Professor Petri Kuosmanen is affiliated with Aalto University as a faculty member of the School of Engineering and holds a position in the Department of Energy and Mechanical Engineering and the Mechatronics unit. Doctoral Degree in Engineering and Technology, Helsinki University of Technology (2004) Licentiate Degree in Engineering and Technology, Helsinki University of Technology (1992) Master's Degree in Engineering and Technology, Helsinki University of Technology (1988) His research focuses on Industrial Internet and Rotor Dynamics , with significant contributions to elevator systems , hydraulics , and wastewater treatment plant design . Recent work includes optimizing natural frequencies in rotor systems and developing digital twins for engineering education . Key trends in his 2024 publications include: Rotor dynamics and vibration analysis Smart data validation in industrial IoT networks Cold-climate adaptations for wastewater treatment Automated fiber optics coating mechanisms Energy efficiency in aeration systems As Principal Investigator, he leads projects like DRIVE FORWARD (2024–2027) and GOOD (2021–2024), focusing on electrified mobile machinery. He actively collaborates with networks such as DAAAM International (Chair) and European CLUSTER-university network (Member).
John A. Rogers is the Louis Simpson and Kimberly Querrey Professor at Northwestern University, holding joint appointments in Materials Science and Engineering, Biomedical Engineering, Mechanical Engineering, Chemistry, and Neurological Surgery. He directs the Querrey-Simpson Institute for Bioelectronics. His work bridges soft materials science, bio-integrated electronics, and nanotechnology, with a focus on wearable medical devices, bioresorbable systems, and neural interfaces. Educations: B.A. & B.S. from University of Texas Austin (1989), S.M. from MIT (1992), Ph.D. in Physical Chemistry from MIT (1995). Prior roles include Director of Bell Labs' Condensed Matter Physics Department and faculty positions at University of Illinois at Urbana-Champaign. Research emphasizes soft materials for bio-inspired electronics, including flexible sensors, microfluidic platforms, and bioresorbable implants. His lab has pioneered epidermal electronics, injectable optoelectronics, and neural interfacing systems. Over 1000 peer-reviewed publications and 100+ patents highlight his contributions to nanotechnology and biomedical engineering. Awards include the Benjamin Franklin Medal (2019), MRS Medal (2018), and MacArthur Fellowship (2009). He is a member of the National Academies of Sciences, Engineering, and Medicine. Current projects span bioelectronic medicines, wearable health monitors, and advanced medical imaging tools.
Xiuwei Zhang is the J.Z. Liang Early-Career Assistant Professor in the School of Computational Science and Engineering (SCoSE) at Georgia Institute of Technology, part of the College of Computing. Her research focuses on computational biology and bioinformatics, particularly in developing machine learning methods for analyzing single-cell omics data, including multi-modal, temporal, and spatial data integration. She leads a lab that designs tools like scDART , scMoMaT , and scMultiSim , which address challenges in multi-omics integration, lineage reconstruction, and simulation. Before joining Georgia Tech, she held postdoctoral positions at UC Berkeley (Nir Yosef’s group), the European Bioinformatics Institute (EBI), and École Polytechnique Fédérale de Lausanne (EPFL). She earned her PhD in computer science from EPFL under Bernard Moret. Her Erdős number is 3, reflecting her collaborative work across computational fields. Her research spans four key areas: multi-batch/single-cell data integration, temporal analysis of cell differentiation, spatial-temporal omics dynamics, and simulation tools for benchmarking methods. She has received prestigious awards, including the NSF CAREER Award (2022) and NIH MIRA (2021). She actively participates in conferences (RECOMB, ISMB) and serves on editorial boards (Journal of Computational Biology). Her group’s recent work includes the scMultiSim simulator (2025), which generates multi-omics spatial data, and LinRace (2023), reconstructing cell lineage histories. She mentors over 15 students and collaborates internationally on projects like the InQuBATE Workshop on Single-Cell Transcriptomics.
