Cicek Cavdar is an Associate Professor at the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology , Sweden. She leads the Intelligent Network Systems research group and specializes in Telecommunication Networks , with a focus on Beyond 5G/6G Mobile Networks , Energy Efficiency , and AI-Assisted Network Management . PhD in Computer Science (2009) from University of California, Davis and Istanbul Technical University Her research spans Cell-Free Massive MIMO , Reconfigurable Intelligent Surfaces (RIS) , UAV Communication Systems , and Green Network Technologies . She actively contributes to 6G Network Architecture and Non-Terrestrial Networks , including satellite and aerial systems. Recent publications highlight AI-driven network optimization for handover management, energy-aware resource allocation , and multi-agent reinforcement learning in complex communication environments. She teaches advanced courses in Communication Systems , Machine Learning , and Software Engineering at KTH.
Snježana Babić serves as Associate Professor and Head of the Graduate Study Program Informatics - Teaching Major at the Faculty of Informatics in Pula , University of Pula. With a PhD obtained in 2016 and university affiliation since 2017, she teaches across undergraduate and graduate programs focusing on ICT fundamentals, web design, digital competencies, and informatics education methodology. Her educational background includes graduation in 1993 followed by doctoral studies culminating in 2016. Though specific institutions aren't detailed in the text, her career trajectory shows progression from foundational ICT teaching to specialized informatics education leadership. Babić's research centers on educational technology adoption with particular emphasis on programming pedagogy for young learners through the MEMA method. Her work investigates digital competencies across multiple educational contexts, from primary schools to higher education. Recent publications demonstrate rapid adaptation to emerging technologies, with 2025 studies examining ChatGPT integration in Croatian educational settings and cross-cultural applications of programming methods. Analysis of her 15 most recent publications reveals consistent focus on technology acceptance models applied to Croatian educators and students. The research trajectory shows evolution from foundational e-learning systems (2016-2020) to cutting-edge AI and robotics applications (2022-2025), maintaining strong methodological focus on teacher motivation , implementation barriers , and culturally-specific adoption factors . Her teaching portfolio demonstrates deep integration with research interests: Undergraduate: ICT Fundamentals, Web Design and Application Graduate: Digital Competencies in Education, Informatics Education Methodology, Practicum for IT Educators Cross-disciplinary: ICT in Nursing, Healthcare Informatics Babić actively contributes to institutional leadership as program head while maintaining robust research productivity. Her work bridges theoretical technology adoption frameworks with practical implementation challenges in Croatian educational contexts, particularly examining how emerging technologies like humanoid robots and AI assistants can be effectively integrated into teaching practices.
Sarita V Adve is the Richard T. Cheng Professor of Computer Science at the University of Illinois at Urbana-Champaign, where she conducts research spanning hardware, programming languages, operating systems, and applications with a focus on domain-specific systems. Her work bridges theoretical foundations and practical implementations, particularly in extended reality and heterogeneous computing. Her educational background includes a Ph.D. and M.S. in Computer Science from the University of Wisconsin-Madison (1993, 1989) and a B.Tech in Electrical Engineering from the Indian Institute of Technology Bombay (1987). Prior to joining Illinois, she served on the faculty at Rice University from 1993 to 1999. Adve's research centers on generalizable and scalable specialization for domain-specific systems, with current emphasis on extended reality (XR) systems including virtual, augmented, and mixed reality. She chairs the ILLIXR consortium to democratize XR research and developed the first fully open-source XR system (ILLIXR). Her foundational contributions include memory consistency models for C++ and Java programming languages, the Spandex coherence framework for heterogeneous systems, and software-driven approaches for hardware reliability. Her work spans hardware reliability (SWAT and RAMP projects), power management (GRACE system), and instruction-level parallelism. Recent publications reveal a strong focus on energy-efficient XR systems, hardware-software co-design for AI workloads, and resilience analysis. Her team explores rendering offload, visual-inertial odometry optimization, and compositional error injection frameworks, often targeting tradeoffs between energy, latency, and accuracy in mobile and edge environments. Fellow of the American Academy of Arts and Sciences Fellow of the ACM and IEEE ACM/IEEE-CS Ken Kennedy Award Anita Borg Institute Woman of Vision in Innovation Award ACM SIGARCH Maurice Wilkes Award Alfred P. Sloan Research Fellowship UIUC University Scholar University of Illinois Campus Award for Excellence in Graduate Student Mentoring Adve actively mentors students and has received multiple teaching awards. She co-founded the CARES movement to address discrimination in CS research events and chairs CS@Illinois CARES. Her service includes leadership roles in ACM SIGARCH (2015-2019), DARPA/ISAT study group, ACM Council, and Computing Research Association. She has secured significant funding including DARPA initiatives and Google Faculty Research Awards. She leads the ILLIXR consortium and has established collaborative research programs such as the $8.3M DARPA Joint University Microelectronics Program. Her lab focuses on open-source XR development, heterogeneous system architectures, and reliability-aware designs, with strong industry and government partnerships.
