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Nikolai MatniView profile

Assistant Professor

• Machine Learning
• Control Theory
• Robotics
• +10 more

Nikolai Matni is an Assistant Professor in the Department of Electrical and Systems Engineering at the University of Pennsylvania. He holds a secondary appointment in the Department of Computer and Information Science and is a member of the Applied Mathematics and Computational Sciences (AMCS) graduate group. His research focuses on integrating learning, optimization, and control for safety-critical and data-driven cyber-physical systems, with applications in robotics, autonomy, and distributed control. Secondary Appointment: Computer and Information Science (University of Pennsylvania) Labs/Centers: GRASP Lab, PRECISE Center His research bridges machine learning, robust control, and autonomous systems, particularly in developing guaranteed-safe strategies for cyber-physical systems. He emphasizes the importance of reliability and robustness in learning-based control for applications like self-driving vehicles and agile robots, where failures could be catastrophic. Recent publications highlight advancements in vision-based robotic control, neural ODEs for motion planning, adversarial exploration strategies, and stability-constrained learning. These works span conferences such as ICRA, CoRL, WACV, IROS, and L4DC, with a focus on safety-critical applications. Notable scientific awards include the NSF CAREER Award, George S Axelby Award (for his work on System Level Synthesis), AFOSR YIP award, and Google Research Scholar Award. He was also elevated to IEEE Senior Member. Matni advises Ph.D. students in Computer and Information Science (CIS), Electrical and Systems Engineering (ESE), and Applied Mathematics and Computational Sciences (AMCS). His teaching includes courses like ESE 2030 (Linear Algebra with Engineering/AI applications) and others focused on control theory and robotics.

Florent CosandierView profile

Lecturer

• Compliant Mechanisms
• Flexure Mechanisms
• Precision Engineering
• +5 more

Florent Cosandier serves as a Lecturer in the Section of Microtechnology and Research Associate at the Micromechanical and Horological Design Laboratory (INSTANT-LAB) within the School of Engineering at Swiss Federal Institute of Technology Lausanne (EPFL). His dual roles bridge precision engineering education and advanced research in mechanical systems design. His research centers on compliant and flexure mechanisms with applications spanning horology, space instrumentation, and micro-technology. Key focus areas include parasitic error minimization in translation stages, dynamic balancing for mechanical oscillators, and additive manufacturing of complex compliant systems. Recent work demonstrates experimental validation of zero-force mechanisms and novel pivot designs for high-precision positioning. Analysis of his 15 most recent publications reveals a dominant trend in rectilinear stage development (6 articles), horological applications (4 articles), and space telescope assembly systems (3 articles). His work consistently emphasizes experimental validation, large-range motion capabilities, and parasitic shift elimination through innovative parallel mechanism configurations. Cosandier has advised at least one PhD student at EPFL: Kruis Johannes Richard Cornelis Geerit. He contributes to teaching through courses like "Advanced mechanisms for extreme environments" within the SMT-ENS unit. As a core member of INSTANT-LAB, he collaborates on projects involving metallic additive manufacturing for damping systems, micro-vibration suppression platforms, and silicon-based flexure mechanisms. His current research trajectory shows increasing focus on space applications and bi-material additive manufacturing techniques.

Crystal NoelView profile

Assistant Professor

• Quantum Computing
• Trapped Ions
• Integrated Photonics
• +4 more

Crystal Noel is an Assistant Professor at Duke University in the Pratt School of Engineering and Trinity College of Arts & Sciences , with appointments in both the Department of Electrical and Computer Engineering and Physics since 2022. She is also a Member of the Duke Quantum Center since 2024. Ph.D. in Electrical and Computer Engineering from University of California, Berkeley (2019) B.S. in Massachusetts Institute of Technology (2013) Her research focuses on quantum computing and simulation with trapped ions , integrated photonics for scalable trapped ion systems , and electric-field noise from surfaces . Recent work includes developing non-invasive mid-circuit measurement techniques, sympathetic cooling for ion chains, and cross-platform quantum state comparison. She has secured significant grants from National Science Foundation , Rochester Institute of Technology , and Defense Advanced Research Projects Agency for quantum co-design and networking projects. Her lab ( Noel Lab ) explores scalable quantum computing architectures and surface noise mitigation. She teaches courses ranging from foundational Fields and Waves: Fundamentals of Information Propagation to advanced topics in Quantum Engineering with Atoms and Advanced Topics in Electrical and Computer Engineering .

