Prof. Dr. Günther Dissertori is a Full Professor and Rector of ETH Zurich, where he oversees teaching and academic affairs. His academic journey began at the University of Innsbruck, followed by a doctoral position at CERN, and he joined ETH Zurich as an Assistant Professor in 2001 before becoming a Full Professor in 2007. Academic Role: Full Professor of Particle Physics Institutional Leadership: Rector of ETH Zurich (since 2022) Contact: guenther.dissertori@sl.ethz.ch Research Interests: Dissertori's work spans Particle Physics and Experimental Physics , notably contributing to the CMS experiment at CERN, which was instrumental in the Higgs boson discovery. His group also developed cost-effective PET devices, leading to the spin-off Positrigo AG . Research keywords include Detector Development , Medical Imaging , and Quantum Physics . Teaching Excellence: Recognized with multiple Golden Owl awards (2005–2020) and the Credit Suisse Award for Best Teaching (2013), Dissertori is celebrated for his pedagogical impact in the Department of Particle Physics. Scientific Contributions: His publications include advancements in CMOS technology, quantum dynamics, and medical applications, reflecting interdisciplinary expertise in high-speed electronics, environmental science, and architectural history.
Professor Harry E. Ruda holds the Stanley Meek Chair in Advanced Nanotechnology at the University of Toronto's Faculty of Applied Science and Engineering. He directs the Centre for Advanced Nanotechnology and leads the Electronic-Photonic Materials Group. His research spans semiconductor nanostructures, focusing on nanoelectronics and nanophotonics, with notable contributions to nanowire growth, quantum transport, and plasmonic effects. Education: B.Sc. in Physics, Imperial College London Ph.D. in Physics, MIT His research interests include: Semiconductor nanowire growth via VLS process Quantum transport and spintronics Nonlinear optical effects in quantum dots/nanowires Surface state control through passivation Photonic crystal structures for optical devices Carrier dynamics in low-dimensional systems Recent publications highlight advancements in InAs nanowire sensors, Coulomb impurity effects, photonic crystal design, and hybrid superconducting/semiconductor devices. His work bridges fundamental electron dynamics and applied quantum technologies. Scientific Awards: Fellow, Canadian Academy of Engineering Fellow, Royal Society of Canada Fellow, Institute of Physics (UK) Fellow, Institute of Nanotechnology Fellow, Institution of Engineering and Technology Fellow, Institute of Materials, Minerals and Mining Fellow, Canadian Academy of Engineering Teaching: MSE335: Materials Physics MSE490: Professional Ethics and Practice MSE1023: Quantum Transport
Scott Barnett is a Professor of Materials Science and Engineering at Northwestern University , specializing in ceramic thin films and electrochemical systems for energy applications. His research spans over 25 years in solid oxide fuel cells (SOFCs) and lithium-ion battery electrodes, with a focus on 3D printing, thin electrolyte deposition, and microstructural evolution under operational stress. Education: Ph.D. and B.S. in Metallurgy and Physics from the University of Illinois at Urbana-Champaign. Research Interests center on: Reversible solid oxide cells for energy storage 3D tomographic imaging of electrode microstructures Novel processing methods for ceramic materials Electrochemical stability and degradation mechanisms Recent Publications highlight advancements in: Pressurization effects on oxygen electrodes 3D printed SOFCs with enhanced performance Nanoparticle infiltration for fuel electrode stability Impedance modeling of lithium-ion batteries Scientific Awards include: Fulbright Scholar (2015) Cheng Tsang Man Endowed Professorship (2008) Office of Naval Research Young Investigator (1986) AVS Fellow (1998) Advising Legacy encompasses over 30 graduate students and postdocs, including Nicholas Geisendorfer (NASA Space Technology Fellow) and Matthew Lu (now at Tesla), with notable alumni placements at institutions like Bloom Energy and Microsoft . His lab employs advanced characterization techniques to predict long-term durability of electrochemical devices.