Michael J. Aziz is the Gene and Tracy Sykes Professor of Materials and Energy Technologies at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS). He serves as Area Chair for Materials Science and Mechanical Engineering and is a Faculty Associate at the Harvard University Center for the Environment. His research focuses on electrochemical engineering for energy and environmental applications, including redox flow batteries, carbon capture, and sustainable energy technologies. Aziz leads the Aziz Group, which develops grid-scale energy storage solutions and innovative methods for CO₂ removal. He holds equity in Quino Energy, a startup commercializing his battery research, and serves as Chief Scientist and Board Member. His work bridges fundamental materials science with practical engineering, emphasizing ClimateTech solutions. Key contributions include aqueous organic redox flow batteries, quinone-based carbon capture systems, and wearable energy storage devices. Education & Affiliations: Affiliated with SEAS since joining Harvard, his academic roles include coordinating the Graduate Consortium for Energy and Environment (2009–2018). His lab (Materials Science Group) is located at McKay 504, with administrative support from Sabrina Azinheira. Research Interests: Aziz's group investigates electrochemical energy storage, CO₂ capture via electrochemical systems, and novel materials for sustainable technologies. They employ advanced techniques like operando electrochemical fluorescence microscopy to study porous electrode dynamics and battery degradation mechanisms. Their work emphasizes scalability and real-world applicability, such as grid-scale battery infrastructure and decarbonization strategies. Recent Trends in Publications: Aziz's recent work emphasizes carbon capture innovations (e.g., acid-base concentration swing methods), hydrogen storage under ambient conditions, and electrochemical synthesis of industrial chemicals like hydrogen peroxide. His group also develops open-source tools like RFBzero for battery modeling and explores bioinspired materials (e.g., self-gelling hydrogel batteries). Awards & Recognition: While no personal awards are explicitly listed in the text, his team members (e.g., Dawei Xi) have received accolades such as the 2025 Carbon Future Young Investigator Award. Aziz's contributions have been recognized through industry partnerships and startup ventures. Advising & Industry Impact: Aziz advises PhD students focusing on electrochemical systems (e.g., Jordan Sosa, Tommy George). His industry engagement includes licensing intellectual property to Quino Energy, which achieved a manufacturing milestone in 2024 for grid-scale battery systems. His research bridges academia and industry, addressing climate challenges through technological innovation. Labs & Teams: The Aziz Group includes interdisciplinary researchers from electrochemistry, chemical engineering, and materials science. Collaborators include institutions like MIT and industry partners. Current projects target next-gen batteries, CO₂ removal systems, and scalable energy storage solutions.
