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Riddhi DasView profile

Researcher

• Soft Robotics
• Biomimetic Robotics
• Autonomous Systems
• +3 more

Riddhi Das is a Postdoctoral Researcher at the University of Freiburg, affiliated with the Cluster of Excellence liv MatS (Freiburg Center for Interactive Materials and Bioinspired Technologies). Their research focuses on soft robotics, particularly the design, fabrication, and actuation of pneumatic soft robots. Current work emphasizes developing soft autonomous machine (SaM) systems with integrated logic gates and sensors for environmental interaction. Key research interests include biomimetic robotics inspired by biological systems such as seahorses and earthworms, peristaltic locomotion in granular media, and modular robotics for multi-terrain environments. The lab aims to merge advancements from liv MatS research areas into fully operational autonomous robotic systems. Publications highlight innovations in bioinspired robotics, granular medium locomotion, and programmable materials. While no awards are explicitly mentioned, their work aligns with cutting-edge interdisciplinary robotics research. Advising and grants details are not provided in the text. The lab is part of the liv MatS initiative, focusing on interactive materials and bioinspired technologies.

• Artificial Intelligence
• Machine Learning
• Signal and Image Processing
• +4 more

Dr. Salim Bouzerdoum is a Senior Professor of Computer Engineering at the University of Wollongong (UOW), affiliated with the School of Electrical, Computer & Telecommunications Engineering. He holds a Ph.D. and M.Sc. in Electrical Engineering from the University of Washington. His roles include former Associate Dean for Research (2007–2013) and Head of School (2004–2006). He has served on the Australian Research Council panels and held visiting professorships globally. Education: Ph.D. in Electrical & Computer Engineering, University of Washington, Seattle, USA M.Sc. in Electrical Engineering, University of Washington, Seattle, USA Research Interests: His work focuses on Artificial Intelligence , Machine Learning , and Signal & Image Processing , with applications in radar imaging, computer vision, and smart sensors. Key areas include neural networks, object detection/tracking, and compressive sensing. Recent projects include assistive navigation tools for vision-impaired individuals and underwater mine detection via sonar imaging. Grants & Funding: He leads or co-leads over 30 funded projects, including: AI-based SAR Satellite Imaging System for Oceanic Waves (AGO, 2024–2025) A portable AI-guided navigation tool for vision-impaired people (KONEKSI, 2024–2026) Deep Learning for Vessel Surveillance using Satellite Imagery (NSW Space Research Network, 2022–2023) Teaching & Supervision: With 30+ years of experience, he has supervised 38 Ph.D. and 22 master’s students, mentored 12 early-career researchers, and delivered courses like Applied Data Analytics and Neural Networks . Current supervision includes projects on deep learning for obstacle detection and semantic segmentation. Awards: Eureka Prize (2011) for Defence Science ARC College of Experts Member (2009–2011) Multiple Vice-Chancellor Research Awards (1998–1999)

• Robotics
• Artificial Intelligence
• Autonomous Systems
• +3 more

Prof. Dr. Frank Kirchner is a leading expert in robotics and artificial intelligence, serving as Executive Director of DFKI Bremen and Professor of Robotics at the University of Bremen since 2002. He founded the Robotics Innovation Center (DFKI Bremen) and co-founded the Brazilian Institute of Robotics (2013) and Institute for Maritime Technologies (MarTech, 2010). Education: Doctorate in Informatics (Dr. rer. nat, Bonn, 1999); Diploma in Informatics and Neurobiology (Bonn, 1994) Research Interests focus on biologically inspired robotic motion, highly redundant systems, AI-driven autonomous robotics, and cross-domain applications in space, maritime, and industrial contexts. His work bridges theoretical and applied robotics, emphasizing simulation-reality gaps and adaptive control frameworks. Recent Publications highlight advancements in co-design optimization for manipulators, planetary exploration robotics, and sensor-based industrial assembly learning, reflecting interdisciplinary trends in AI, mechatronics, and environmental adaptation. Scientific Awards: Honorary Doctorate (2017, SENAI CIMATEC, Brazil) BBAW Membership (2015–) Advising includes supervising 65 doctoral theses (38 completed, 27 in progress) and mentoring over 250 bachelor’s/master’s students at the University of Bremen. He leads major projects like AI-REEFSHIELD and FieldCoBots , with funding from EU, DFG, BMBF, and DLR.