JIANG Xingyu is Chair Professor and Head of the Department of Biomedical Engineering at the Southern University of Science and Technology (SUSTech) . Since 2018 he has led a multidisciplinary team developing advanced micro- and nano-scale tools for analytical chemistry, microfluidics and nanomedicine. Education Postdoctoral Research, Harvard University (2004–2005) Ph.D. in Chemistry, Harvard University (2004) B.S. in Chemistry, University of Chicago (1999) Research Interests Professor Jiang’s research integrates analytical chemistry , microfluidics , biomedical engineering and nanomedicine . His laboratory designs microfluidic chips for point-of-care diagnostics, engineers gold nanoclusters and nanoparticles for antimicrobial and anticancer therapy, and develops soft flexible bio-electronics for neural interfaces and wearable health monitoring. Across 400+ publications, recent work demonstrates a clear trend toward translational nanomedicine : point-of-care viral variant detection, nanoantibiotic strategies against multidrug-resistant bacteria, CRISPR delivery systems for cancer therapy, and conformal electronic tattoos for human-machine interfaces. Scientific Awards & Honours Fellow, American Institute for Medical and Biological Engineering (2020) Fellow, Royal Society of Chemistry (2016) Tencent Science Exploration Award (2019) Chief Scientist, National Key R&D Program (2019–) National Science Fund for Distinguished Young Scholars (2010) Young Investigator Award, Human Frontier Science Program (2007) Research Funding & Teams He currently directs the Nanoscience Laboratory at SUSTech, hosts National Key R&D Program projects as Chief Scientist, and serves on editorial boards of Advanced Healthcare Materials , Lab on a Chip , Nanoscale Horizons , Nanoscale and Nanoscale Advances . The group is actively recruiting post-docs, research professors and technicians across chemistry, materials, biology and medical engineering disciplines.
Metin Sitti is a Professor and currently serves as a part-time adjunct professor at Koç University's Faculty of Medicine and Engineering. He is also the President of Koç University and Director of the Max Planck Institute for Intelligent Systems since 2014. His research spans robotics , micro/nanorobotics , physical intelligence , bio-inspired robotics , and materials science . Undergraduate: Boğaziçi University (Electrical and Electronics Engineering, 1992) Master's: Boğaziçi University (1994) PhD: University of Tokyo (Electrical Engineering, 1999) His research focuses on small-scale robotics for biomedical applications, including magnetic microrobot swarms , biohybrid systems , and functional materials . Recent publications emphasize 3D control , wireless actuation , and clinical translation of robotic systems. Scientific Awards : 2020 Scientific Breakthrough of the Year 2018 Koç University Rahmi M. Koç Science Medal 2014 IEEE/ASME Best Mechatronics Paper Award 2013/2012 World RoboCup Micro-Robotics First Prize He has advised numerous students and collaborates with institutions like Carnegie Mellon University and University of Stuttgart. His work integrates physical intelligence into miniature robots for medical imaging , drug delivery , and autonomous systems .
Sungkwon Park is a Professor in the Department of Food Science and Biotechnology at Sejong University, specializing in advanced food science and biotechnology research with a focus on meat science, cultured meat production, and sustainable food systems. His research integrates molecular biology, food biotechnology, and systems biology to develop innovative food solutions. His educational background includes a Ph.D. from Purdue University (2008), M.S. from Yeungnam University (2001), and B.S. from Yeungnam University (1999). Prior to his current position, he worked as a Postdoctoral Fellow at Virginia Tech (2008-2012) and as a Research Officer at the National Institute of Animal Science, RDA (2012-2015). Professor Park's research interests focus on livestock production optimization, meat processing for health functionality, environmentally friendly animal production systems, and in vitro meat production. His work has led to significant achievements including the identification of calcium and glucose interaction mechanisms in muscle metabolism, development of oleogel-based meat processing techniques, optimization of feed ingredients for sustainable livestock, and establishment of in vitro meat production systems. His recent publications (2023-2025) demonstrate a strong focus on cultured meat technology, meat science, and sustainable food production. The research spans cellular mechanisms for cultured meat production, safety and regulatory aspects of alternative proteins, comparative analysis of muscle satellite cells, and optimization of meat processing techniques. His work shows a clear trend toward developing practical applications for next-generation meat products with emphasis on health functionality and environmental sustainability. Professor Park actively serves as a reviewer for Frontiers in Veterinary Science and is an Editorial Board Member of the Korean Society of Animal Science. His laboratory, the M&M'a lab (Functional Food Lab), conducts research on high-value-added, health-functional BioFood and future foods using bio-convergence technologies.
