR lab develops systems for healthcare, education, and human-robot collaboration.
Karthik R. Narasimhan is a Professor at Princeton University's School of Engineering and Applied Science in the Department of Computer Science. Previously, he earned his PhD from MIT under Regina Barzilay and served as a visiting research scientist at OpenAI during 2017-18. His research focuses on the intersection of language and decision-making, building autonomous agents that learn from both experience and human knowledge. His research spans multiple high-impact areas including language agents (Text-DQN, CALM, ReAct, Tree of Thoughts), reinforcement learning (h-DQN, Multi-Objective RL), and AI safety (Toxicity in ChatGPT, DataMUX). He has developed critical datasets and benchmarks such as WebShop, InterCode, SWE-bench, and SILG that have become standard evaluation tools in the field. Current work emphasizes agent capabilities, software engineering automation, and multimodal interaction. His publication trends show strong focus on practical agent deployment (SWE-agent, Tree of Thoughts), safety evaluation (Probing AI Safety), and efficiency improvements (DataMUX). Recent work increasingly addresses real-world challenges in software engineering, security, and human-AI collaboration through rigorous benchmarking. Co-author of foundational GPT (2018) paper Key developer of Text-DQN (2015), CALM (2020), ReAct (2022), Tree of Thoughts (2023) Creator of influential benchmarks: WebShop (2022), SWE-bench (2023), InterCode (2023) He actively advises students through Princeton's computer science program, with research supported by multiple grants focused on autonomous agent development and language-based decision systems. His GitHub repositories (nlp-datasets, text-world-player) demonstrate strong community engagement in open-source research tools. Current projects include advancing language agent capabilities through Reflexion (2023) and Tree of Thoughts (2023) frameworks while addressing critical safety and efficiency challenges.
Prof. Dr. Timothy Roscoe is a Full Professor in the Department of Computer Science at ETH Zurich. His research focuses on operating systems, networking, and distributed systems. He was inducted as an ACM Fellow in 2014 for contributions to these fields. Previously, he worked at Intel Research Berkeley, UC Berkeley (Adjunct Professor), and Sprint Labs. His work includes foundational contributions to systems like PlanetLab, P2 Declarative Networking, and the Nemesis OS. Roscoe holds a PhD from the University of Cambridge and has led projects in cloud computing, wide-area network measurement, and secure systems design. His current research emphasizes hardware-software co-design, formal verification of systems, and scalable memory architectures. Education: PhD in Computer Science, University of Cambridge (1995) Key Roles: Principal Researcher at Intel Berkeley Lab, Visiting Researcher at National ICT Australia Research Highlights: Contributions to distributed systems (PlanetLab), declarative networking (P2), and secure microkernels (seL4 integration). Current projects address challenges in disaggregated memory systems, coherent interconnects, and trustworthy embedded systems. Awards: ACM Fellow (2014), numerous grants and industry collaborations. Labs/Teams: Systems Group at ETH Zurich, focusing on OS design, hardware architectures, and formal methods.
Andy Pavlo is an Associate Professor with Indefinite Tenure in the Computer Science Department at Carnegie Mellon University's School of Computer Science. He is an active member of the CMU Database Group and the Parallel Data Laboratory, where he leads research in database management systems with a focus on self-driving architectures, transaction processing, and large-scale analytics. His work bridges academic research and industry applications through projects like NoisePage, OtterTune (which he co-founded and served as CEO before it ceased operations), and Peloton. Dr. Pavlo's research interests span database management systems with particular emphasis on autonomous database architectures that can self-tune and optimize without human intervention. His work explores transaction processing systems that can handle high-throughput workloads while maintaining consistency, and large-scale data analytics techniques that efficiently process massive datasets. He has made significant contributions to query optimization, database extensibility, and automatic database tuning using machine learning techniques. His recent work on database extensibility revealed critical issues in PostgreSQL's extension ecosystem, showing that approximately 16% of extensions are incompatible with at least one other extension due to API violations and memory errors. His research output demonstrates a consistent focus on practical database systems challenges, with recent publications examining database extensibility, user-defined function optimization, and the cyclical nature of database research. The articles show a strong trend toward making database systems more autonomous, with increasing integration of machine learning techniques for automatic tuning and optimization. His work often combines deep theoretical analysis with practical implementation in open-source systems. Dijkstra Award 2024 for contributions to database systems research Dr. Pavlo actively mentors graduate students, with current advisees including Wan Shen Lim, William Zhang, and Sam Arch (co-advised with Todd Mowry). His former students have gone on to successful careers in both industry and academia. He has secured significant research funding through CMU's affiliate program with major database companies including ClickHouse, DataStax, dbt, Firebolt, MotherDuck, RelationalAI, SingleStore, Spiral, PingCAP/TiDB, Yellowbrick, and Yugabyte. His research is supported by these industry partnerships and likely includes NSF funding given his active participation in the database research community. At CMU, Dr. Pavlo leads the Database Group and organizes several seminar series including "SQL or Death," "Database Building Blocks," and "ML⇄DB Technical Talks." These seminars bring together researchers and practitioners to discuss cutting-edge developments in database systems. He also runs a summer research internship program that has attracted students for multiple consecutive years, indicating a strong research group with ongoing projects and funding.