Cory SimonView profile

Associate Professor

• Machine Learning
• Bayesian Optimization
• Computational Materials Science
• +3 more

Cory Simon serves as Associate Professor in the Department of Chemical, Biological, and Environmental Engineering within Oregon State University's College of Engineering. His research integrates machine learning, optimization, and chemical engineering to advance materials discovery and environmental sensing systems. His academic foundation includes a Ph.D. in Chemical Engineering from the University of California, Berkeley and a B.S. in Chemical Engineering from The University of Akron. Simon's work centers on Bayesian methodologies for scientific challenges, featuring: Bayesian optimization for adaptive materials synthesis Statistical inversion of physical systems with uncertainty quantification Computational design of nanoporous sensor arrays Stochastic algorithms for robotic environmental monitoring Recent publications demonstrate accelerating focus on multi-fidelity optimization for molecular design and atmospheric water harvesting, bridging chemical engineering with computational science through data-driven approaches. Leading The Simon Ensemble research group, Simon champions a versatile 'buffet-style' research philosophy—drawing from mathematics, statistical mechanics, and machine learning to address interdisciplinary problems across chemistry, materials science, and environmental engineering.

Truong NghiemView profile

Associate Professor

• Intelligent cyber-physical systems
• Digital twins
• Scientific and physics-informed machine learning
• +5 more

Truong Nghiem is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Central Florida (UCF), part of the College of Engineering and Computer Science. He holds a Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania and previously served as an Assistant and Associate Professor at Northern Arizona University (2018–2024). His research focuses on intelligent cyber-physical systems, digital twins, physics-informed machine learning, and distributed optimization/control, with applications in smart buildings, autonomous vehicles, and robotics. He leads the intelligent Cyber-Physical Systems (iCPS) Lab, advancing foundational research in these areas. Notable awards include the NSF CAREER Award (2023) for composite physics-informed learning and the NSF ERI Award (2022) for building HVAC system research. He is a Senior Member of the IEEE and a member of the ACM. Recent work emphasizes safe machine learning for control systems, communication-efficient optimization algorithms, and physics-constrained motion prediction for autonomous systems. His publications span journals like IEEE Robotics and Automation Letters and conferences such as the American Control Conference. Grants and research initiatives include projects on HVAC system modeling, distributed trajectory planning for multi-vehicle systems, and adaptive sampling strategies for mobile sensor networks. Collaborations involve industry and academic partners in energy systems, robotics, and control engineering. The iCPS Lab’s work integrates theory, simulation, and real-world validation to address complex cyber-physical challenges.

Nirwan AnsariView profile

Professor

• 6G Networks
• Wireless Charging
• Machine Learning
• +5 more

Nirwan Ansari is a Distinguished Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT). His research focuses on cutting-edge advancements in 6G networks , wireless charging , machine learning , and Internet of Things (IoT) . He has contributed extensively to AI-driven network optimization and sustainable energy solutions for next-generation communication systems. Ph.D., Electrical Engineering, Purdue University (1988) M.S., Electrical Engineering, University of Michigan-Ann Arbor (1983) B.S., Electrical Engineering, NJIT (1982) His recent work explores AI-native network slicing , UAV-assisted edge computing , and holographic communication . Publications highlight synergies between terrestrial and non-terrestrial networks , digital twin integration, and energy-efficient IoT systems . He serves as an Honorary Chair and contributes to major conferences like IEEE INFOCOM and IWCMC.