Fabian Suchanek is a full professor at Institut Polytechnique de Paris, specifically affiliated with Télécom Paris. He leads research in the Data, Intelligence, and Graphs (DIG) team within the Computer Science department. His academic career focuses on bridging artificial intelligence with structured knowledge representations. Suchanek's research interests span artificial intelligence, knowledge bases, and natural language processing, with particular emphasis on knowledge graph construction , rule mining , knowledge-based language models , and explainable AI . His work demonstrates how structured knowledge can enhance machine learning systems, particularly large language models, by providing factual grounding and interpretability. The research group he leads develops practical systems that address real-world knowledge management challenges. His recent publications showcase a strong trajectory in knowledge-intensive AI, with notable contributions to knowledge graph completion, rule mining techniques, and neural approaches to knowledge base validation. The research demonstrates increasing integration between symbolic and neural approaches to AI. Best Student Paper Award at KR 2024 for work on contextual reasoning Best Demo Award of IJCAI 2024 for rule mining in knowledge graphs French Open Research Award for the YAGO project Best Paper Award of ESWC 2021 for Neural Knowledge Base Repairs Suchanek has secured significant research funding, evidenced by his active recruitment of PhD students for knowledge-based language model research. He has held visiting positions, including at Nanyang Technological University (June-September 2023), and is recognized internationally through keynote invitations such as the Singapore ACM SIGKDD Symposium 2023. He has deliberately stepped back from administrative duties at Institut Polytechnique de Paris to focus on research. His laboratory maintains strong industry connections through open-source software projects including the YAGO knowledge base, AMIE for rule mining, STACI for explainable AI, and several other tools that have become standard in knowledge representation research.
Marta Kwiatkowska is a Professor of Computing Systems at the University of Oxford and a Fellow of Trinity College. Her research focuses on probabilistic verification , quantitative model checking , and formal methods for complex systems including autonomous robots, medical devices, and biological systems. She leads the development of the PRISM and PRISM-games probabilistic model checkers. Key research areas: Probabilistic systems, formal verification, autonomous robotics, medical device analysis, systems biology Grants: ERC Advanced Grant VERIWARE, EPSRC Programme Grant Mobile Autonomy Awards: 2024 ETAPS Test-of-Time Tool Award for PRISM Students: Current and former advisees in topics spanning formal methods, robotics, and quantitative verification The PRISM-games extension enables verification of stochastic multi-player games with applications in network protocols, autonomous systems, and game theory. Her work bridges theory, algorithms, and practical implementation, with real-world applications in ubiquitous computing and nanotechnology.
Kostas Bekris is a Professor in the Department of Computer Science at Rutgers University, specializing in Robotics and Artificial Intelligence. His research focuses on motion planning, autonomous manipulation, and robot control, with notable contributions to tensegrity robotics, perception-driven systems, and large-scale package handling. He leads a team conducting groundbreaking work in robotics, supported by grants from NSF, NASA, and industry collaborators like ExxonMobil. His group emphasizes interdisciplinary approaches, combining machine learning, topological methods, and differentiable physics modeling to advance robot capabilities in complex environments. Education details are not explicitly stated in the provided texts, but his academic career has included significant mentorship of PhD students and postdoctoral researchers. Key projects involve vision-driven manipulation pipelines, obstacle detection systems (PROBE), and resilient robot designs inspired by biological structures. He has been recognized for his work through prestigious awards including the NASA Early Career Grant and multiple NSF grants, as well as team achievements in robotics competitions like the Amazon Picking Challenge. Research interests span robotics subfields such as: Autonomous manipulation in cluttered environments Learning-based control for dynamic systems Topological data analysis for motion reasoning Tensegrity and soft robotics architectures Sim-to-real transfer in robotic tasks His team's work has produced open-source software tools and datasets, advancing benchmarks in manipulation and perception. Recent articles emphasize scalable solutions for industrial automation and robust navigation strategies in unstructured settings. Scientific achievements include: Development of PROBE for proprioceptive obstacle detection Advances in differentiable physics engines for tensegrity systems NSF-funded projects on robotic rearrangement and modular morphologies Advising contributions span over a decade, with current advisees focusing on topics like non-prehensile manipulation and large-scale storage optimization. Collaborations with industry (e.g., ExxonMobil) and academic partners (Yale University) reflect his commitment to applied robotics research. Labs and teams under his leadership include the Rutgers CS Robotics Group, contributing to projects like the ARIAC challenge platform and packing/industrial automation systems. Future work targets improved robot resilience in disaster scenarios and enhanced human-robot collaboration paradigms.