René van de MolengraftView profile

Professor

• Autonomous Robotics
• Robotics Control Systems
• Human-Robot Interaction
• +3 more

René van de Molengraft is a Full Professor of Robotics at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e). He holds dual professorships in EAISI High Tech Systems and EAISI Foundational. His research focuses on autonomous robotic systems operating in human environments, emphasizing adaptability and task execution in varying conditions. Academic Background: MSc in Mechanical Engineering (TU/e, 1986) PhD in Identification of Mechanical Systems for Control (TU/e, 1990) Career progression: Assistant Professor (1990–2008) → Associate Professor (2008–2024) → Full Professor (2024) Research Interests: Autonomous robotics, human-robot interaction, agricultural automation, and control systems. His work emphasizes practical applications, such as the Tech United RoboCup team (world champion in multiple years) and large-scale robotics competitions. Projects: Key initiatives include the Tech United RoboCup team, the AI-matters manufacturing network, and the Frontiers in Autonomous Systems Technology (FAST) project. He has organized major robotics events like the 2013 and 2024 RoboCup World Championships in Eindhoven. Labs/Teams: Founder and leader of Tech United, a robotics team renowned for its achievements in robotic soccer and service robotics. Active in TU/e's Robotics research group and collaborations with industry partners.

• Space Geodesy
• Satellite Laser Ranging
• Lunar Laser Ranging
• +7 more

Karl Ulrich Schreiber is an Adjunct Professor at the Department of Physics and Astronomy, University of Canterbury, New Zealand, and an apl. Professor at the Institute for Astronomical and Physical Geodesy at the Technical University of Munich (TUM). He is a scientist at the Geodetic Observatory Wettzell, jointly operated by TUM and the Bundesamt für Kartographie und Geodäsie (BKG). His work bridges fundamental physics and geodetic applications, with leadership roles in major international projects including ESA’s MAGIC/Science, QSG4EMT, and Baltic+ Theme 5, as well as DFG Research Units NEROGRAV and UPLIFT. His research focuses on Space Geodesy , Satellite and Lunar Laser Ranging , and Ring Laser Technology . He has pioneered the use of large ring laser gyroscopes for measuring Earth's rotation, polar motion, and seismic rotations. His work enables high-precision monitoring of geophysical phenomena such as Earth tides, Chandler wobble, and rotational ground motions from earthquakes. He is a key contributor to multi-technique co-location studies (VLBI, SLR, GNSS) and time transfer experiments, advancing the Global Geodetic Observing System (GGOS). His recent publications show a strong trend in developing and applying large-scale ring laser arrays (e.g., ROMY) for geophysical sensing, photon-counting laser ranging for space debris and satellite tracking, and optical timing systems for synchronization across geodetic networks. These efforts span disciplines including geodesy, seismology, quantum optics, and fundamental physics. Scientific contributions include: Development of the Wettzell Large Ring Laser (G-ring) for continuous Earth rotation monitoring. First direct measurements of Earth's diurnal polar motion and Chandler wobble using ring lasers. Pioneering work in rotational seismology, validating ring laser data against seismic arrays. Contributions to lunar laser ranging and its role in reference frame realization. Leadership in ESA and DFG projects advancing space geodesy and inertial sensing. He advises doctoral and master’s students within the DFG Research Training Group UPLIFT and collaborates with international institutions on instrumentation and data analysis. His lab at Wettzell hosts advanced laser ranging and ring laser systems, serving as a fundamental geodetic observatory. Future work includes enhancing clock ties for global geodesy, expanding multi-component rotation sensing, and advancing space-based geodetic technologies.