Mehdi Abdollahi is an Associate Professor at Chalmers University of Technology's Department of Food and Nutrition Science. His research focuses on alternative proteins, food biotechnology, and plant-based hybrid foods, with emphasis on sustainable utilization of food side streams, legumes, cereals, and microalgae as future protein sources. Develops pH-shift technology and ultrasound-assisted methods for protein extraction Specializes in hybrid food engineering via fermentation and biorefinery Works on 3D food printing and high-moisture extrusion for food analogs Researches collagen and biobased food packaging materials His work includes >100 peer-reviewed publications, 4 book chapters, and 3 patents. Current projects involve collaborations with Arla Foods, Lantmännen, and Nordic Seafarm, addressing sustainable seafood systems and plant-protein hybridization. 2024 Bertebos Prize recipient 2025: Recognized among Sweden's Top 101 Sustainability Figures Mentors 7 PhD students and 3 postdocs while collaborating with European institutions like Kristianstad University and Ankara University. His group explores biorefinery strategies, hybrid food functionality, and innovative packaging solutions.
Tobi Delbruck is a titular professor of physics and electrical engineering at ETH Zurich, where he leads the Sensors Group at the Institute for Neuroinformatics (INI) in Zurich, Switzerland. He collaborates closely with Shih-Chii Liu and Giacomo Indiveri as part of the 'hardware groups' at INI. Delbruck has also served as visiting faculty at Caltech and is a Fellow of the IEEE. His work focuses on bio-inspired and neuromorphic event-based sensory processing systems. Professor Delbruck's research spans multiple areas of neuromorphic engineering, with particular emphasis on event-based vision systems and low-power analog VLSI circuits. His work has significantly advanced the field of Dynamic Vision Sensors (DVS), which mimic the human retina's response to changes in brightness rather than capturing full frames. This approach enables extremely low-latency vision processing with minimal power consumption, making it ideal for high-speed applications and robotics. His research has applications in robotics, autonomous systems, and low-power embedded vision. Delbruck is an active contributor to the neuromorphic engineering community, co-organizing the annual Telluride Workshop on Neuromorphic Engineering and serving in leadership roles with IEEE. He has authored numerous influential publications and co-authored books including "Event-Based Neuromorphic Systems" and "Analog VLSI: Circuits and Principles." His jAER (Java Address-Event Representation) project provides open-source tools for real-time event-based sensory processing. Analysis of his recent publications shows a clear trend toward integrating event-based vision with deep learning techniques and applying these systems to practical robotics problems. His scientific achievements have been recognized with multiple awards including: IEEE Fellow Winner of Best Live Demonstration award at ISCAS 2012 Honorable Mention Award from Sensory Systems Technical Committee at ISCAS 2012 Overall Best Student Paper Award and Best Paper Award from Sensory Systems Technical Committee at ISCAS 2010 Winner of the 2006 ISSCC Jan Van Vessem Outstanding European Paper Award Professor Delbruck actively mentors students and has supervised numerous PhD and Master's theses in the areas of neuromorphic engineering and event-based vision systems. His group has secured significant research funding from various sources to support their innovative work in bio-inspired sensory processing. He teaches courses on "Electronics for Physicists II (Digital)" and "Neuromorphic Engineering," helping to train the next generation of researchers in this field. The Sensors Group at INI, which Delbruck leads, operates state-of-the-art facilities for designing and testing neuromorphic vision systems. The group maintains close collaborations with researchers worldwide and has developed several important open-source resources including the jAER project and bias generator design kits. Their work continues to push the boundaries of what's possible with event-based sensory processing, with applications ranging from high-speed robotics to low-power embedded vision systems.