Ana Klimovic is an Assistant Professor at the Department of Computer Science, ETH Zürich, and Deputy Head of the Institute for Computing Platforms. She leads the Efficient Architectures and Systems Lab (EASL) and focuses on optimizing cloud computing performance and resource efficiency. Education: Ph.D. in Electrical Engineering (Stanford University), M.S. in Electrical Engineering (Stanford), B.A.Sc. in Engineering Science (University of Toronto) Previous Roles: Research Scientist at Google Brain Her research spans cloud computing, operating systems, distributed systems, and their intersection with machine learning. Key areas include cloud-native programming models, elastic storage, GPU sharing, and data pipeline optimization. The 2025-2024 articles highlight trends in serverless computing, large language model (LLM) serving, GPU optimization, and data-centric ML systems. Themes include elasticity, resource multiplexing, heterogeneous computing, and infrastructure for AI/ML workloads. Scientific Awards: Microsoft Research PhD Fellowship, Stanford Graduate Fellowship She has led research projects on ephemeral storage, distributed training automation, and cost-efficient ML preprocessing, with grants from Microsoft Research and Stanford.
Professor Todd Squires is a distinguished faculty member in the Department of Chemical Engineering at the University of California, Santa Barbara, within the Robert Mehrabian College of Engineering. His research focuses on the fundamental principles of transport phenomena as applied to interfaces, membranes, and complex fluids, employing theoretical, computational, and experimental approaches to address significant challenges in micro-scale fluid mechanics. Dr. Squires' educational background includes: BS in Physics, UCLA (1995) BA in Russian Language and Literature, UCLA (1995) PhD in Physics, Harvard University (2002) His research interests span microfluidics and electrokinetics, active and nonlinear microrheology of complex materials, polymer dynamics and sensors, with particular emphasis on non-linear electrokinetic flows, interfacial rheology, and the self-assembly of nanostructured materials. His work bridges fundamental fluid mechanics with practical applications in microfluidic devices, energy storage, and biomedical systems, demonstrating the versatility of this fascinating field. Analysis of Professor Squires' recent publications reveals a consistent focus on interfacial phenomena, with particular attention to the rheological properties of fluid interfaces, particle dynamics in complex fluids, and novel microfluidic techniques for measuring and manipulating these systems. His research demonstrates strong interdisciplinary connections between chemical engineering, physics, and materials science, with applications spanning energy storage, biomedical engineering, and environmental systems. Professor Squires has received numerous prestigious awards and honors: 2018 Robert W. Vaughan Lecture in Chemical Engineering, Caltech 2015 Elected Fellow of the American Physical Society 2013 Mid-Career Award, American Electrophoresis Society 2012 The Dudley Saville Memorial Lecture at Princeton 2010 Pierre Gilles de Gennes Prize 2010 Allan P. Colburn Memorial Lectureship, University of Delaware 2009 Francois Frenkiel Award for Fluid Mechanics 2009 Camille Dreyfus Teacher-Scholar Award 2008 Beckman Young Investigator 2007 NSF CAREER Award 2005 'Rising Star' - Chronicle of Higher Education As principal investigator of the Squires Group, Professor Squires leads a dynamic research team that combines experimental, theoretical, and computational approaches to investigate transport phenomena at interfaces. His work has been supported by major funding agencies including the National Science Foundation, with his CAREER award indicating early recognition of his potential as both researcher and educator. While specific grant details aren't provided in the source material, his extensive publication record and prestigious awards suggest robust and sustained research funding. The Squires Group maintains state-of-the-art laboratory facilities for studying micro-scale fluid mechanics, including specialized equipment for microrheology measurements, microfluidic device fabrication, and interfacial characterization. Their research environment fosters collaboration across disciplines, with connections to materials science, physics, and biomedical engineering researchers at UCSB and beyond.