• Autonomous Driving
• Sensor Fusion
• Intelligent Transportation Systems
• +5 more

Prof. Dr.-Ing. Christoph Stiller is a full professor at the Karlsruher Institut für Technologie (KIT) and serves as the director of the Institute of Measurement and Control Technology (Institut für Mess- und Regelungstechnik, MRT). His work focuses on autonomous driving, sensor fusion, probabilistic estimation, HD mapping, motion planning, and intelligent transportation systems. Education: Details on his academic degrees are not provided in the text, but he holds the title of Dr.-Ing. indicating a doctoral degree in engineering. Research Interests: Prof. Stiller's research spans a wide array of topics critical to the development of autonomous vehicles. His work includes: Sensor Fusion: Integrating data from LiDAR, cameras, and radar to create robust perception systems. HD Mapping & Localization: Developing high-definition maps and precise localization techniques for urban and highway environments. Motion Planning & Decision Making: Creating algorithms for safe and efficient trajectory planning under uncertainty. Machine Learning & AI: Applying deep learning and reinforcement learning to perception, prediction, and control tasks. Publication Trends: His recent publications (2023–2025) emphasize robust traffic light detection, image stitching for panoramic views, motion prediction using redundancy reduction, and safety-enhanced model predictive control. The work increasingly integrates learning-based methods with classical control and estimation theory. Scientific Awards: No specific awards are listed in the provided text. Teaching & Supervision: Prof. Stiller teaches foundational and advanced courses in measurement and control systems, probabilistic estimation, and autonomous driving. He holds regular office hours during both summer and winter semesters and is actively involved in advising students and researchers. Labs & Teams: He leads the Institute of Measurement and Control Technology (MRT) at KIT, which is engaged in cutting-edge research in autonomous systems. The institute collaborates with industry and academia on large-scale projects such as UNICARagil and various European initiatives.

• Dynamic Systems and Control
• Mechatronics
• Digital Printing and Fabrication
• +7 more

George T. C. Chiu is a Professor in the School of Mechanical Engineering at Purdue University, with courtesy appointments in Electrical and Computer Engineering and Psychological Sciences. He holds a 50% appointment as Assistant Dean for Global Engineering Programs and Partnerships. His research focuses on mechatronics, dynamic systems and control, functional printing, and human-machine interaction, with applications in biomedical engineering, robotics, and advanced manufacturing. Education: PhD (1994), MS (1990) University of California, Berkeley; BS (1985) National Taiwan University. Research interests emphasize application-driven solutions for printing technologies, motion control, and embedded systems. Notable projects include developing inkjet printing for biomedical materials and sensor systems. Awards include ASME Fellowship (2013) and the 2024 ASME Rabins Leadership Award. Publications span topics like inkjet drop dynamics, control systems, and biofabrication. He has led initiatives such as the Purdue FIRST Programs, fostering K-12 STEM education through robotics mentorship. Editorial roles include Editor-in-Chief of IEEE/ASME Transactions on Mechatronics (2017-2019).

• Quantum photonics
• Quantum optomechanics
• Spin qubits in 2D materials
• +5 more

Tongcang Li is a Professor of Electrical and Computer Engineering and Physics at Purdue University, affiliated with the Elmore Family School of Electrical and Computer Engineering and the Department of Physics and Astronomy. He holds joint appointments at the Birck Nanotechnology Center and the Purdue Quantum Science and Engineering Institute. His research focuses on quantum photonics, optomechanics, and quantum sensing, with breakthroughs in levitated nanoscale systems and Casimir effects. Education: PhD, The University of Texas at Austin, 2011 BS, University of Science and Technology of China, 2004 Research Interests: Spin qubits in 2D materials (e.g., hexagonal boron nitride) Levitated optomechanics for quantum control and sensing Casimir interactions and vacuum friction Quantum transducers and optically trapped nanoparticles Notable Achievements: 2018: One of 10 APS Physics Highlights of the Year for GHz rotation of levitated nanoparticles 2022: Featured in Optics & Photonics News' 'Optics in 2022' for on-chip optical levitation with metalenses Grants & Funding: Supported by NSF, DOE, Gordon and Betty Moore Foundation, Toyota, ONR, DARPA, Sandia National Laboratories, and Los Alamos National Laboratory. Labs/Teams: Leads the Quantum Sensing and Optomechanics Laboratory at Purdue, advancing quantum sensing and quantum information processing technologies.