Babak MehranView profile

Associate Professor

• Transportation Network Resilience
• Big Data Analytics in Transportation
• Autonomous and Connected Vehicles
• +4 more

Babak Mehran is an Associate Professor in the Department of Civil Engineering at the University of Manitoba (Price Faculty of Engineering). He holds a PhD in Civil Engineering from Nagoya University (2009). His research focuses on transportation network resilience, big data analytics, and AI-driven solutions for traffic management. He leads the Urban Mobility and Transportation Informatics Group (UMTIG), collaborating with government and industry on applied transportation research. Key research areas include autonomous vehicle integration, cold-region traffic vulnerability, and optimization of public transit systems. Dr. Mehran has advised graduate students on topics like traffic safety, sensor placement, and semi-flexible transit design. His work bridges theoretical models (e.g., reinforcement learning algorithms) with real-world applications such as winter road maintenance strategies and transit demand analysis. Recent publications emphasize AI-driven traffic prediction, climate adaptation for infrastructure resilience, and safety metrics for truck operations in harsh environments. He collaborates internationally on transportation policy and has contributed to methodologies for evaluating congestion relief strategies using travel time reliability analysis. Lab: Urban Mobility and Transportation Informatics Group (UMTIG) Key Partners: Government agencies, transportation industries, academic collaborators Current Focus: Autonomous shared mobility, cold-climate traffic systems, data fusion for traffic monitoring

Wei ShiView profile

Professor

• Distributed computing
• Cloud computing
• Data center networks
• +6 more

Professor Wei Shi is a faculty member at the School of Computer Science, Carleton University. His research focuses on distributed computing, cloud networks, algorithm design for sensor/actuator systems, big data analytics, and data privacy. Notable projects include federated learning optimizations, blockchain-enabled edge intelligence for IoT/vehicle networks, and AI-driven cybersecurity solutions. His work addresses challenges in dynamic resource allocation, anomaly detection, and privacy-preserving techniques. Research Interests: Distributed Computing: Optimizing federated learning and client selection algorithms for wireless networks. Blockchain & Edge Intelligence: Developing decentralized systems for IoT and vehicular networks using AI large models. Security & Privacy: Innovating methods to detect AI-generated content, combat cyber-physical attacks, and protect user data privacy. Publications: Recent works emphasize federated learning applications, blockchain integration with edge computing, and cybersecurity for vehicular/IoT ecosystems. Key themes include energy-efficient algorithms, dynamic resource allocation, and intrusion detection in constrained environments. Email: wei.shi@carleton.ca

Munir NazzalView profile

Professor

• Transportation Engineering
• Civil Engineering
• Pavement Engineering
• +4 more

Dr. Munir Nazzal is a Professor of Civil Engineering and Director of the Center for Smart, Sustainable & Resilient Infrastructure (CSSRI) at the University of Cincinnati. His research focuses on sustainable transportation infrastructure, pavement engineering, and innovative materials technology. He leads over $13M in grants from federal and state agencies, specializing in asphalt mixtures, pavement performance, and smart infrastructure. He serves as Principal Investigator (PI) on numerous projects, including optimizing maintenance equipment tracking, evaluating micro-surfacing bond strength, and developing AI-driven pothole detection systems. Nazzal is an editor for the ASCE Journal of Materials in Civil Engineering and Buildings Journal, and a licensed professional engineer in Ohio and Louisiana. His work integrates emerging technologies like IoT and autonomous vehicles for infrastructure monitoring. Key contributions include field validation of robotic crack sealing, analysis of aramid fibers in asphalt, and lifecycle cost studies of winter pothole patching methods. His research emphasizes cost-effective, environmentally friendly solutions for local and state transportation systems. Recent grants include a $600,000 federal project for district highway maintenance research, and a $1.2M study on robotic crack sealing methods. He collaborates with industry partners like Honda on vehicle-based roadway data pilots. Nazzal's lab explores nanoscale asphalt properties, thermal expansion effects, and recycled material utilization in pavements.

