Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.
Huy T Tran is an Assistant Professor in the Department of Aerospace Engineering at the University of Illinois at Urbana-Champaign's College of Engineering, with additional appointments at the Applied Research Institute. His research focuses on the intersection of robotics, artificial intelligence, and multi-agent systems, with applications spanning autonomous navigation, critical infrastructure resilience, and intelligent transportation. Dr. Tran earned his Ph.D. in Aerospace Engineering from Georgia Institute of Technology in 2015, following advanced degrees from Georgia Tech and University of Wisconsin-Madison. His academic journey includes research assistant professor positions before achieving his current assistant professor role in 2021. He previously worked as a Senior Multi-Disciplinary Systems Engineer at The MITRE Corporation and served as a Visiting Scholar at the Air Force Institute of Technology. His research interests encompass Autonomy, Reinforcement Learning, Artificial Intelligence, Machine Learning, Robotics, Multiagent Systems, Intelligent Transportation Systems, and Critical Infrastructure Resilience. As director of the Lab for Intelligent Robots and Agents (LIRA), he leads cutting-edge research in autonomous systems that interact with humans and other robots. His work has evolved from foundational resilience modeling in aerospace systems toward increasingly sophisticated AI applications in multi-robot coordination and explainable decision-making. Dr. Tran's publication record demonstrates a clear trajectory toward explainable AI and human-AI collaboration, with recent work focusing on generating explanations for reinforcement learning policies, coordination in ad hoc teams, and neuro-symbolic approaches to robot policy interpretation. His research bridges theoretical advances with practical applications in air traffic control, field robotics, and critical infrastructure management. Best Paper Award: Theoretical (2016 Complex Adaptive Systems Conference) Selected for oral presentation at IROS 2023 Workshop 27% full paper acceptance rate at AAMAS 2022 44% acceptance rate at ICRA 2020 As an educator, Dr. Tran teaches core aerospace courses including Computational Systems Engineering, Aerospace Numerical Methods, and Reinforcement Learning. He has secured significant research funding from NASA's Transformational Tools and Technologies program, ARL A2I2 program, ONR Science of AI program, and DARPA. His current projects span ad hoc teaming in multi-robot systems, collective autonomous air mobility, hierarchical reinforcement learning, and interpretable AI agents.
Ziming Zhang is an Assistant Professor in the Department of Electrical and Computer Engineering at Worcester Polytechnic Institute (WPI) , with additional affiliations in Data Science and Robotics Engineering. He previously held research roles at Mitsubishi Electric Research Laboratories (MERL) and Boston University. PhD in Computing (2013) from Oxford Brookes University , UK MS in Computing Science (2010) from Simon Fraser University , CA BS in Computer Science and Technology (2005) from Northeastern University , China Research interests span computer vision , machine learning , and their applications in point cloud processing , medical imaging , autonomous driving , and IoT . He leads the Vision, Intelligence, and System Laboratory (VISLab) at WPI. Recent publications focus on 3D reconstruction , hyperbolic learning , and robust classifiers . Awards include the R&D100 Award 2018 and NSF funding for data-efficient deep learning. PhD Students: Yecheng Lyu (co-supervised), Guojun Wu (co-supervised), Hangrui Zhang, Xuechu Yu Master's Students: Yun Yue, Yuping Shao Visiting Scholars: Fangzhou Lin His lab partners with industry and academic institutions, focusing on autonomous systems , robotics , and scientific imaging projects.
Mohammad Pirani is an Assistant Professor in the Department of Mechanical Engineering at the University of Ottawa, with a joint appointment at the School of Electrical Engineering and Computer Science. Previously, he held postdoctoral and research assistant professor roles at the University of Waterloo, University of Toronto, and KTH Royal Institute of Technology. Education: Ph.D., Mechanical and Mechatronics Engineering, University of Waterloo (2017) MASc., Electrical and Computer Engineering, University of Waterloo (2014) BASc., Mechanical Engineering, Amirkabir University of Technology (2011) His research focuses on resilient and fault-tolerant control in complex systems, including networked control systems and multi-agent systems . He explores intersections with network science , cybersecurity , and machine learning , addressing vulnerabilities in cyber-physical systems like automotive networks. Notable contributions include publications in IEEE Transactions on Control of Network Systems and Automatica , with recent work on network critical slowing down and graph-theoretic resilience strategies. His research trends emphasize reliable learning , security in distributed systems , and data-driven detection of critical transitions . Scientific Awards: Senior Member, IEEE Mohammad Pirani holds a dual appointment at the University of Ottawa and an adjunct professor position at the University of Waterloo. His work bridges mechatronics , robotics and automation , and networked systems , with future directions targeting cybersecurity in cyber-physical systems.