Matteo Sonza Reorda is a Full Professor at the Polytechnic University of Turin, affiliated with the Department of Automatic Control and Computer Science (DAUIN). He holds roles such as Partnership Agreement Coordinator with SMAT and has served as Vice-Rector for Research (2021–2024). His research focuses on fault tolerance, hardware reliability, and AI acceleration, with contributions to GPU/CNN reliability, self-test libraries, and defect-oriented testing. Education: M.S. in Electronics Engineering, Politecnico di Torino (1986) Ph.D. in Computer Engineering, Politecnico di Torino (1990) Research Interests: His work spans automatic test equipment, circuit reliability, GPU fault tolerance, neural network hardening, and embedded systems safety . He leads the Electronic CAD & Reliability Group and collaborates with institutions like the ISI Foundation and the National Research Council (CNR). Publications & Impact: With over 180 publications, his recent work emphasizes AI accelerator reliability, fault injection techniques, and safety-critical systems. Key trends include GPU resilience for CNNs, self-test library optimization, and radiation fault modeling in neural networks. Awards & Recognition: IEEE Fellow (2016–) Multiple best-paper awards at IEEE conferences (DDECS, DATE, etc.) Grants & Collaborations: Coordinator of EU projects (RESCUE, TUTORIAL) Partnerships with EDF, Marelli Europe, and SMAT Lead on National HPC/Quantum Computing Spoke 1 (2022–2025) Labs/Teams: Leads the CAD Group and collaborates with the French-Italian LIA LAFISI lab on hardware-software integration.
Qi Alfred Chen is an Assistant Professor in the Department of Computer Science at the University of California, Irvine (UCI), within the Donald Bren School of Information and Computer Sciences. He also holds affiliations with the Department of Electrical Engineering and Computer Science (EECS), the Institute of Transportation Studies at UC Irvine (ITS-Irvine), the Center for Embedded and Cyber-physical Systems (CECS), the Institute for Software Research (ISR), and the UC Irvine Cybersecurity Policy & Research Institute (CPRI). His research focuses on network and systems security, with particular emphasis on autonomous vehicle and IoT security. Dr. Chen received his Ph.D. from the University of Michigan in 2018. His educational background has prepared him for his current research in security of critical computer systems. His work bridges theoretical security principles with practical implementations in real-world systems. Chen's research interests center on network and systems security , with a major focus on smart systems and IoT security , particularly in transportation and autonomous vehicle systems . His work addresses security challenges through systematic problem analysis and mitigation, discovering and mitigating security problems in next-generation transportation systems, smartphone OSes, network protocols, DNS, GUI systems, and access control systems. His research has high impact in both academic and industry contexts, with over 10 top-tier conference papers, a DHS US-CERT alert, multiple CVEs, and coverage in major news media like Fortune and BBC News. His publication record shows a clear evolution from foundational work on network protocols and smartphone security toward increasingly sophisticated security analyses of autonomous vehicle systems and AI-powered transportation technologies. The research trajectory demonstrates growing technical sophistication and real-world impact, with recent work focusing on physical-world adversarial attacks against autonomous driving perception systems, LiDAR spoofing, and security of multi-sensor fusion in autonomous vehicles. NSF CAREER Award (2022) on securing the AI stack in emerging autonomous and connected CPSs Chancellor's Award for Excellence in Undergraduate Research Mentorship, UC Irvine (2021) 5th place nation-wide at National CCDC competition (2021, as faculty advisor) 1st place (Gold Medal) at CCDC Western Regional competition (2021) ProQuest Distinguished Dissertation Award, University of Michigan (2019) Dr. Chen has mentored numerous successful students, including PhD candidates and undergraduates who have gone on to positions at major tech companies like Meta, Uber, Amazon, and Intel. His research group has secured significant funding, including an NSF CAREER award, and has made substantial contributions to the field through high-impact publications and vulnerability disclosures. He is also the co-founder of the ISOC VehicleSec Symposium and has organized the AutoDriving CTF contest at DEF CON. Chen leads the AV & IoAT Security Research Group at UCI, focusing on security challenges in autonomous vehicles and the broader Internet of Autonomous Things. His team has developed numerous attack demonstrations and security analyses that have received significant media attention and influenced industry practices. The group maintains an active YouTube channel showcasing their security research.