Amit LalView profile

Professor

• Microsystem Engineering
• MEMS and NEMS
• Ultrasonic Sensors
• +12 more

Amit Lal is a Professor in the School of Electrical and Computer Engineering at Cornell University, with affiliations in Biomedical Engineering, Applied Engineering Physics, and Mechanical and Aerospace Engineering. He is a member of key research centers including Cornell CCMR, NBTC, and KAUST-CU. Education: B.S. in Electrical Engineering, California Institute of Technology, 1990 Ph.D. in Electrical Engineering, University of California, Berkeley, 1996 Prof. Lal's research focuses on the development of integrated microsystems using micro- and nanoscale fabrication. His work spans ultrasonic MEMS, low-power IoT sensors, atomic microsystems, and bio-robotics. He directs the SonicMEMS Laboratory, advancing technologies in GHz ultrasonics, inertial sensing, and chip-scale manipulation of particles. His interdisciplinary interests include biomedical imaging, solid-state devices, nanotechnology, and plasma science. His recent publications highlight innovation in energy harvesting, MEMS gyroscopes, and biologically integrated systems. The works reflect strong trends in autonomous sensing, miniaturized power sources, and hybrid bio-electromechanical systems, particularly for medical and navigation applications. Scientific Awards and Honors: NSF CAREER Award Whitaker Foundation Award Department of Defense Exceptional Service Award Best Program Manager Award, DARPA IEEE Ultrasonics and Frequency Control Symposium Best Paper Award IEEE NEMS Best Paper Award Robert M. Scharf 1977 Professor, Cornell Engineering HHMI Visiting Scientist, Janelia Farms Intel Fellowship (awarded to advisee) Prof. Lal has advised numerous students who have gone on to win awards and publish impactful research. He has secured significant research funding through DARPA and other agencies, managing and initiating multiple high-impact programs. His leadership extends to service on technical committees for IEEE conferences and journals, including Transducers and the IEEE Sensors Council. He has also contributed to academic recruiting within ECE. He leads the SonicMEMS Laboratory , a multidisciplinary research group focused on transforming sensing, communication, and computation at the microscale. The lab fosters collaboration across engineering and life sciences, pushing the boundaries of what integrated microsystems can achieve.

• Computer Graphics
• Computer Vision
• Human-Computer Interaction
• +7 more

Changjian Li is an Assistant Professor in the School of Informatics at the University of Edinburgh. He leads the GraphViX Group (Graphics, Vision and X) and is a member of the Institute of Perception, Action and Behaviour (IPAB). His research spans computer graphics, computer vision, and human-computer interaction with a focus on 3D generation and analysis. Education: Bachelor's Degree from Shandong University (2014) Ph.D. from the University of Hong Kong (2019) under Prof. Wenping Wang Postdoc at University College London (UCL) with Prof. Niloy Mitra Starting Researcher position at Inria with Dr. Adrien Bousseau Research Interests: Changjian's research focuses on sketch-based 3D modeling, CAD modeling, point cloud processing, and medical imaging applications. He develops systems that bridge intuitive sketching with precise CAD workflows, enhances 3D animation pipelines, and applies neural methods to sparse medical data reconstruction. Scientific Recognition: Best Paper Honorable Mention Award (MICCAI 2021) CADTalk selected as Highlight (CVPR 2024 top 10%) ACM SIGGRAPH Asia 2018 cover image selection ACM SIGGRAPH Asia 2015 technical paper highlight CVPR 2019 poster highlighted in 'Computer Vision News' Advising & Collaborations: He mentors postdocs and PhD students including Duolikun Danier, Haocheng Yuan, Ankan Bhunia, and Lei Zhong. Former advisees include Salvatore Esposito (now at Edinburgh), Guangshun Wei (Shandong University), and Mingjun Yang (University of Melbourne). Collaborates with Oisin Mac Aodha, Hakan Bilen, and Niloy Mitra. Professional Service: Currently serves as Associate Editor for IEEE TVCG and participates in program committees for SIGGRAPH Asia, SIGGRAPH, EuroGraphics, and Geometry Design and Computing (GDC) conferences.