Professor David Abbink is a Full Professor of Haptic Human-Robot Interaction at Delft University of Technology, holding a joint appointment between the Department of Cognitive Robotics in the Faculty of Mechanical Engineering and Industrial Design Engineering since November 2023. He founded the Delft Haptics Lab and co-founded the Cognitive Robotics Department in 2017. Abbink leads the transdisciplinary research and innovation centre FRAIM, which was awarded the prestigious NWO Stevin Premie (Dutch Nobel Prize equivalent) in June 2024. Trained as a mechanical engineer specializing in biomechanics, Abbink's research focuses on human behavior adaptations when interacting with autonomous systems. He has published over a hundred scientific articles on human-robot interaction, haptics, shared control, tele-operation, driver assistance systems, and sensorimotor control. His research has been funded by industry partners (Nissan, Boeing, Renault), RVO (Brightsky project 2022-2026), and the Dutch Science Foundation NWO through personal grants (VENI 2010-2014, VIDI 2015-2019). Abbink's recent work centers on worker-robot relations as an academic focus, collaborating with organizations like Erasmus Medical Centre for nursing work, Schiphol and KLM for baggage handling, and KLM Engine Repair Services for maintenance work. He also serves as scientific director for the Centre for Meaningful Human Control, launched in October 2024. His work bridges engineering, social sciences, and practical applications to responsibly shape the future of work with emerging robotic capabilities. NWO Stevin Premie (2024) Best IEEE SMC journal paper on Cybernetics (2019) Top 25 scientific talents according to New Scientist (2015) Best teacher of Faculty 3mE (2013, 2014) Best teacher of Department of BioMechanical Engineering (seven consecutive years) Abbink has supervised over 110 MSc students and 11 PhD students. His educational contributions include developing the Master Programme in Robotics at TU Delft and receiving international recognition for his course 'The Human Controller.' He is also a prominent science communicator, featured on national television, radio, and major Dutch newspapers, and has delivered lectures at venues like The Royal Institution and Lowlands Festival. Despite his academic commitments, Abbink maintains a drummer persona, having recorded four albums and performed over 400 shows across three continents between 1999-2014.
Emily Cross is a Full Professor at the Department of Humanities, Social and Political Sciences at ETH Zurich, leading the Social Brain Sciences Professorship since spring 2023. She previously held professorships at Bangor University (Wales), University of Glasgow (Scotland), Macquarie University (Australia), and Western Sydney University's MARCS Institute (Australia). Her research centers on how embodied experience shapes social learning and perception across diverse contexts. Key contributions include identifying neural signatures of embodied expertise using dancers, developing embodied neuroaesthetics theory, uncovering neurocognitive foundations of visual learning across lifespans, and pioneering paradigms for human-robot social engagement. Her interdisciplinary approach bridges technology, performing/visual arts, and social sciences to explore experience-dependent plasticity at brain and behavioral levels. Recent publications (2024-2025) demonstrate intense focus on human-robot interaction dynamics, aesthetic movement perception, and context-dependent social cognition. Work increasingly examines self-disclosure mechanisms to robots, cultural influences on robot acceptance, and neural correlates of movement synchrony, reflecting her expanding influence at the neuroscience-robotics intersection. Scientific awards include: Philip Leverhulme Prize for Psychology Jacob Bronowski Award from British Science Foundation Young Talent Award from Dutch Neuroscience Society RoboHub and Insight Analytics top women in robotics listings Australia’s Superstars of STEM (2022) Cross passionately trains next-generation scientists with emphasis on research ethics. Her work attracts major funding from ERC, NIH, Fulbright Commission, ESRC, EPSRC, and UK Ministry of Defence. She serves on UNESCO’s International Bioethics Committee (co-rapporteur for neurotechnology ethics report) and as Associate Editor for International Journal of Social Robotics. She leads ETH Zurich's dynamic Social Brain Sciences group, which embraces interdisciplinarity through research paradigms bridging technology, performing/visual arts, and biological/social sciences, while maintaining active roles in editorial boards and conference committees including Intelligent Virtual Agents and Affective Computing meetings.