Jiajun Wu is an Assistant Professor of Computer Science and, by courtesy, of Psychology at Stanford University. He holds multiple affiliations including membership in Bio-X, Faculty Affiliate status at the Institute for Human-Centered Artificial Intelligence (HAI), and membership in both the Wu Tsai Human Performance Alliance and Wu Tsai Neurosciences Institute. Dr. Wu earned his Ph.D. and S.M. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology before joining Stanford. Dr. Wu's research program focuses on creating AI systems that understand and interact with the physical world through the integration of computer vision, machine learning, robotics, and cognitive science. His work emphasizes physics-based modeling combined with deep learning to develop systems capable of perceiving, reasoning about, and predicting physical interactions. Key research areas include 3D scene understanding, neurosymbolic AI approaches, multimodal perception (combining vision, sound, and language), and embodied intelligence for robotics applications. His lab develops novel frameworks that bridge the gap between neural networks and symbolic reasoning to create more interpretable and robust AI systems. Analysis of Dr. Wu's recent publications reveals a strong trajectory toward integrated multimodal understanding for embodied AI. His work increasingly combines vision, sound, and language processing with physical reasoning to create systems that can interact meaningfully with the physical world. There's a clear progression from foundational computer vision research toward practical robotics applications, with significant emphasis on foundation models for robotics, sim2real transfer techniques, and creating comprehensive datasets for embodied AI research. Dr. Wu's exceptional contributions have been recognized with numerous prestigious awards including the NSF CAREER award (2024), Young Investigator Programs from ONR (2024) and AFOSR (2023), the Okawa research grant (2024), and being named to IEEE Intelligent Systems' 'AI's 10 to Watch' (2024). He has received multiple best paper awards at leading conferences including ICRA (2024), SIGGRAPH Asia (2023), and CoRL (2023). Dr. Wu actively mentors a large cohort of students across multiple levels, serving as primary advisor for doctoral candidates, master's students, and numerous independent researchers. His research is supported by substantial funding from major technology companies including Google, Meta, Amazon, Samsung, and J.P. Morgan, as well as government agencies like NSF, ONR, and AFOSR, reflecting the significance and impact of his work in physical AI and multimodal perception systems. Dr. Wu leads a dynamic research group at Stanford that collaborates extensively with the Wu Tsai Neurosciences Institute and Institute for Human-Centered AI. Current projects include developing neurosymbolic models for computer graphics, creating multisensory datasets like OBJECTFOLDER 2.0 for sim2real transfer in robotics, and building foundation models for embodied intelligence that can understand and manipulate objects with human-like physical intuition.
Dr. Yi Shen is a Senior Lecturer at the School of Chemical and Biomolecular Engineering, The University of Sydney, and Chair of RACI Women in Chemistry. She is also affiliated with multiple research institutes including Sydney Institute of Agriculture, Sydney Southeast Asia Centre, The Centre for Drug Discovery Innovation, and The University of Sydney Nano Institute. PhD in Soft Materials from ETH Zurich Postdoctoral research at University of Cambridge and Harvard University Her research focuses on protein phase behavior and functional biomaterials development, utilizing soft matter approaches and microfluidic techniques to address challenges in neurodegenerative diseases, sustainable materials, and biomedical engineering. She has published extensively in top journals like Nature Nanotechnology and PNAS, with a particular emphasis on: Protein liquid-liquid phase separation mechanisms Biomaterials from protein nanofibrils Microfluidic manipulation of biological systems Biodegradable bioplastics development Shear force effects on biomolecular systems Pathological protein aggregation dynamics Key scientific achievements include: 2022 ARC DECRA Fellowship 2022 Sydney Nano Frontier award 2018 ETH Zurich Spark Award (for Fe delivery system invention) 2012 Princeton Grand Challenges Program 2 patents pending 2 Nature Nanotechnology cover articles As an educator, she coordinates CHNG2802 Chemical Engineering Modelling and Analysis, co-teaches CHNG3804 Biochemical Engineering and CHNG5605 Bio-products: Laboratory to Marketplace, and guest lectures across biomedical and nanotechnology programs. Her lab actively collaborates with institutions in Switzerland (ETH Zurich), UK (Cambridge), and US (Harvard, Princeton), focusing on transforming biomolecular understanding into real-world applications in health, industry, and environmental sustainability.