Majid Ghayoomi is a Professor and Civil Engineering Undergraduate Coordinator in the Department of Civil and Environmental Engineering at the University of New Hampshire's College of Engineering and Physical Sciences. His research focuses on geotechnical engineering and geomechanics, particularly unsaturated soil mechanics and geotechnical earthquake engineering. He teaches courses such as Soil Mechanics, Engineering Behavior of Soils, and Geotechnical Modeling. Dr. Ghayoomi holds a Ph.D. from the University of Colorado at Boulder, an M.S. from Sharif University, and a B.S. from the University of Tehran. His research interests include bioremediation, hazards mitigation, soil-structure interaction, and materials testing. He leads the Geotechnical Modeling and Innovation lab, advancing bio-inspired solutions and remote sensing applications in geotechnical systems. His recent work emphasizes climate change impacts on seismic resilience, microbial stabilization of soils, and satellite-based soil moisture monitoring. Key contributions include studies on liquefaction mitigation, seismic site response, and infrastructure vulnerability in dynamic environments. His research spans theoretical, experimental (centrifuge modeling), and computational approaches to address complex geotechnical challenges.
Dr. Anwar Haque is an Associate Professor in the Department of Computer Science at Western University, Canada, and a Faculty of Science Distinguished Research Professor. He holds a Ph.D. in Electrical and Computer Engineering and an M.Sc. in Computer Science from the University of Waterloo. Prior to academia, he was Associate Director at Bell Canada. His research focuses on 5G networks, IoT, cybersecurity, AI, and autonomous systems, with over 100 peer-reviewed publications and $15M in collaborative grants. Dr. Haque leads the Western Information & Networking Group (WING) Lab and is the founder/CEO of Bamboo Innovations Inc., a tech startup developing socially responsible smart technologies. Leadership roles include industry expert-in-residence in the Faculty of Science, Undergraduate Chair of the Computer Science Department, and member of Western’s Senate. He has delivered over 30 keynote talks and media features include BBC Earth and The Globe and Mail. Awards include the IEEE CCECE Leadership Award and multiple grants from NSERC, MITACS, and Bell Canada. His work spans network reliability, smart grids, and cybersecurity, with industry partnerships like the Bell-Western 5G Research Centre.
Dr. Gloria Milena Monsalve Bravo is an Advanced Queensland Industry Research Fellow and lecturer at The University of Queensland's School of Chemical Engineering, where she develops novel multiscale simulation techniques combining molecular simulations with macroscopic physics-based modeling to solve complex energy and environmental problems. Her interdisciplinary work bridges applied mathematics and engineering to improve understanding of phenomena in complex systems across chemical, biomedical, and ecological applications. Her research focuses on: Multiscale simulation techniques for complex systems Molecular simulations coupled with macroscopic modeling Gas permeation and separation in mixed-matrix membranes Uncertainty and sensitivity analysis in mathematical models Applied mathematics for engineering problems Dr. Monsalve Bravo's publication record demonstrates a strong trajectory in membrane technology and computational modeling. Her recent work has advanced understanding of gas transport in novel membrane materials, particularly mixed-matrix membranes, with applications in carbon capture and hydrogen storage. She has made significant contributions to theoretical frameworks for modeling permeation in finite-sized composite systems and developed Bayesian approaches for analyzing parameter uncertainty in sorption predictions. Her research bridges fundamental science with practical applications in energy and environmental engineering. Her scientific contributions have been recognized through research funding including: ARC Research Hub for Value-Added Processing of Underutilised Carbon Wastes (2024-2029) Tailor-made composite membranes for greenhouse gas capture (2023-2026) through Advance Queensland Industry Research Fellowships Dr. Monsalve Bravo actively mentors PhD students on cutting-edge projects related to membrane technology, catalyst development, and waste conversion. She collaborates extensively across disciplines, as evidenced by her diverse publication record spanning chemical engineering, materials science, and environmental applications.
Yannis Paschalidis is a Distinguished Professor at Boston University with appointments in Electrical and Computer Engineering, Systems Engineering, Biomedical Engineering, and Computing & Data Sciences. He serves as Director of the Rafik B. Hariri Institute for Computing and Computational Science & Engineering. He holds a PhD (1996) and MS (1993) in Electrical Engineering and Computer Science from MIT, and a Diploma (1991) from the National Technical University of Athens. His interdisciplinary research spans optimization, control systems, machine learning, and data science with applications in healthcare, autonomous systems, and networks. Key focus areas include developing algorithms for autonomous navigation, healthcare analytics for clinical decision support, energy demand optimization, and computational biology for protein interaction modeling. Recent publications demonstrate strong focus on AI robustness (adversarial defenses, distributional robustness), healthcare applications (cognitive impairment detection, epidemic control), and sustainable systems (power networks, ecological forecasting). Methodological innovations center on reinforcement learning, distributionally robust optimization, and geometric analysis of classical algorithms. CAREER Award (NSF) IEEE Fellow (2014) IFAC Fellow (2022) IBM/IEEE Smarter Planet Award IEEE Computer Society Crowd Sourcing Prize IMIA Best Paper Award Charles DeLisi Award (2020) Distinguished Professor of Engineering As primary advisor to 35 PhD graduates, he leads the Network Optimization & Control (NOC) Lab. His research is funded by NSF, NIH, DoD, ARPA-E, and industry partners, including major grants on Neuro-Autonomy (ONR MURI), pandemic preparedness (ARPA-E NewRAMP), and healthcare AI (NIH QuBBD). He directs the Network Optimization & Control Lab focusing on optimization, learning, and control for autonomous systems, healthcare, and networks. The lab develops fundamental methodologies with applications in robotics, computational medicine, and infrastructure systems.
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.
Vijay Raghunathan is a Professor in the Department of Electrical and Computer Engineering at Purdue University's College of Engineering. His work focuses on hardware and software architectures for embedded systems, wireless sensors for IoT, and wearable/implantable electronics with emphasis on low power design, energy harvesting, emerging memory technologies, and secure system design. Academic Rank: Professor Department: Electrical and Computer Engineering University: Purdue University Research Focus: Energy-efficient embedded systems, IoT, wearable devices His research explores low power design at both board-level and system-on-chip scales, micro-scale energy harvesting , and reliable/secure system design for medical devices. Recent work focuses on Processing-in-Sensor/Memory for battery-free AIoT devices, state space models for neural processing units, and security coprocessor integration in autonomous systems. Analysis of his publications reveals trends in energy-efficient neural network acceleration , approximate computing for edge inference , and compute-in-memory architectures . Key subfields include collaborative edge-cloud partitioning , sparse DNN accelerators , and security frameworks for medical devices. Vijay's work also addresses energy-accuracy tradeoffs in multimodal cognitive systems and intermittent computing using non-volatile memory technologies. His contributions span from microcontroller energy management to security protocols for implantable electronics.
Dr. Tommaso Marcato is a Lecturer at the Department of Chemistry and Applied Biosciences, ETH Zürich. He earned his MSc in Chemical and Bioengineering from ETH Zürich after completing his BSc in Chemical Engineering at Politecnico di Milano, Italy. His research focuses on perovskite light-emitting diodes (PeLEDs), emission anisotropy, and light-outcoupling efficiency, with a particular emphasis on transition dipole moment orientation and nanocrystal self-assembly. His publications span topics such as Stabilization of CsPbI₃ nanoplatelets via metal iodide doping Molecular orientation engineering in OLEDs Ultraflexible self-powered optoelectronics Electroluminescent metasurfaces using perovskite nanocrystals His work aims to overcome photon trapping in devices by manipulating emitter orientation and exploring quantum confinement effects. Dr. Marcato's recent articles (2019–2025) demonstrate expertise in Hybrid perovskite systems Quantum dot applications Photonic device architecture Surface passivation techniques . He is part of the Shih group at ETH Zurich and has received funding from ETH-33 18-2 for his research on graphene-templated molecular alignment in LEDs.
