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Yi ShengView profile

Associate Professor

• Molecular Biology
• Biochemistry
• Structural Biology
• +4 more

Yi Sheng is an Associate Professor in the Department of Biology at York University, Faculty of Science. He leads the Sheng Lab, focusing on understanding the ubiquitin-proteasome system (UPS) and its role in disease pathogenesis. His research explores protein ubiquitination dynamics and their implications in cancers, immune disorders, and neurodegenerative diseases. He is eligible to supervise graduate students in the Biology Graduate Program. Research Interests: Molecular mechanisms of protein ubiquitination UPS regulation in cellular processes (cell cycle, stress response) Development of novel therapeutic strategies targeting UPS dysfunction Lab Members: Current graduate students include Gabriella Gerzon (PhD), Daniel Martinho (MSc), and Angelo Vivona (MSc). Past students have contributed to projects on protein stability, signaling pathways, and disease models. Undergraduate researchers have explored topics like BIOL 4000 projects in molecular biology and biochemistry. Teaching: Teaches BIOL 3110 (Molecular Biology I), BIOL 1000C (Biology I), and BIOL 5028 (Graduate Molecular Biology). Focuses on nucleic acid metabolism, introductory biology concepts, and protein structure analysis workshops. Lab Location: Life Sciences Building, 327B Bench 2, York University, Toronto, Ontario.

• Environmental Robotics
• Robotic Vision
• Deep Learning
• +3 more

Dr. Dorian Tsai is a Research Fellow and Associate Investigator at the Queensland University of Technology (QUT) Centre for Robotics, affiliated with the School of Electrical Engineering & Robotics. His research focuses on environmental robotics, robotic vision, and deep learning applications for large-scale environmental challenges. He currently leads the Technology Development stream in the Reef Restoration and Adaptation Project (RRAP), developing robotic technologies for coral monitoring and endangered species tracking. Education: Bachelors in Engineering Science (University of Toronto), Masters in Space Science & Technology (Lulea Technical University), Robotics & Automation (Aalto University), and a PhD in Robotics from QUT. His doctoral work involved light field features for camera motion control, completed under supervisors Prof. Peter Corke, Dr. Donald Dansereau, and Dr. Thierry Peynot. Research emphasizes robotic solutions for marine conservation (e.g., Great Barrier Reef preservation), precision agriculture, and autonomous systems. His work combines machine learning, computer vision, and robotics engineering to address real-world environmental and industrial challenges. Prior to QUT, he worked at the Canadian Space Agency and completed thesis research at NASA's Jet Propulsion Lab on rover docking systems.

Maral AminpourView profile

Assistant Professor

• Computational Biology
• Drug Discovery
• Machine Learning Applications in Biomedical Engineering
• +7 more

Dr. Maral Aminpour is an Assistant Professor in the Department of Biomedical Engineering at the University of Alberta , where she leads a computational lab focused on drug discovery and biological systems modeling. Her research integrates artificial intelligence and physics-based methods to study protein-protein interactions, with particular emphasis on repurposing drugs for COVID-19 and optimizing anti-tubulin cancer therapeutics . Her lab develops hybrid AI-physics software tools to advance rational drug design and has contributed to understanding ivermectin's multi-target effects, Omicron's neurovirulence, and microtubule-targeting cancer drugs. Current projects include computational approaches to PROTACs design and antiparasitic drug discovery . Teaches graduate courses in Rational Drug Design (BME 620) and Machine Learning for Biomedical Applications (BME 677) Lab website: Aminpour Lab Active research areas: Computational drug discovery , AI in biomedical engineering , Protein interaction modeling

Ignacio Torroba BalmoriView profile

Researcher

• Underwater Robotics
• Simultaneous Localization and Mapping (SLAM)
• Autonomous Underwater Vehicles (AUVs)
• +3 more

Ignacio Torroba Balmori is a postdoctoral researcher at KTH Royal Institute of Technology, affiliated with the Department of Aerospace, Mobility and Naval Architecture and the Robotics, Perception and Learning (RPL) division. He holds a PhD from RPL under the supervision of John Folkesson, focusing on Simultaneous Localization and Mapping (SLAM) for autonomous underwater vehicles (AUVs). His current research emphasizes underwater SLAM with sonar and camera systems, path planning, control strategies, and system identification for AUVs operating in open waters and confined spaces. His work centers on applications such as autonomous seabed surveying, algae farm monitoring, and seaweed mapping. He is actively involved in developing the AUV SAM, Kongsberg Hugin, BlueROV2, USV FloatSAM, and the AUV Lolo. As a mentor, he has supervised master’s theses on topics including underwater SLAM algorithms and bathymetric informative path planning. He teaches courses like 'Introduction to Robotics' (assistant) and 'Underwater Technology' (teacher). Key technical contributions include system identification for hydrobatic AUVs using physics-informed machine learning and tools for bathymetric SLAM, such as the SubmapsRegistration repository. His research is hands-on, prioritizing field robotics and problem-driven solutions.

Ou MaView profile

Professor

• Space Robotics
• Machine Learning
• Autonomous Systems
• +3 more

Dr. Ou Ma is the Alan B. Shepard Chair Professor at the University of Cincinnati's College of Engineering and Applied Science (CEAS), Department of Aerospace Engineering. He leads the Intelligent Robotics and Autonomous Systems (IRAS) Lab, focusing on space robotics, autonomous systems, and machine learning. His academic career includes roles as John Nakayama Chair Professor (NMSU) and visiting positions at Tsinghua University and the German Aerospace Center (DLR). