Prof. Dr. Andreas Butz is a Full Professor and Chair for Human-Computer Interaction at the Department for Informatics, Ludwig-Maximilians-Universität München (LMU Munich). He leads the Media Informatics Group, focusing on innovative interaction techniques and interfaces in immersive environments like VR/AR, automotive systems, and smart spaces. His research emphasizes perceptual user interfaces, social robotics, and designing systems that balance invisibility with transparency. Key research areas include: Virtual/Augmented Reality interfaces for productivity and social interaction AI-driven decision support in safety-critical domains (aviation, healthcare) Haptic and wearable interaction technologies Automotive UI design for driver assistance systems Principles of explainable AI and human-AI collaboration His work bridges theory and practice through projects like: VR-based movement training systems AI trust calibration mechanisms Multi-modal interaction frameworks for automotive environments Systems for analyzing long-term music listening behavior Recent articles explore topics ranging from AI support in pilot decision-making to haptic wearables and creative writing interfaces. His team collaborates with industry partners on electric vehicle information systems and in-car interaction challenges.
Dr. hab. Piotr Łukomski is an Associate Professor at the Department of Political Theory, Institute of Political Science, University of Wrocław. His academic career focuses on the intersection of political theory, philosophy, and cultural analysis, with notable contributions to Hannah Arendt's philosophy, game theory applications in politics, and the role of imagination in political thought. Department: Political Theory Email: piotr.lukomski@uwr.edu.pl ORCID: 0000-0002-5307-616X Research Interests: His work spans conceptual metaphors in political theory, decision-making under hazardous conditions, cultural evolution of tyranny, and the aestheticization of politics. He examines how digital technologies (like VR) reshape political identity and how Arendtian frameworks apply to modern governance. Teaching: Coordinates social consulting labs and teaches decision-making processes in political contexts, with a focus on practical applications in hazardous conditions. Publications: Recent articles analyze VR-era political identity, Hannah Arendt's relevance to modern democracy, and the integration of problem-solving strategies in political thought.
Risto Miikkulainen is a Professor of Computer Science and Neuroscience at the University of Texas at Austin and VP of AI Research at Cognizant AI Lab. He directs the UTCS Neural Networks Research Group and is currently on leave from UT, working on Evolutionary Computation and Deep Learning at Sentient Technologies, Inc. Education: Ph.D. in Computer Science, UCLA, 1990 M.S. in Applied Mathematics, Helsinki University of Technology (now Aalto University), 1986 Risto Miikkulainen's research focuses on biologically-inspired computation such as neural networks and evolutionary computation. His work spans three main areas: (1) Neuroevolution, evolving complex deep learning architectures and recurrent neural networks for sequential decision tasks in robotics, games, and artificial life; (2) Cognitive Science, developing models of natural language processing, memory, and learning that shed light on disorders such as schizophrenia and aphasia; and (3) Computational Neuroscience, studying the development, structure, and function of the visual cortex, episodic memory, and language processing. His research combines theoretical understanding of biological information processing with practical applications for developing intelligent artificial systems. His recent publications (2025) show a strong focus on evolutionary approaches to AI development, particularly in neural architecture search, loss function optimization, and explainable AI. Many papers explore the intersection of evolutionary computation with deep learning, creating more efficient and transparent AI systems. His work spans theoretical foundations and practical applications in areas ranging from environmental control systems to cognitive modeling. Scientific Awards: College of Fellows, International Neural Network Society, 2024 Best Pathway to Impact Award, NeurIPS Climate Change workshop, 2024 AAAI Fellow, 2023 IEEE CIS Evolutionary Computation Pioneer Award, 2020 Gabor Award, International Neural Network Society, 2017 Outstanding Paper of the Decade Award, International Society for Artificial Life, 2017 IEEE Fellow, 2016 Multiple Best Paper Awards at GECCO, CIG, and CEC conferences Deployed Application Award, AAAI/IAAI-2013, AAAI/IAAI-2018 Miikkulainen has extensive experience mentoring students through undergraduate research courses like CS378 Computational Intelligence in Game Design I and II, where students develop independent research projects on the OpenNERO research platform. He has received multiple awards for deployed applications, demonstrating the practical impact of his research. His work has led to the development of the NERO game platform, which serves as both an educational tool and research platform for AI. He directs the UTCS Neural Networks Research Group, which focuses on neuroevolution, cognitive science models, and computational neuroscience. The group has developed the NERO (Neuro-Evolving Robotic Operatives) platform, a machine learning game that allows users to train intelligent agents through evolutionary computation. The group's work spans theoretical research and practical applications in AI, with connections to both academic and industry partners.
Jeehwan Kim is an Associate Professor in Mechanical Engineering and Materials Science and Engineering at MIT. He joined the Mechanical Engineering faculty in 2015 and became a joint faculty member in DMSE in 2016. His research focuses on nanotechnology for computing/electronics, electronic/photonic devices, neuromorphic computing, and heterogeneous integration. He holds over 100 patents from IBM and has received awards like the Samsung Fellow (2022) and DARPA Director’s Award (2021). Education : BS (Hongik University), MS (Seoul National University), PhD (UCLA), all in Materials Science and Engineering. Research Interests : Kim’s group innovates in 2D materials, remote epitaxy, neuromorphic systems, and next-gen electronics. Key areas include monolithic 3D integration, bioelectronic devices, and energy-efficient semiconductors. His work bridges material physics with practical device applications. Awards : Samsung Fellow (2022) DARPA Director’s Award (2021) Young Faculty Award (2019) IBM Faculty Award (2016) IBM Master Inventor (2012) Labs/Teams : Jeehwan Kim Research Group at MIT, focusing on advanced material synthesis and device engineering. Active in cross-disciplinary projects involving AI and semiconductor innovation.
Milos Popovic is a Professor and Director at the Institute of Biomedical Engineering, University of Toronto, and serves as Senior Scientist and Director of Research at the Toronto Rehabilitation Institute (KITE), University Health Network. He holds the Toronto Rehab Chair in Spinal Cord Injury Research and Neural Engineering and co-leads the Centre for Research in Advanced Neural Implant Applications (CRANIA). His leadership spans academic, clinical, and translational research domains in neuroengineering and rehabilitation. His research focuses on neurorehabilitation, neuroprosthetics, functional electrical stimulation (FES), brain-machine interfaces, and assistive technologies . He develops physiological control systems and therapeutic robotics to restore motor function after spinal cord injury and stroke. His work integrates biomechanics, signal processing, and human-machine interfaces to innovate rehabilitative solutions. Dr. Popovic's recent publications emphasize electrical neuromodulation, FES therapy for motor recovery, deep brain stimulation for cognitive deficits, and wearable/implantable technologies . The articles reflect a strong trend toward closed-loop systems, translational research, and interdisciplinary innovation in neuroengineering and rehabilitation. Swiss National Science Foundation Technology Transfer Award - 1st place (1997) Engineering Medal for Research and Development, Professional Engineers of Ontario (2008) Elected to the College of Fellows, American Institute of Medical and Biological Engineering (2011) 1st Prize and Best Intellectual Property Award, TiEQuest Business Venture Competition (2012) Morris (Mickey) Milner Award for Assistive Technologies (2013) University of Toronto Inventor of the Year Award (2013) University Health Network’s Inventor of the Year Award (2015) Dr. Popovic has secured significant research funding and leads the Neural Engineering and Therapeutics team at KITE. He co-founded MyndTec Inc. and the Canadian National Spinal Cord Injury Conference, demonstrating strong mentorship, innovation, and national impact. He advises graduate students and postdoctoral fellows in biomedical engineering and rehabilitation sciences. He leads the Rehabilitation Engineering Laboratory and the Neural Engineering and Therapeutics Team at KITE, fostering collaboration across engineering, neuroscience, and clinical rehabilitation. His lab develops advanced neurotechnologies with a focus on clinical translation and commercialization.
Casey Boyle serves as Associate Professor in the Department of Rhetoric and Writing at the University of Texas at Austin's College of Liberal Arts, where he also directs the Digital Writing & Research Lab. His academic profile demonstrates significant contributions to digital rhetoric, accessibility studies, and posthuman theory through both research and teaching. Boyle's research interests span Rhetorical Theory, Digital Rhetoric, Accessibility, Aesthetics, Digital Humanities, Media Studies, AI & Reading/Writing, Techno-poetics/ethics, and Posthumanism . His work explores how digital technologies reshape rhetorical practices, with particular attention to accessibility as both ethical imperative and theoretical framework. His book Rhetoric as a Posthuman Practice examines information as embodied material practice, arguing that digital rhetoric concerns how bodies become informed through practice that includes not only traditional communication but also how information technologies organize those bodies. Analysis of Boyle's recent publications reveals consistent engagement with posthuman and material approaches to rhetoric, with increasing focus on accessibility, digital environments, and the intersection of rhetoric with environmental concerns. His work demonstrates interdisciplinary reach across philosophy, media studies, and digital humanities, with recurring themes of embodiment, materiality, and the ethics of digital communication. Through his teaching, Boyle offers courses such as RHE 330C (Access Designed), RHE 391 (Rhetoric and Aesthetics), and RHE 325M (Advanced Writing), with course descriptions emphasizing experiential learning and practical application of accessibility principles. His Racing to Empathy project (with Terrance Green) develops immersive digital environments to address implicit bias against Black girls in primary education, while A Version to Access (with Nathaniel Rivers) explores accessibility ontologically through the concept of nonequal design.
Magnus Liebherr is a Professor at the University of Duisburg-Essen , focusing on Technology Acceptance , Artificial Intelligence , and Sustainable Transportation . His work bridges Business Administration with Human-Computer Interaction , exploring how users adapt to emerging technologies like autonomous vehicles and AI systems. Key research areas include: Acceptance of AI applications in mobility Business model development for climate-neutral transportation Cognitive and psychological factors in technology interaction Digital media effects on adolescent well-being Trust calibration in automated systems His recent publications examine Large Language Model dependency , gamified language learning , and mental workload metrics for autonomous vehicles. While no formal awards are listed, his interdisciplinary work spans psychology , engineering , and business strategy .
Ugur Cetintemel is the Khosrowshahi University Professor of Computer Science at Brown University, where he has been since completing his PhD at the University of Maryland in 2001. His research focuses on data management systems, database systems, distributed systems, and stream processing, with recent work integrating AI techniques into database systems. He teaches courses such as Database Management Systems and Data Science fundamentals. Notable contributions include the Aurora and Borealis stream processing engines, S-Store for transaction processing, and DBPal for natural language interfaces. His work emphasizes scalable, efficient systems for large-scale data challenges. Education: PhD in Computer Science, University of Maryland, 2001 MS in Computer Science, Bilkent University, 1996 BS in Computer Science, Bilkent University, 1994 Research Interests: Data management, stream processing, distributed systems, predictive analytics, and AI integration with databases. Key projects include optimizing database systems for modern hardware, developing real-time stream processing frameworks, and exploring interactive data exploration techniques. Grants & Advising: Extensive contributions to grants and collaborations, though specific grant details are not listed. Supervises graduate students in areas like database systems and machine learning integration. Part of the Brown Data Management Group. Labs/Teams: Leads research within the Brown Data Management Group, focusing on advancing database systems for big data and real-time analytics.
Jay Henderson is an Assistant Professor in the Department of Computer Science at Memorial University of Newfoundland, leading the Human-Computer Interaction (HCI) Lab. His research focuses on quantitative HCI, measuring human performance with emerging technologies such as mixed reality and generative AI. He holds a PhD from the University of Waterloo and has held roles including Postdoctoral Fellow at Carleton University and Senior Research Scientist at Huawei Technologies Canada. Education: PhD in Computer Science, University of Waterloo (2021) BSc Hons in Computer Science (minors in Mathematics and Psychology), Mount Allison University (2016) Research Interests: Henderson’s work bridges computer science with psychology and mathematics, emphasizing objective measurement of user interactions. Key areas include mixed reality productivity, generative AI interfaces, gesture-based input, and multimodal feedback systems. His quantitative approach ensures practical insights for technology design. Key Grants & Awards: NSERC Discovery Grant ($155,000 over 5 years) NSERC Discovery Launch Supplement ($12,500) David R. Cheriton Graduate Scholarship ($20,000 over 2 years) Teaching & Supervision: Teaches courses like COMP 4303 (AI for Games) and supervises multiple graduate and undergraduate researchers. Notable supervisees include Daniel Jo (MSc) and Arunav Saha (BSc Honours). Service Contributions: Served on ACM committees including Graphics Interface and CHI Late Breaking Work. Acted as Virtual Chair for ACM ASSETS 2024 and contributed to ACM’s name change policy as a transgender advocate.