Chris G. Van de Walle is the Herbert Kroemer Distinguished Professor in the Department of Materials at the University of California, Santa Barbara's College of Engineering. As a member of the National Academy of Engineering and fellow of multiple prestigious scientific societies including the American Physical Society and Materials Research Society, he leads the Computational Materials Group which is part of UCSB's strong computational science cluster within the Materials Department. His research interests focus on novel electronic materials, particularly wide-band-gap semiconductors (III-V nitrides, II-VI compounds), transparent conductors, complex oxides, loss mechanisms in light emitters, two-dimensional conductors, quantum information science, and the physics and chemistry of hydrogen interactions with solids. His group uses first-principles computational techniques to study atomic and electronic structure of crystalline, polycrystalline and amorphous materials, interfaces, surfaces, defects, and heterojunctions. Analysis of his recent publications reveals a strong focus on semiconductor materials for quantum technologies, with particular emphasis on GaN, Ga 2 O 3 , and related compounds. His work combines computational materials science with applications in optoelectronics, quantum information, and energy technologies, demonstrating consistent innovation in understanding defects and their role in material properties. Major Awards and Recognitions: Aneesur Rahman Prize for Computational Physics (APS) Materials Theory Award (MRS) Vannevar Bush Faculty Fellowship (DoD) John Bardeen Award (TMS) Medard W. Welch Award (AVS) Highly Cited Researcher (Clarivate Analytics) Professor Van de Walle has mentored numerous successful researchers, including Dr. Fangzhou Zhao (Corbett Prize winner) and Dr. Mark Turiansky (APS Nicholas Metropolis Award recipient). His group maintains strong connections with the UCSB Quantum Foundry and the Solid State Lighting and Energy Electronics Center, demonstrating collaborative research efforts across multiple disciplines. The group actively investigates defects for quantum information science, loss mechanisms in light emitters, nitride semiconductors, halide perovskites, oxides, and hydrogen interactions with materials.
Prof. Alois Christian Knoll is a full professor at the Technical University of Munich (TUM) in the School of Computation, Information and Technology. His academic career includes roles at Bielefeld University and leadership in major EU initiatives like the Human Brain Project and ECHORD++. He specializes in robotics, AI, and autonomous systems, with a focus on medical robotics, sensor-based systems, and neuromorphic engineering. Knoll has supervised over 100 doctoral theses and authored/co-authored over 1,000 publications. Education: Diploma in Electrical Engineering (University of Stuttgart, 1985); PhD in Computer Science (Technical University of Berlin, 1988); Habilitation (TU Berlin, 1993). He has been at TUM since 2001, leading the Robotics, AI, and Real-Time Systems department. Research interests span autonomous systems, neuro-IT integration, and traffic simulation. Key projects include fortiss (Bavarian State Institute for Computer Science) and TUM-CREATE (Singapore collaboration). Awards include IEEE Fellow, University of Tokyo Fellow, and the Carl-Ramsauer-Prize (1990). Current roles include editorships in robotics journals, leadership in EU flagship projects, and teaching across multiple programs. His work bridges computer science, neuroscience, and engineering, with applications in healthcare, automotive systems, and urban mobility.
Prof. Roger Wattenhofer is a Full Professor at the Department of Information Technology and Electrical Engineering, ETH Zurich, Switzerland, and Deputy head of the Computer Engineering and Networks Lab. He holds a doctorate in Computer Science from ETH Zurich (1998) and has held positions at Brown University and Microsoft Research before returning to ETH. His research focuses on distributed computing, wireless networks, and algorithmic systems design, with contributions to Byzantine agreement protocols, blockchain technologies, and neural network architectures. He teaches courses such as Distributed Systems and Computational Thinking. Education: Ph.D. in Computer Science (ETH Zurich, 1998). Research interests include distributed systems, network algorithms, and the intersection of machine learning with distributed computing. His work spans both theoretical foundations and practical implementations, addressing challenges in fault tolerance, consensus mechanisms, and algorithmic efficiency. Recent publications explore topics like adversarial robustness in voting systems, privacy in reinforcement learning, and generative music models. He actively contributes to open-source frameworks and benchmarks for neural algorithmic reasoning.