Javier Alonso-Mora is a Professor in the Department of Mechanical Engineering at Delft University of Technology, specializing in Learning & Autonomous Control. His research focuses on autonomous systems, robotics, motion planning, and transportation logistics, with applications in mobile manipulation, dynamic environments, and urban mobility. He leads key projects such as INTERACT (Intuitive Interaction for Robots among Humans) and ACT (Perceptive Acting Under Uncertainty), exploring human-robot interaction, autonomous vehicles, and healthcare robotics. Notable achievements include an ERC Starting Grant (2022) and a Veni Grant (2017). His work addresses challenges in robot navigation, control systems, and fleet optimization, with contributions to both theoretical advancements and practical implementations. Projects like TRiLOGy focus on sustainable water transportation, while HARMONY advances assistive robotics in healthcare. Alonso-Mora’s research leverages geometric fabrics for motion planning, probabilistic modeling for dynamic environments, and multi-agent coordination. He collaborates internationally and contributes to open-source frameworks for robotics. His recent publications emphasize safety-aware control, instance-aware semantic mapping, and adaptive systems for cluttered environments.
Hoda Heidari is the K&L Gates Career Development Assistant Professor in Ethics and Computational Technologies at Carnegie Mellon University (CMU), with joint appointments in the Machine Learning Department and the Institute for Software, Systems, and Society. She is affiliated with the Human-Computer Interaction Institute and the Heinz College of Information Systems and Public Policy, and co-leads the university-wide Responsible AI Initiative and K&L Gates Initiative for Ethics and Computational Technologies. Education: PhD in Computer and Information Science (University of Pennsylvania), MSc in Statistics (Wharton School) Her research focuses on the Ethical, Societal, and Policy Implications of AI , particularly fairness and accountability in high-stakes domains. Her work includes evaluating risks/benefits of general-purpose AI, human-AI decision-making systems, and AI governance frameworks. She has received multiple awards, including best paper honors at AIES, FAccT, and SAT-ML. Her research is supported by the NSF Program on Fairness in AI, PwC, CyLab, Meta, and J. P. Morgan. Recent Publications examine generative AI safety, fairness measurement, AI incident documentation, and ethical governance. Her teaching includes courses on Responsible AI, ML Ethics, and Societal Decision-Making, with a focus on preparing students to critically analyze AI's societal impact. Scientific Awards: Best Paper (AIES 2024, FAccT 2021, SAT-ML 2023), Exemplary Track Award (EC 2021) Grants: NSF, PwC, CyLab, Meta, J. P. Morgan She advises doctoral students and postdocs across CMU departments and collaborates with interdisciplinary teams. Her service includes organizing AI safety workshops and advising on NIST guidelines for AI red-teaming.
Dr. Mohammad Zulkernine is a Full Professor and Canada Research Chair in Cyber-Physical System Security at Queen’s University’s School of Computing (Faculty of Arts and Science). He leads the Queen’s Reliable Software Technology (QRST) research group and directs the Queen’s Centre for Security & Privacy. His research focuses on secure software systems for cyber-physical systems, including autonomous vehicles, IoT, and cloud computing. Dr. Zulkernine holds a cross-appointment in Electrical and Computer Engineering and is a licensed Professional Engineer in Ontario. Education: BSc (Bangladesh BUET), MEng (Japan), PhD (University of Waterloo). He joined Queen’s in 2003 and has held sabbaticals at University of Trento, Italy and Irdeto Canada. He has published over 250 papers, led 35+ research projects, and supervised 120+ students. Awards include Canada Research Chairs (Tier I and II), Queen’s Excellence in Graduate Supervision Award, and Distinguished Supervision Award from the School of Computing. Research Interests: Cyber-Physical System Security, Software Reliability, IoT Security, Vehicle Networks, Secure Software Engineering, and Cybersecurity Risk Assessment. Active industry collaborations include EU-funded projects and Canada-Africa initiatives.
Dr. Hiren Patel is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. He holds a Doctorate in Computer Engineering from Virginia Tech and previously worked as a postdoctoral fellow at UC Berkeley under Edward A. Lee. His research focuses on real-time embedded systems, computer architecture, machine learning hardware, and cybersecurity. He teaches courses like ECE 150 (Programming), ECE 320/429 (Computer Architecture), and ECE 327 (Digital Systems). Research Interests: Cyber-physical systems and hybrid architectures Hardware/software co-design methodologies Predictable cache coherence protocols IoT and edge computing systems Security in embedded and real-time systems Recent work emphasizes cache coherence solutions for safety-critical systems and GPU acceleration strategies. His publications address challenges in multicore predictability, FPGA bandwidth optimization, and autonomous robotics orchestration. No specific awards are listed, though his extensive publication record indicates significant contributions to embedded systems research. He currently oversees graduate student applications focusing on his core research areas.