Francesc Moll EchetoView profile

Associate Professor

• Energy Harvesting
• Integrated Circuit Design
• Low Power Electronics
• +5 more

Francesc Moll Echeto is an Associate Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Departament d'Enginyeria Electrònica and the Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona. He leads the HIPICS research group focused on high-performance integrated circuits and systems design. His expertise spans energy harvesting, low-power electronics, process variability management, and secure circuit design. He coordinates the Doctorat en Enginyeria Electrònica program and has coordinated EU-funded projects like the European Processor Initiative (EPI). Education: M.S. in Physics, Universitat de les Illes Balears, 1991 Ph.D. in Electronic Engineering, Universitat Politècnica de Catalunya, 1995 Research Focus: His work addresses energy-efficient computing, including: - Design of circuits tolerant to manufacturing variability - Energy harvesting from mechanical and RF sources - Secure hardware countermeasures against side-channel attacks - RISC-V architecture implementations in advanced technologies - Edge computing and autonomous sensor systems Grants & Collaborations: Coordinator of R&D projects like 'ARQUITECTURA DE COMPUTADORES DE ALTAS PRESTACIONES' (PID2023-146511NB-I00) Part of the Barcelona Zettascale Lab consortium Collaborations with Barcelona Supercomputing Center and industry partners Awards: HiPEAC Paper Award (2023, 2024) for innovations in vector processing and DNN acceleration Labs/Teams: Leads the HIPICS group and the EFRICS subgroup, collaborating on EU-funded initiatives like the European Processor Initiative. Active in open-source silicon projects (e.g., Sargantana RISC-V processor).

• Autonomous Driving
• Machine Learning
• Wireless Communication
• +11 more

Dr. Tao (Kevin) Huang is a researcher at James Cook University's College of Science and Engineering, with expertise spanning autonomous driving, wireless communication systems, and medical imaging applications. His work integrates machine learning, sensor fusion, and multimodal data analysis to address complex challenges in vehicular networks, environmental monitoring, and healthcare technology. Research Interests: Dr. Huang's research focuses on Autonomous driving perception systems IoT-enabled vehicular networks AI for medical diagnostics and environmental sensing Signal processing and privacy-preserving communication protocols Recent Publications: His 2025 work emphasizes advancements in V2X cooperative perception, radar-LiDAR-camera fusion, and diffusion models for medical imaging. Key trends include cross-modal robustness, real-time processing for autonomous systems, and AI applications in sustainability.

Mikael EklundView profile

Professor

• Autonomous Systems
• Nonlinear System Identification and Control
• Health Informatics
• +3 more

Dr. Mikael Eklund is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, within the Faculty of Engineering and Applied Science. He holds a PhD (2003), MSc (1996), and BSc (1989) in Electrical and Computer Engineering from Queen’s University. His research focuses on Autonomous Systems , Nonlinear System Identification and Control , Health Informatics , and Pervasive and Mobile Computing . He has expertise in medical image processing, robotic vehicles, and smart sensors for assisted living. Education and Work Experience : - PhD (Electrical and Computer Engineering), Queen’s University (2003) - MSc and BSc from Queen’s University (1996, 1989) - Visiting Postdoctoral Scholar at UC Berkeley (2003–2006) - Adjunct Assistant Professor at Queen’s University (2003) - Former Teaching Fellow at Queen’s University (1996–2001) - Industrial experience in flight control system engineering (CAE Inc., 1989–1996) Research Contributions : - Developed SensorNet, a wireless infrastructure for assisted living. - Advanced methods for nonlinear system identification in chemical processes and aerospace systems. - Pioneered real-time UAV safety protocols and model predictive control algorithms for aerial pursuit-evasion games. - Explored EMG signal processing for hand force estimation and MEG signal source localization in neuroscience. Teaching and Outreach : - Teaches courses like Medical Image Processing and Electric Circuits. - Active in interdisciplinary projects like the ITALH initiative for elder tech integration. - Presented at conferences such as IEEE EMBC, ACC, and CDC, emphasizing healthcare IT and autonomous systems.