Mithuna S. Thottethodi is a Professor and Interim Associate Head of Teaching and Learning at the Elmore Family School of Electrical and Computer Engineering at Purdue University. He holds a B.Tech. from the Indian Institute of Technology, Kharagpur (1996), and a Ph.D. in Computer Science from Duke University (2002). His research focuses on computer architecture, interconnection networks, distributed systems, and security, with notable work on sparse tensor accelerators and processing-near-memory architectures. His work has been funded by the NSF, AT&T, and SK Hynix. Research interests include security, interconnection networks in multicores, storage performance optimization, and memory hierarchies. Notable contributions span hardware accelerators for machine learning, secure speculative execution, and datacenter network congestion control. He has advised over 20 graduate students, many of whom have joined top tech firms like Google, Microsoft, and Intel. Awards: NSF CAREER Award (2007) Wilfred Hesselberth Teaching Excellence Award (2021) Multiple Eta Kappa Nu Outstanding Professor Awards Teaching includes undergraduate courses like EE 437 (Computer Design) and graduate courses such as ECE 666 (Advanced Computer Architecture). He also advises VIP and EPICS student teams.
Anastasia Ailamaki is a Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL), renowned for her work in database systems and data management . Her research focuses on optimizing query processing for modern hardware, particularly GPUs and heterogeneous systems, and advancing cloud data analytics with serverless architectures like PixelDB . She has co-authored influential frameworks for adaptive query optimization , hardware-conscious database engines , and model-relational data management . Key research areas: GPU acceleration , HTAP , query approximation , spatial data processing , and cloud-native databases . Recent work emphasizes cross-task optimizations in distributed environments, efficient sampling , and context-aware joins integrating vector embeddings. In 2023, she contributed to adaptive recursive query optimization and speculative K-means clustering, while 2024 publications addressed proportional caching (HPCache) and model-relational systems . Her collaborations span institutions such as MIT, Microsoft, and ETH Zurich, with publications in top venues like SIGMOD , VLDB , and ICDE .
Lee Miller is a Professor in the Department of Neurobiology, Physiology, and Behavior at the University of California, Davis, College of Biological Sciences. His research integrates neural engineering, physiology, and computational methods to develop communication restoration technologies and investigate sensory processing mechanisms. His primary research interests include neural engineering for speech neuroprosthetics, electrophysiological analysis of speech production, auditory neuroscience, and geometric approaches to neuromuscular signal decoding. He employs surface electromyography (EMG), electroencephalography (EEG), and computational modeling to study brain-machine interfaces for speech restoration and multisensory integration. Recent publications reveal a dominant focus on EMG-based speech neuroprostheses, with geometric and topological analysis of neuromuscular signals emerging as a key methodology. His lab has pioneered non-invasive approaches to speech articulation decoding, created standardized EMG databases, and investigated neural mechanisms of attention in speech-in-noise processing. This work bridges engineering innovation with fundamental neuroscience to address communication disorders. Professor Miller leads the Miller Lab at UC Davis, which specializes in neural engineering for communication restoration. The lab develops real-time speech synthesis systems from neural signals and investigates the physiological basis of speech production and perception using multimodal recording techniques.