Dr. Kevin Kochersberger is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech , with a career spanning academic research, technical innovation, and educational leadership. His work focuses on autonomous aerial systems , robotic control , and applied aerodynamics , particularly through the Uncrewed Systems Laboratory . Kochersberger's research has pioneered UAV-based radiation detection , 3D terrain mapping , and low-resource drone applications , including establishing the African Drone and Data Academy in Malawi . Education: Ph.D., Mechanical Engineering, Virginia Tech (1994) M.S., Mechanical Engineering, Virginia Tech (1984) B.S., Mechanical Engineering, Virginia Tech (1983) A.S., Engineering Science, Jamestown Community College (1981) Kochersberger's publications demonstrate expertise in UAV path planning , smart material actuation , and radiation source localization , with over $9M in research funding. His scientific awards include AIAA Associate Fellow (2009) and Aviation Week Aerospace Laureate (2003). Notable projects involve helicopter-deployable robotic systems and urban canyon navigation without GPS. Recent articles highlight BVLOS drone simulators , 2.5D terrain mapping , and autonomous negative obstacle traversal , reflecting his focus on real-time adaptive control and heterogeneous robotic systems . He teaches Drone Technology and Flight Operations and Advanced Design Projects , emphasizing student-driven innovation and industry collaboration .
Surya Ganguli is an Associate Professor in the Department of Applied Physics at Stanford University, with courtesy appointments in Neurobiology and Electrical Engineering. He serves as Senior Fellow at the Stanford Institute for Human-Centered AI and is affiliated with the Stanford Neuroscience Institute , Bio-X , and Wu Tsai Neurosciences Institute . His research spans theoretical neuroscience, machine learning, and statistical mechanics. Ph.D. , UC Berkeley, Theoretical Physics (2004) M.A. , UC Berkeley, Physics (2000) M.A. , UC Berkeley, Mathematics (2004) M.Eng. , MIT, Electrical Engineering and Computer Science (1998) B.S. , MIT, Physics (1998) B.S. , MIT, Mathematics (1998) B.S. , MIT, Electrical Engineering and Computer Science (1998) His lab explores how higher-level cognitive phenomena emerge from neural network dynamics, focusing on perception, memory, attention, and decision-making . Research themes include statistical mechanics of learning , neural representational geometry , and biologically plausible learning rules . Current work examines nonlinear interactions in neural networks through the Schmidt Science Polymath Award (2023). Key article trends reveal expertise in neural coding limits (2022 Nature), synaptic plasticity models (2022 Neural Computation), and deep learning theory (2022 NeurIPS publications). His 2019 Annual Review chapter on statistical mechanics of deep learning established foundational insights into network criticality. Scientific Awards : NSF Career Award (2019) Simons Foundation Investigator (2016) McKnight Scholar Award (2015) James S. McDonnell Foundation Scholar (2014) Sloan Research Fellow (2013) As advisor, he mentors 10+ doctoral students across Applied Physics, Neurosciences, and Computer Science, including Vamshi Balanaga and Mason Kamb. His lab collaborates with experimental teams at Stanford and beyond, supported by grants from NSF , Simons Foundation , and Swartz Foundation . The Neural Dynamics & Computation Lab unites physicists, mathematicians, and neuroscientists to decode cognition through interdisciplinary methods.
Andres F. Arrieta is an Associate Professor of Mechanical Engineering at Purdue University's School of Mechanical Engineering in West Lafayette, Indiana. He leads the Programmable Structures Lab and holds affiliations with multiple research areas including dynamics, advanced materials, and robotics. His research focuses on adaptive structures, mechanical metamaterials, and programmable systems. Education: Mechanical Engineer, Universidad de los Andes, Bogotá, 2006 Ph.D., University of Bristol, United Kingdom, 2010 Postdoctoral Research Fellow, ETH Zurich, 2012 Research Interests: His work emphasizes multistable structures, structural nonlinearity, and elastic instabilities. He explores applications in energy harvesting, morphing wings, and mechanical metamaterials. Recent trends include bio-inspired designs and smart materials for adaptive systems. Awards: 2019 ASME Best Paper Award (Bioinspired Materials) 2018 Gary Anderson Early Achievement Award 2017 Journal Cover Feature (Chiral Metastructure) 2012 ETH Postdoctoral Fellowship Labs/Teams: Leads the Programmable Structures Lab, focusing on innovative metastructures and adaptive robotics systems.