Abraham D. Stroock is an Assistant Professor at the School of Chemical and Biomolecular Engineering, Cornell University, since 2003. He holds a B.A. in Physics (Cornell, 1995), M.S. in Solid State Physics (University of Paris, 1997), and Ph.D. in Chemical Engineering (Harvard, 2002). His research bridges microfluidics, biophysics, and sustainable energy. Education: B.A., Physics, Cornell University (1995) M.S., Solid State Physics, University of Paris VI/XI (1997) Ph.D., Chemical Engineering, Harvard University (2002) The Stroock Lab explores micrometer-scale chemical processes inspired by plant biology, focusing on liquid manipulation, negative-pressure water properties, vascular development in tissue engineering, and fluid mechanics in microsystems. Key technologies include microtensiometers and nanoporous membranes . His recent work (2025-2024) spans optical phenotyping using soft robotics, hydromechanical signaling in plants, tissue scaffolds for regenerative medicine, and advanced models for transpiration control. These studies integrate bioengineering, nanotechnology, and environmental science. Scientific Awards: Van Ness Lectureship (2010) Camille Dreyfus Teacher Scholar Award (2009) NSF CAREER Award (2008) MIT Technology Review TR35 (2007) ONR Young Investigator Award (2004) 3M Non-Tenured Faculty Award (2006) Beckman Young Investigator Award (2006) Dreyfus New Faculty Award (2003) He has led projects on superheated loop heat pipes , phosphorescent oxygen sensors , and synthetic tree-on-a-chip systems. His teaching includes advanced biomolecular engineering (ChemE 7770), and he contributes to policy through the Chemistry and Chemical Biology (CBE) Policy Committee.
Karen M Feigh is a Professor and Associate Chair for Research in the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology, holding the prestigious David S. Lewis Professorship. Her interdisciplinary work integrates aerospace engineering with cognitive sciences to address human-machine interaction challenges in complex aviation and autonomy systems. Education B.S. in Aerospace Engineering, Georgia Institute of Technology MPhil in Aeronautics, Cranfield University, UK Ph.D. in Industrial and Systems Engineering, Georgia Institute of Technology Dr. Feigh's research centers on cognitive engineering applications for flight operations and air traffic management. Through ethnographic studies, human-in-the-loop experiments, and expert system design, she develops solutions that align technology with human cognitive processes to enhance safety and efficiency in NextGen air traffic concepts, vertical lift systems, and autonomous vehicle operations. Scientific Awards David S. Lewis Professorship in the School of Aerospace Engineering (2025) AIAA Wilbur and Orville Wright Graduate Award (2006) Zonta International Amelia Earhart Fellowship (2005) National Science Foundation Graduate Research Fellowship (2001-2006) Marshall Scholarship (2001-2003) As director of the Cognitive Engineering Center (CEC), Dr. Feigh mentors graduate researchers and leads interdisciplinary collaborations across Georgia Tech's research ecosystem. The CEC, embedded within the Vertical Lift Research Center of Excellence and Institute for Robotics and Intelligent Machines, secures funding from agencies including NSF and AIAA to advance adaptive intelligence for industrial robotics and air traffic control systems. Laboratories and Collaborations The Cognitive Engineering Center under Dr. Feigh's leadership conducts field work, human-subjects studies, and mathematical modeling to solve human-machine interaction challenges. The lab maintains active partnerships with NASA, FAA, and industry stakeholders to implement research findings in real-world aerospace operations, with current focus on adaptive interfaces for autonomous systems and crew decision support tools.
Olli Seppänen serves as Associate Professor in Civil Engineering at Aalto University's School of Engineering, specializing in operations management for construction productivity improvement. He coordinates the Vision 2030 consortium—comprising 13 Finnish construction and design firms—to develop industrialized building methods for 2030, while leading multiple Business Finland-funded research initiatives focused on digital construction workflows and real-time monitoring. His research centers on lean construction principles, location-based management systems, and digital transformation through IoT, AI, and robotic vision. Key focus areas include prefabrication optimization, construction logistics, and shifting work off-site to industrialize processes. He aims to solve industry-wide productivity challenges by creating real-time situational awareness and implementing takt production systems for workflow stability. Recent publications (2024-2025) reveal strong emphasis on digital twin frameworks, semantic modeling for quality assurance, and AI applications in risk management. His work bridges theoretical lean construction concepts with practical implementations, particularly in real-time resource tracking, waste reduction in MEP work, and cross-sector learning from high-performing teams. Seppänen has received significant recognition including: School of Engineering doctoral dissertation award (2024) Best paper at IEEE Wireless Sensors Conference (2019) Nordic Conference best paper award for PhD research (2019) DSc dissertation award (2010) As principal investigator, he manages: Vision 2030 consortium projects (2-3 annually; PI for two current projects) iCONS: Real-time resource flow monitoring via indoor positioning RECAP: Deep learning analysis of progress/quality from images/point clouds DiCtion: Integrated data systems for real-time stakeholder situation pictures He actively contributes to the "Performance in Building Design and Construction" research group and leverages the Vision 2030 consortium as a collaborative platform for industry transformation, driving adoption of digitalized, industrialized construction methods through academic-industry partnerships.