H.F. Machiel Van der LoosView profile

Associate Professor

• Rehabilitation Robotics
• Roboethics
• Design Methodology
• +3 more

H.F. Machiel Van der Loos is an Associate Professor and Associate Head – External at the Department of Mechanical Engineering, University of British Columbia. He holds a PhD from Stanford University (1992) in human-robot interaction and a Diplôme d'Ingénieur from École Polytechnique Fédérale de Lausanne (EPFL). As Director of the CARIS Lab, his research focuses on rehabilitation robotics, roboethics, design methodology, and human-robot interaction in industrial contexts. He has authored over 50 peer-reviewed journal articles and 100 conference papers, and serves as Associate Editor for the Journal of Assistive Technology . His teaching includes core design courses such as the Capstone Design Project and cross-disciplinary 'Designing for People' courses spanning Computer Science, Applied Science, and Library Science. Van der Loos organized major conferences including IEEE ICORR 2013 and ICED17 at UBC. His work includes developing assistive technologies like power-assisted wheelchairs, AR interfaces for human-robot collaboration, and rehabilitation robots. The CARIS Lab emphasizes ethical considerations in corporeal robotics and user-centered design principles. Current research projects involve multimodal robot programming through AR, gesture-based interaction, and adaptive wheelchair control systems. His lab has collaborated with industry partners like JDQ Systems Inc. and Tableau to advance practical robotics solutions.

Dimitrios ZekkosView profile

Professor

• Geotechnical Engineering
• Landslides
• Unmanned Aerial Vehicles (UAVs)
• +7 more

Dimitrios Zekkos is a Professor of Civil and Environmental Engineering at the University of California, Berkeley, and serves as Vice Chair for Strategic Planning and Implementation. He is also Founder and CEO of ARGO-E LLC, focusing on geotechnical and geoenvironmental solutions. Ph.D., University of California, Berkeley (2005) M.S., Geoengineering, University of California, Berkeley (2002) Joint B.S./M.Eng Degree, University of Patras, Greece (2001) Zekkos specializes in infrastructure resilience, landslide analysis, earthquake engineering, and UAV/satellite-enabled geohazard reconnaissance. His work combines experimental, computational, and autonomous systems to model earth material response to static/dynamic loads. His recent publications emphasize landslide inventory statistics, gravelly soil liquefaction, MSW landfill behavior, and erosion dynamics in mountainous regions. Key themes include remote sensing integration, machine learning applications, and 3D modeling of geohazards. Outstanding Innovator Award (ISSMGE, 2015) ASCE Arthur Casagrande Professional Development Award (2012) ASCE Collingwood Prize ASCE Middlebrooks Award Zekkos leads the Center for Land-Surface Hazards (CLaSH) and has secured EPA grants for landfill methane mitigation. His research spans geotechnical, geoenvironmental, and earthquake engineering domains with a focus on autonomy-enabled data acquisition.

Azadeh AnsariView profile

Associate Professor

• Nano/Micro-Electro-Mechanical Systems (N/MEMS)
• RF Applications
• Resonant Devices
• +3 more

Azadeh Ansari is an Associate Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology, holding the Sutterfield Family Early Career Professorship. She received her B.S. from Sharif University of Technology (2010), and M.S. and Ph.D. from the University of Michigan (2013, 2016), followed by a postdoctoral fellowship at Caltech (2016–2017). Her research focuses on nano/micro-electro-mechanical systems (N/MEMS), with emphasis on III-V semiconductors and piezoelectric materials. Key areas include resonant devices for RF applications, nonlinear devices, and integrated microsystems. Ansari leads projects in microscale robotics, phononic frequency combs, and III-V electro-acoustic devices. Research Interests: Resonant devices for timing, sensing, and RF applications III-V mm-wave acoustic filtering Microscale robot design and control Nonlinear resonators and phononic frequency combs III-V electro-acoustic devices and HEMTs Her recent work includes collaborations with NASA JPL on extraterrestrial micro-swimmers and DARPA-funded projects on inertial sensors and high-temperature pressure sensors. Ansari has secured grants from DARPA DSO and presented at IEEE Transducers 2025 with four papers. She advises graduate students such as Zhijian (Chris) Hao, who defended his PhD in 2024. Ansari’s awards include the 2017 ProQuest Distinguished Dissertation Award and the University of Michigan Towner Prize (2016). She serves on the IEEE Sensor’s Young Professional Committee and technical committees for IEEE IFCS 2018. Lab and Collaborations: The Ansari Lab is part of Georgia Tech’s Institute for Electronics and Nanotechnology. Collaborators include Prof. Kimberly Hoang (PBS-featured neurosurgery micro-drillers) and teams at Penn State University. Current projects include DARPA-funded frequency comb inertial sensors and underwater micro-robot sensor development for ICRA 2025.