• Computer Vision
• Natural Language Processing
• 3D Human Motion Synthesis
• +3 more

Gül Varol is a permanent researcher at École des Ponts ParisTech's IMAGINE group, an ELLIS Scholar, and Guest Scientist at Max Planck Institute. She holds a PhD from Inria Paris/ENS with awards from ELLIS and AFRIF. Her academic service includes Program Chair at ECCV'24 and Area Chair roles at major conferences. Current affiliations: IMAGINE group (École des Ponts ParisTech), Max Planck Institute Previous roles: Postdoctoral researcher at University of Oxford Her research focuses on vision-language applications, particularly in 3D human motion synthesis, sign language technology, and audio description generation. Key techniques include text-conditioned diffusion models, temporal context modeling, and synthetic data utilization. Scientific contributions recognized through: Google Research Scholar award (2023) ELLIS PhD Award (2020) AFRIF PhD thesis award (2020) Best application paper at ACCV'20 Recent publications demonstrate expertise in: Text-driven 3D motion editing (MotionFix, 2024) Cross-dataset generalization studies (TMR++, 2024) Temporal action composition frameworks (TEACH, 2022) Sign language dense annotation methods (BOBSL, 2022) Zero-shot audio description generation (AutoAD-Zero, 2024) She actively contributes to dataset development including BOBSL (British Sign Language corpus) and SURREACT synthetic action dataset, while pioneering new evaluation metrics for audio description quality and motion retrieval benchmarks.

• Quantum Magnetometry
• Precision Electromagnetic Measurements
• Plasma Immersion Ion Implantation (PIII)
• +7 more

Michael P. Bradley is a Professor in the Department of Physics and Engineering Physics at the University of Saskatchewan, affiliated with the College of Arts and Science. He holds a Ph.D. from MIT and is a Professional Engineer (P.Eng.). His research focuses on precision measurement techniques, plasma-based nanofabrication, and quantum metrology, including work on diamond NV-centre magnetometers and superconducting watt balance systems. He leads the University of Saskatchewan Plasma Physics Laboratory (U of S PPL) and has received a Canada-UK Joint Quantum Technology grant for quantum sensor development. Education BSc (Honours) in Applied Physics, University of New Brunswick Ph.D. in Physics, Massachusetts Institute of Technology (MIT) Research Interests Bradley specializes in quantum magnetometry , plasma processing , semiconductor nanostructures , and precision electromagnetic measurements . His lab develops novel techniques for materials characterization and fabrication, including plasma immersion ion implantation (PIII) for micro- and nano-scale engineering, graphene doping, and silicon photonics. Recent work includes advancements in diamond NV-centre magnetometry for quantum technologies. Grants & Collaborations Recipient of a prestigious Canada-UK Joint Quantum Technology grant (2023). Collaborated internationally, including at the Bureau International des Poids et Mesures (BIPM) in France, where he contributed to superconducting watt balance prototypes for redefining mass standards. Teaching Teaches courses in optics, thermodynamics, and planetary astronomy, including EP421: Optical Systems & Materials and ASTR104: Planetary Astronomy .

Stavros G. VougioukasView profile

Professor

• Agricultural Robotics
• Mechanization of Specialty Crops
• Automation in Harvesting
• +5 more

Stavros G. Vougioukas is a Professor and Vice Chair in the Department of Biological and Agricultural Engineering at the University of California, Davis. His research focuses on agricultural robotics, mechanization, and automation for specialty crops, with particular emphasis on robotic harvesting systems and precision agriculture technologies. He leads initiatives in developing actuator systems, perception, and control mechanisms to optimize crop management. Key areas of expertise include robotic fruit harvesting, autonomous vehicle navigation in orchards, and site-specific pest management strategies. His work integrates mechanical engineering principles with advanced automation to address labor shortages and improve agricultural efficiency. Recent projects emphasize data-driven solutions for yield estimation, worker activity analysis, and economic viability of robotic systems. Academic contributions span over 50 peer-reviewed publications (2023-2025), with a focus on robotic orchard platforms, crop transport systems, and sensor-based automation. Notable innovations include vacuum suction end-effectors for fruit harvesting and GNSS-free navigation systems for autonomous vehicles. He also explores sustainable agricultural machinery through techno-economic analyses of electric/hybrid tractors. Current research bridges robotics and agricultural economics, addressing labor cost optimization and precision irrigation. His lab collaborates with industry partners to translate prototypes into field-ready solutions, emphasizing practical applications for specialty crop production systems.