Tosiron Adegbija is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Arizona, where he serves as Director of Graduate Studies and Thomas R. Brown Endowed Fellow. He is a member of the Graduate Faculty and actively contributes to research and teaching in computer architecture and embedded systems. Education: PhD in Electrical and Computer Engineering, University of Florida, 2015 MS in Electrical and Computer Engineering, University of Florida, 2011 BS in Electrical Engineering, University of Ilorin, Nigeria, 2005 His research centers on energy-efficient computing with a focus on bio-inspired computer architecture , including spiking neural network (SNN) accelerators and in-memory computing. He also explores domain-specific architectures , adaptable memory systems , and microprocessor optimizations for IoT . His work leverages novel memory technologies like STT-RAM to enhance performance and reduce energy consumption in embedded and resource-constrained systems. Recent publications highlight trends in hybrid SNN acceleration, domain-specific accelerator generation, and system-level design space exploration. His research is increasingly focused on neuromorphic computing, automated hardware design, and ultra-efficient architectures using emerging materials like antiferromagnetic tunnel junctions. Scientific Awards: National Science Foundation (NSF) CAREER Award (2019) Elected IEEE Senior Member (2020) Best Paper Award at IEEE ISVLSI (2014) Teaching Award, University of Arizona (2018) ACM GLSVLSI Travel Award (2015) He advises numerous graduate and undergraduate students, many of whom have pursued careers at institutions like Pacific Northwest National Labs, Micron Technology, and Amazon. He has secured significant funding, including a $1.9M NSF FuSE2 grant for energy-efficient computing. His lab collaborates with UA Physics, CMU, and UNL. He has also developed educational tools for Chipyard and RISC-V, supporting hands-on learning in computer architecture. Labs and Research Teams: Leads a research group focused on bio-inspired and domain-specific computing, fostering innovation in energy-efficient hardware. The lab emphasizes hardware/software co-design, neuromorphic engineering, and real-world deployment in IoT and biomedical applications.
Achim Menges is a Research Professor and Max Planck Fellow at the University of Stuttgart, where he directs the Institute for Computational Design and Construction (ICD). His work bridges architecture, engineering, and computational design, with a focus on developing innovative construction methods and materials. Menges leads the Cluster of Excellence IntCDC: Integrative Computational Design and Construction for Architecture, a major research initiative funded by the German Research Foundation. Menges' research centers on computational design, robotic construction, and biomimetic architecture, with particular emphasis on timber construction, adaptive building systems, and digital fabrication. His work integrates principles from bionics to create responsive, sustainable building systems that adapt to environmental conditions. Notable projects include the BUGA Wood Pavilion (2019), Urbach Tower, BUGA Fibre Pavilion, and the livMatS Biomimetic Shell, all demonstrating his commitment to material innovation and sustainable construction practices. His recent publications reveal a consistent focus on advancing timber construction techniques, developing bio-inspired responsive systems, and implementing robotic fabrication processes. The research shows a clear trajectory toward more sustainable, resource-efficient building methods that integrate digital design with physical construction processes. Menges' work increasingly addresses multi-story timber systems and circular construction principles. Bauwende Prize der Universität Stuttgart 2025 Menges leads numerous research initiatives through the Cluster of Excellence IntCDC, securing significant funding for projects exploring computational design and robotic construction. His work involves extensive collaboration with industry partners and interdisciplinary research teams. Menges directs the ICD research laboratory, which focuses on developing novel computational design methods, robotic fabrication processes, and innovative material systems for architecture. The institute maintains strong partnerships with industry leaders in construction technology and materials science, facilitating the translation of research into practical applications.