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.
Shigeru Uesugi is Professor in the School of Creative Science and Engineering, Faculty of Science and Engineering, Waseda University. He directs interdisciplinary research that fuses mechanical engineering, human–robot interaction, and philosophy of technology to create co-creative interfaces, sports-assist devices, and mediated communication systems. Education: Ph.D. in Engineering, Waseda University Research Interests: Uesugi’s work centres on Human Interface & Interaction Design , Mediated Communication , and Being Design . He explores how technology can extend human bodily perception and foster co-creative relationships between users and machines, merging insights from robotics, sports science, and philosophy. Recent articles analyse embodied interaction in shared virtual spaces, remote collaboration via tangible interfaces such as networked “Lazy Susan” tables, and full-body rocking systems that create a sense of togetherness over distance. His publications reveal a steady focus on designing hardware–software hybrids that make remote partners feel co-present. Scientific Awards: 14th Okawa Thesis Award, Honorable Mention (2004) Human Interface Society Paper Award (2004) Grants & Projects: JSPS KAKENHI (A) “Comprehensive research on the relationship between scientific/technological innovation and human society” (2023-2026) JSPS KAKENHI Challenging Research “Transformations of intentionality and responsibility via artifacts” (2022-2025) JSPS KAKENHI “Fascia tension-propagation suit for motor-function enhancement” (2020-2023) Labs & Teams: He leads the Human-being Design Engineering Laboratory whose members develop co-creative interfaces, sports-training devices, and rehabilitation tools. The group maintains the website www.wesugi.mech.waseda.ac.jp and collaborates with the Waseda Research Institute for Science and Engineering.
François Guimbretière is a Professor in the Department of Information Science at Cornell University, with affiliations to the Department of Design & Technology. He holds a PhD in Computer Science from Stanford University and previously served on the faculty at the University of Maryland before joining Cornell in 2009. His research centers on human-computer interaction, human-robot interaction, and interface design, with a strong emphasis on hardware/software co-design to create seamless, sustainable, and innovative interactive systems. His work spans multiple domains including interactive fabrication, remote collaboration, and low-power interfaces. Guimbretière's recent research explores novel fabrication methods such as interactive printing and yarn-based electronics, as well as immersive remote embodiment systems that reduce reliance on physical travel. These efforts reflect a broader trend toward sustainable and accessible interaction technologies. His publications demonstrate consistent contributions to top-tier venues in HCI and ubiquitous computing, focusing on tangible, wearable, and environmentally conscious interfaces. Scientific Recognition: He advises graduate and undergraduate researchers in the development of next-generation interactive systems. His lab supports projects in digital fabrication, remote presence, and sustainable design, often involving interdisciplinary collaboration. While specific grants are not listed, his research trajectory suggests sustained funding in human-centered technology innovation. He leads a research group focused on building practical, user-centered systems that bridge the digital and physical worlds through creative engineering and design. The lab emphasizes hands-on prototyping, real-world deployment, and the integration of traditional craft with advanced technologies.