Renjie ZhaoView profile

Assistant Professor

• Wireless Networking
• Mobile Computing
• 5G/6G Technologies
• +8 more

Renjie Zhao is an Assistant Professor in the Department of Computer Science at Johns Hopkins University and a member of the Data Science and AI Institute. His research focuses on wireless networking and mobile computing, with significant contributions to millimeter-wave communications, software-defined radio, and IoT systems. Dr. Zhao received his B.E. in Electric Power Engineering and Automation from Shanghai Jiao Tong University in 2018, followed by an M.S. (2020) and Ph.D. (2023) in Electrical and Computer Engineering from the University of California San Diego, where he was advised by Professor Xinyu Zhang. His research centers around three main areas: next-generation wireless network architectures (5G millimeter wave, 6G joint communication and sensing, Internet of Things), novel radio hardware and software design (software-defined radio, wireless brain interfaces, low-power ultra-wide-band), and ubiquitous communication and sensing systems (smart homes, virtual/augmented reality, localization, ultra-reliable RFID for supply chains). His work bridges theoretical innovation with practical implementation, often resulting in open-source hardware and software platforms that advance the field. Dr. Zhao's research has been published in top conferences including ACM SIGCOMM, MobiCom, and NSDI. His work demonstrates a clear progression from foundational wireless communication systems to increasingly sophisticated sensing and localization applications, with consistent focus on practical deployment challenges and solutions. Scientific Awards: Best Paper Award at ACM MobiCom 2020 for work on massive MIMO millimeter-wave software radio Best Paper Award at ACM SenSys 2023 for NeuroRadar paper Hopkins AITC funding for AI technologies promoting healthy aging Dr. Zhao actively serves the research community as TPC member for major conferences including MobiCom'25, NSDI'25, and MobiSys'25, and as a reviewer for leading journals. He is involved in multiple NSF-funded projects, including an NSF CIRC project developing the next-stage M-Cube platform. His lab, focused on wireless systems, maintains strong industry connections with companies like Qualcomm and Samsung. Dr. Zhao leads the M-Cube project, an open-source millimeter-wave massive MIMO software radio platform that has been adopted by numerous research institutions worldwide. His team continues to develop innovative wireless technologies with practical applications in supply chain management, healthcare, and smart environments.

Neil WhiteView profile

Professor

• Medical sensors
• Intelligent sensor systems
• Energy harvesting
• +2 more

Neil White is Professor of Intelligent Sensor Systems at the University of Southampton's Electronics and Computer Science (ECS) school and serves as Director of the ECS Centre for Healthcare. He has held various leadership positions including Head of Electronics and Computer Science from 2011 to 2015 and has been instrumental in establishing research initiatives in sensor technology and energy harvesting. His research interests focus on medical sensors , intelligent sensor systems , and energy harvesting technologies. Professor White's work bridges the gap between engineering and healthcare applications, with significant contributions to wearable medical devices, particularly respiratory monitoring systems. His research integrates micro-electromechanical systems (MEMS), energy harvesting techniques, and smart textiles to create innovative healthcare solutions. Analysis of his recent publications reveals a strong focus on energy harvesting technologies, medical sensor applications, and e-textile development. His work spans multiple disciplines including biomedical engineering, electrical engineering, and materials science, with applications in healthcare monitoring, environmental sensing, and transportation systems. The research demonstrates a consistent theme of creating self-powered, intelligent sensor systems for practical applications. Professor White has received notable recognition including the Callendar silver Medal (2009) from the Institute of Measurement and Control and the 1989 Educational Prize from the International Society for Hybrid Microelectronics. Principal Investigator on NIHR i4i project developing low-cost wearable respiration sensors Former Director and co-founder of Perpetuum Ltd., specializing in vibration energy harvesting Current collaborations with clinicians at University Hospital Southampton Extensive funding from EPSRC, European Union, and industry partners Professor White leads research within the Smart Electronic Materials and Systems group, the Institute for Life Sciences, and the Centre for Health Technologies. His work in the Interdisciplinary Musculoskeletal Health and Digital Health research areas demonstrates his commitment to cross-disciplinary collaboration to address complex healthcare challenges through engineering solutions.