Elliot Hawkes is an Associate Professor in the Department of Mechanical Engineering at the University of California, Santa Barbara (UCSB). His research bridges design, mechanics, and non-traditional materials to develop robust, adaptable, human-safe robots for uncertain environments. He leads the Hawkes Lab, focusing on bio-inspired microstructured adhesives, nonlinear compliant mechanisms, soft actuators, exoskeletons, and growing robots. PhD from Stanford University, 2015 Postdoctoral Scholar at Stanford's CHARM Lab, 2015-2016 Assistant Professor at UCSB since 2016 Current projects include: Material-like robotic collectives with spatiotemporal control Variable friction shoe for locomotor therapy High-force soft actuators for industrial applications Vine-inspired robots for search and rescue Growing robots for biomedical and environmental use Recent publications in Science and Nature highlight breakthroughs in soft robotics and human-safe actuation. His team has received multiple NSF GRFP awards and a UCSB Regents Fellowship. The lab holds patents in adhesive gripping, soft actuation, and reconfigurable robotics.
Professor Lyudmila Mihaylova is a distinguished academic at the University of Sheffield's School of Electrical and Electronic Engineering, where she holds the position of Professor of Signal Processing and Control. She has established herself as a leading researcher in the fields of signal processing, Bayesian methods, and autonomous systems, with significant contributions to particle filtering techniques for intelligent transportation systems. Her work bridges theoretical developments with practical applications across multiple domains including transportation, healthcare, and industrial automation. Prof. Mihaylova's research interests center on nonlinear filtering, sequential Monte Carlo methods, statistical signal processing, and sensor data fusion. Her work spans both theoretical advancements and practical implementations, with particular focus on high-dimensional problems including vehicular traffic flow estimation, image processing, and localization in sensor networks. She has extensive experience with various image modalities such as optical, thermal, LIDAR, SAR, and hyperspectral imaging. Her group actively develops novel methods for autonomous intelligent systems focusing on sensing, tracking, decision making, and machine learning applications. Analysis of Prof. Mihaylova's recent publications reveals a strong trend toward uncertainty quantification in machine learning models, particularly for safety-critical applications. Her work increasingly integrates traditional signal processing techniques with modern deep learning approaches, with applications spanning sewer inspection robotics, medical diagnostics (particularly sleep apnea detection), UAV swarm tracking, industrial manufacturing, and autonomous vehicle systems. A significant portion of her recent research focuses on developing robust methods that can handle incomplete or outlier-corrupted data while providing reliable uncertainty estimates. Among her notable professional achievements: President of the International Society of Information Fusion (ISIF) Senior member of the IEEE Signal Processing Society Associate Editor for IEEE Transactions on Aerospace and Electronic Systems Associate Editor for Elsevier Signal Processing Journal Prof. Mihaylova has successfully mentored numerous PhD students and postdoctoral researchers, many of whom have gone on to prominent academic and industry positions. Her research has been supported by major funding bodies including EPSRC, EU, MOD/DSTL, and industry partners, with recent projects including 'Protecting Environments with UAV Swarms' (InnovateUK, 2022-2024), 'ShiRAS: Towards Safe and Reliable Autonomy in Sensor Driven Systems' (NSF-EPSRC, 2019-2023), and 'Confident safety integration for Cobots' (Lloyd's Register Foundation, 2019-2020). Her research group follows a collaborative approach with the philosophy 'We share knowledge, we grow.' Prof. Mihaylova maintains active research collaborations with institutions worldwide and has held previous academic positions at Lancaster University (2006-2013) and University of Bristol (2004-2006), along with research visiting positions at the University of Ghent, Katholic University of Leuven, and the Bulgarian Academy of Sciences.