Lin Ma is currently an Assistant Professor at the University of Michigan, Ann Arbor in the Department of Electrical Engineering and Computer Science (College of Engineering). Previously, they served as a Post Doctoral Fellow at Carnegie Mellon University (2021-2022) and as a Software Engineer at Databricks, Inc. (2022-2023). Research Interests focus on the intersection of database systems and machine learning, particularly in developing self-driving database management systems . Key areas include workload forecasting , automated index optimization , query execution acceleration , and machine learning integration for database automation. Their work explores GPU-accelerated analytics, memory optimization, and transactional consistency models. Academic Contributions span 15+ publications in top venues like VKDB , SIGMOD , and CIDR , including recent 2025 papers on Vortex (GPU memory optimization) and Scompression (workload compression). Earlier work introduced QueryBot 5000 , a workload forecasting framework, and explored anti-caching for storage optimization in OLTP systems. Teaching includes courses like EECS 584: Advanced Database Management Systems and EECS 484: Database Management Systems at the University of Michigan (2023-2025), and 15-445/645 Database Systems at Carnegie Mellon University. Service involves program committee roles for SIGMOD (2023-2025), VLDB (2022-2025), and CIDR (2024-2025). They also served on admissions and search committees at both institutions. Advising includes supervising PhD and MS students: Siyuan (Doug) Dong , Zhongwei Xu , and Haotian (Jack) Gong (co-advised with Barzan Mozafari), among others.
Ning Nan is an Associate Professor at the University of British Columbia's Sauder School of Business, specifically within the Department of Accounting and Information Systems. With a BA from Peking University, an MA from the University of Minnesota, and a PhD from the University of Michigan, Dr. Nan focuses on digital business strategy, evolvable IT infrastructure, and complex adaptive systems. His research explores blockchain applications, agent-based modeling, and the intersection of AI with societal challenges like sustainability. Education: PhD in Information Systems, University of Michigan MA in Information Systems, University of Minnesota BA in Computer Science, Peking University Research Interests: Dr. Nan investigates how technology shapes organizational and societal systems, with a focus on AI ethics, sustainability through personalized recommendations, and blockchain's role in decentralized supply chains. He employs agent-based modeling to simulate complex phenomena like innovation diffusion and online community dynamics. Recent work addresses explainable AI in smart cities and carbon-reduction gamification strategies. Teaching: In 2024-2025, he teaches Data Management for Business Analytics , emphasizing practical applications of data-driven decision-making. Key Research Themes: His articles highlight trends in AI sustainability (e.g., carbon footprint impacts of recommendation systems), digital business strategy (blockchain governance, app update strategies), and foundational IS theory (hyperturbulence and IS strategy).
Professor Marta Zofia Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College at the University of Oxford, where she has held a faculty position since 2007. She previously served as Professor of Computer Science at the University of Birmingham (2001–2007), Reader and Lecturer at the University of Birmingham (1994–2001), and Lecturer at the University of Leicester (1986–1994). Her academic career began as Assistant Professor at the Jagiellonian University in Kraków, Poland (1980–1988). Education: BSc/MSc in Computer Science, Jagiellonian University, Kraków MA, University of Oxford PhD, University of Leicester Research Interests: Professor Kwiatkowska spearheaded the development of probabilistic and quantitative verification methods on the international stage. Her work bridges theory and practice through the PRISM model checker—the leading software tool in probabilistic model checking—used worldwide for research and teaching. Application domains include communication and security protocols , nanotechnology designs , power management , ubiquitous computing and systems biology . She investigates automated verification , temporal logics , semantic models for concurrency , real-time systems , and biological process modelling . Current grant funding exceeds £3.7 million from EPSRC, EU and ERC, including the prestigious ERC Advanced Grant VERIWARE. Scientific Awards & Honours: Fellow of the Royal Society Fellow of the ACM Fellow of the European Association for Theoretical Computer Science (EATCS) Fellow of the British Computer Society (BCS) Fellow of the Polish Society of Arts & Sciences Abroad ERC Advanced Grant VERIWARE (€2.046 M, 2010–2015) Top Cited Article Award, Theoretical Computer Science (2005–2010) Best Paper Award, QEST 2006 Doctoral Supervision & Grants: Professor Kwiatkowska actively supervises doctoral students (D.Phil. at Oxford) and post-doctoral researchers. She welcomes applications in areas aligned with her research interests, detailed here . Current students include Charlie Griffin, Daqian Shao, Matthew Yuan and Minghao Liu; past students and researchers number over twenty, many now in faculty or industry leadership roles. Laboratory & Teams: She leads the Oxford Quantitative Verification group within the Department of Computer Science. Ongoing projects include FUN2MODEL, ELSA, FAIR and the flagship PRISM probabilistic model checker. The group maintains strong collaborations with biological, robotics and engineering teams worldwide.