David Schuster is an Associate Professor of Physics at the University of Chicago. His primary research focuses on experimental condensed matter physics, with a particular emphasis on circuit quantum electrodynamics (cQED), superconducting qubits, and quantum information science. He leads the Schuster Lab, which explores quantum systems, hybrid quantum technologies, and topological materials. Education: Ph.D. in Physics from Yale University (2007), advised by Robert Schoelkopf. His doctoral work pioneered advancements in circuit QED, demonstrating strong coupling between superconducting qubits and microwave resonators. Research Interests: The lab investigates superconducting quantum circuits, topological photonics, quantum sensors for dark matter, and scalable quantum computing architectures. Projects include developing fluxonium qubits, autonomous error correction, and hybrid systems involving trapped electrons on helium. Key Contributions: Published in Nature , Science , and Physical Review Letters on topics like topological circuits, photon blockade, and dark matter detection using superconducting cavities. Collaborates with groups at Stanford, Purdue, and other institutions on quantum technologies. Students and Collaborators: Advises numerous graduate and undergraduate students, including prominent alumni who have transitioned to postdocs and industry roles. Lab members present at major conferences like the APS March Meeting. Labs: Schuster Lab at the University of Chicago, with access to state-of-the-art facilities like the Pritzker NanoFabrication Facility. Collaborates with the Awschalom, Cleland, and Houck groups on hybrid quantum systems and materials science.
Prof Aaron Thean is the Deputy President (Academic Affairs) and Provost at the National University of Singapore (NUS). Formerly, he served as Dean of the College of Design and Engineering at NUS and held senior roles at IMEC (Belgium) as Vice President of Logic Technologies and Director of Logic Devices Research. His expertise spans advanced semiconductor device technologies, including FinFETs, nanowire FETs, III-V/Ge channels, and emerging beyond-CMOS architectures. He holds degrees from the University of Illinois Urbana-Champaign (B.Sc., M.Sc., Ph.D. in Electrical Engineering) and has published over 300 papers with 50+ patents. His awards include the Gregory Stillman Award (2001) and Compound Semiconductor Innovation Award (2014). Research interests focus on semiconductor innovation, device-process co-optimization (DTCO), and monolithic 3D integration. Notable contributions include industry-first Gate-First HKMG technologies, advanced strained silicon platforms, and neuromorphic computing hardware. His work bridges academia and industry through collaborations with Qualcomm, IBM, and foundry partners. Current initiatives emphasize energy-efficient computing and wearable sensor systems. Prof Thean’s leadership spans NUS-wide academic strategy and global research partnerships. His technical legacy includes foundational advancements in transistor scaling, low-power CMOS design, and AI-driven failure analysis methodologies.
Dr. Jing Li is an Associate Professor and Eduardo D. Glandt Faculty Fellow at the University of Pennsylvania , holding dual appointments in the Electrical and Systems Engineering and Computer and Information Science departments. As co-director of the CyberSavvy nationwide security research center and director of the Penn Computational Intelligence Lab (PennCIL) , she pioneers innovations in non-von Neumann computing paradigms. Her research spans post-CMOS technologies, in-memory computing, and hardware-software co-design for security and AI applications. PhD in Computer Engineering, Purdue University (2009) BSc in Electrical Engineering, Shanghai Jiaotong University (2004) Research Focus: Dr. Li's work addresses fundamental challenges in computer systems across the stack. Key areas include: In-Memory Computing: Liquid Silicon architecture combining RRAM with silicon CMOS through monolithic 3D integration Security Engineering: Transforming computer security from "Art" to formal "Engineering" discipline within CyberSavvy Virtualization: Cloud FPGA abstraction layers decoupling compilation from runtime resource management Graph Analytics: Degree-aware optimization techniques for massive-scale graph processing Deep Learning Systems: Roofline model extensions for FPGA-based CNN acceleration Scientific Impact: Awarded DARPA Young Faculty Award , NSF CAREER Award , and IBM CEO Milestone Award , her team has achieved world records in energy-efficient computing (ENIAD supercomputer). With 46 U.S. patents and over 80 publications, she leads ecosystem development for emerging computing architectures through initiatives like the open-source MEG simulation platform . Community Leadership: Dr. Li serves on program committees for flagship conferences ( ISCA , FPGA Symposium ), chairs the International Memory Workshop , and contributes to the MLsys conference's inaugural committee. She actively mentors through multiple PhD openings and industry collaborations.