Keenan Albee is a Robotics Technologist at NASA’s Jet Propulsion Laboratory and an incoming Assistant Professor at the University of Southern California (starting Fall 2025). His research focuses on autonomous robotics for extreme environments including lunar missions, microgravity, and underwater operations. Education: Ph.D. in Aeronautics and Astronautics (Autonomous Systems), MIT (2022) S.M. in Aeronautics and Astronautics, MIT (2019) B.S. in Mechanical Engineering, Columbia University (2017) Albee’s work integrates optimal control , reinforcement learning , and motion planning to develop autonomy for mobile robotic systems operating under uncertainty. His expertise spans space robotics , microgravity systems , and underwater robotics , with a focus on environment-aware algorithm design. Recent research includes parametric information-aware motion planning (RATTLE algorithm), distributed multi-agent exploration, and robust control for uncooperative targets. His publications highlight on-orbit validation of autonomy algorithms via NASA’s Astrobee platform and upcoming lunar missions. Scientific Awards: NASA Space Technology Research Fellowship (2022) Albee actively develops open-source autonomy frameworks and will establish the Laboratory for Autonomous Systems in Exploration and Robotics (LASER) at USC. His work bridges theoretical control methods with real-world deployment, including first-of-its-kind achievements in space robotics.
John F. Reid is a prominent Research Professor at the University of Illinois at Urbana-Champaign in the College of Engineering , with dual appointments in Computer Science and Agricultural and Biological Engineering . He serves as Executive Director of the Center for Digital Agriculture . With over 35 years of experience in academic and industrial R&D, his career spans faculty roles at UIUC (1986-2000), leadership at Deere & Company (2000-2020), and Vice President positions at Brunswick Corporation (2020-2022). Education : Ph.D. in Agricultural Engineering (Texas A&M, 1987), M.S. and B.S. in Agricultural Engineering (Virginia Tech, 1982 & 1980) Dr. Reid's research focuses on agricultural automation , machine vision , and innovation management . He has pioneered agricultural robotics , precision technologies , and embodied AI applications in food, construction, and marine systems. His work has resulted in over 30 patents in automated guidance , sensor systems , and agricultural informatics . His scientific contributions center on stereo vision navigation , 3D field mapping , and adaptive control systems for mobile equipment. These innovations underpin modern precision agriculture and agricultural robotics frameworks. Major awards include: NAE Election (2019) ASABE Fellow (2004) University Scholar (1995) Academy of Engineering Excellence (2020) He holds leadership roles in international organizations including the CIGR Working Group on Circular Bioeconomy Systems (Chair 2024-present) and Fraunhofer USA (2013-2022).
Shimon Y. Nof is a Professor of Industrial Engineering at Purdue University's PRISM Center , where he directs NSF-industry supported research on collaborative robotics, cyber-physical systems, and industrial automation. He has held visiting positions at MIT and universities across six countries. Education: B.Sc./M.Sc. in Industrial Engineering & Management (Technion, Israel), Ph.D. in Industrial & Operations Engineering (University of Michigan) Key Achievements: Pioneered computer-aided facility design and Collaborative Control Theory (CCT), with applications spanning factories of the future, agricultural robotics, and transportation security systems His research focuses on cyber-supported integration of distributed e-Work systems and robotics, including precision agriculture with sensor networks. The PRISM Center under his leadership has developed groundbreaking protocols like Best Matching Protocol (BMP) and HUB-CI telerobotics, with real-world implementations across 400+ labs globally. Scientific honors include: Engelberger Medal (2002) Induction into Purdue's Book of Great Teachers (1999) Leadership roles in IFPR and IFAC Multiple book awards from Association of American Publishers The PRISM Global Research Network (est. 2001) now extends his work through 18 books and 6 patents, including the FTTP-TIF communication protocol and Facility Sensor Network (FSN) technology currently applied in greenhouse robotic operations.
Istvan David is an Assistant Professor in the Department of Computing and Software at McMaster University , with research expertise spanning Digital Twins , Model-Driven Engineering , and Sustainability . His work bridges theoretical and applied domains, focusing on smart ecosystems , collaborative modeling , and AI-driven simulation . Key contributions include frameworks for digital twin evolution and interoperability in sustainable systems. Education : BSc, MSc, and PhD in Computer Engineering and Computer Science from Budapest University of Technology and Economics, and University of Antwerp. Research Areas : Digital Twins, Model-Driven Engineering, Reinforcement Learning, Smart Ecosystems, Sustainability, Collaborative Modeling, Cyber-Biophysical Systems, and Software Architecture. Recent Article Trends emphasize AI integration with digital twins, collaborative modeling in industrial contexts, and sustainable systems engineering . His work often combines machine learning with formal modeling to address challenges in technical sustainability and smart agriculture .