Kyle C. Hale is an Associate Professor at Oregon State University's School of Electrical Engineering and Computer Science (College of Engineering). He holds a Ph.D. and M.S. from Northwestern University (2016, 2013) and a B.S. in Computer Science from UT Austin (2010). Prior to joining Oregon State in 2024, he served as an Associate Professor at Illinois Tech in Chicago. His research spans operating systems, high-performance computing (HPC), virtualization, computer architecture, and system security. Current work focuses on specialized system software stacks for emerging computing paradigms like memory disaggregation and parallelism optimization. He leads the HExSA Lab and collaborates with the HiPCastor group. Scientific Awards: NSF CAREER Award (2023-2028) Illinois Tech College of Computing Excellence in Research (2023) Illinois Tech College of Computing Excellence in Teaching (2021) Illinois Tech Department of Computer Science Teacher of the Year (2020) EuroSys '22 Best Artifact Award Recent Research Trends: His publications emphasize compiler techniques for memory-disaggregated systems, optimizing parallel runtimes through hardware-software integration, virtualization at fine granularities, and accelerating machine learning workloads via system-level innovations. Keywords include HPC, virtualization, parallelism, and secure execution contexts. Teaching: Courses taught include Computer Architecture (CS/ECE 472), System Security (CSP 544), Operating Systems (CS 450), and advanced topics in serverless/edge computing. He actively recruits PhD students to the HExSA Lab.
Golan Levin is Professor of Electronic Art at Carnegie Mellon University's School of Art, with courtesy appointments in the School of Design, School of Architecture, School of Computer Science, and Entertainment Technology Center. From 2009 to 2022, he served as Director and Co-Director of CMU's Frank-Ratchye STUDIO for Creative Inquiry, a laboratory dedicated to supporting atypical, anti-disciplinary research at the intersection of arts, science, technology, and culture. Levin's research spans interactive art, digital fabrication, information visualization, and generative design. He explores the critical potential of visualization, generative computation for expressive form, and how abstraction connects to realities beyond language. His practice engages interactive gestural robotics, nonverbal interaction aesthetics, and tactical applications of personal digital fabrication through responsive artifacts and media provocations that highlight human-machine relationships. His publications reveal consistent innovation in real-time audiovisual systems, interactive fabrication interfaces, and pedagogic tools for artists. Key trends include slit-scan video techniques, tangible augmented-reality performance, and noise-based visualizations, demonstrating his commitment to expanding human action vocabulary through digital media while bridging artistic expression with computational systems. Levin's work has received significant recognition: Permanent collection inclusion at Museum of Modern Art (MoMA) Whitney Biennial exhibition "50 Designers Shaping the Future" by Fast Company (2012) Competitive grants from National Endowment for the Arts, National Endowment for the Humanities, Creative Capital, and Rockefeller MAP Fund As an educator, Levin teaches "studio courses in computer science" on interactive art, experimental capture, and generative design, emphasizing computation as a medium for critical inquiry. His research funding from major cultural institutions supports interdisciplinary exploration at the arts-technology nexus. The Frank-Ratchye STUDIO for Creative Inquiry, which he directed for 13 years, remains a vital hub for anti-disciplinary collaboration, continuing his legacy of fostering creative agency through technology-infused artistic practice.