Prof. Dr. Melanie Zeilinger is an Associate Professor at the Department of Mechanical and Process Engineering at ETH Zurich, leading the Intelligent Control Systems group at the Institute for Dynamic Systems and Control. She holds a diploma in Engineering Cybernetics from the University of Stuttgart (2006) and a Ph.D. in Electrical Engineering from ETH Zurich (2011). Her postdoctoral research included stints at EPFL (2011–2012), a Marie Curie fellowship at UC Berkeley and the Max Planck Institute (2012–2015), and a professorship at the University of Freiburg (2018–2019). Her research focuses on learning-based control, distributed control systems, and robotics , with applications to medical devices (e.g., hydrocephalus shunts) and human-in-the-loop systems. She organizes the Conference on Learning for Dynamics and Control (L4DC) and contributes to initiatives like the "Algorithm on My Team" project. Her awards include the ETH Medal for her PhD thesis, a Marie-Curie IO Fellowship , and an SNF Assistant Professorship grant . She serves as an Associate Editor for IEEE Control Systems Letters and actively reviews for top journals/conferences like IEEE TAC, Automatica, and NeurIPS. Key projects include: VIEshunt: A smart ventricular shunt for hydrocephalus treatment, combining control systems and medical engineering. Autonomous Racing: Contextual tuning and safety-certified learning-based MPC for real-time obstacle avoidance. Data-Driven Control: Integrating Gaussian processes and state-space models into MPC frameworks for uncertain systems. Her work bridges control theory, machine learning, and robotics, addressing societal challenges such as healthcare and energy efficiency.
Bryan H. Choi is an Associate Professor of Law at the University of Colorado Law School , where he bridges law and computer science to address software and AI safety. His work on software liability has influenced national cybersecurity strategy discussions. As an Adviser for the ALI Principles Project on Civil Liability for Artificial Intelligence , he shapes legal frameworks for emerging technologies. Education : JD and AB in Computer Science from Harvard University; clerkships with U.S. Court of Appeals judges Leonard I. Garth and William C. Bryson. Roles : Former joint appointment at Ohio State University Law School and Computer Science Department; Faculty Fellow at UPenn's CTIC; Director of Law and Media at Yale's ISP. Research Focus : Choi's scholarship examines software liability , AI accountability , and privacy law through interdisciplinary lenses. He critiques institutional approaches to software safety and advocates for empirical legal frameworks over participation-based models. Recent Articles address AI malpractice , NIST software standards , and forensic tool validation , reflecting trends in AI regulation and cyber-physical system liability . His 2021 NSF grant funded technical-legal methods for safety-critical systems. Awards & Grants : National Science Foundation (NSF) Grant (2021) Adviser, ALI Principles Project on Civil Liability for Artificial Intelligence Community Engagement : Active in Law and Computer Science communities , serving on committees for the ACM Symposium , Cybersecurity Law and Policy Scholars Conference , and co-organizing the AAAI Bridge Program on AI and Law .
Aaron D. Ames is the Bren Professor of Mechanical and Civil Engineering, Control and Dynamical Systems, and Aerospace at the California Institute of Technology (Caltech). He serves as the Booth-Kresa Leadership Chair and Director of the Center for Autonomous Systems and Technologies since 2025. His academic journey includes a BS in Mechanical Engineering and BA in Mathematics from the University of St. Thomas (2001), followed by an MA in Mathematics and a PhD in Electrical Engineering and Computer Sciences from UC Berkeley (2006). Research Interests span theoretical and experimental work in hybrid systems, nonlinear control, and bipedal robotic locomotion. Specific focus areas include: Control Barrier Functions (CBFs) for safety-critical systems Powered prostheses and robotic assistive devices Legged locomotion for bipedal and quadrupedal robots Cyber-physical systems and autonomous control Model predictive control and real-time optimization Humanoid robotics and geometric safety filters Recent publications emphasize risk-aware control, safety verification, and locomotion on constrained environments, with applications to drones, exoskeletons, and quadrupedal robots. His work often integrates theoretical advancements with practical validation through the AMBER Lab. Scientific Awards & Honors : NSF CAREER Award (2010) Donald P. Eckman Award (2015) Leon O. Chua Award (2005) Bernard Friedman Prize (2006) Teaching includes graduate courses on nonlinear control, hybrid systems, and robotics at Caltech, alongside prior roles at Georgia Tech and Texas A&M. He leads the AMBER Lab (Bipedal Robotics) and has secured major grants from the National Science Foundation, NASA, and industry partners like Miso Robotics and SRI International.
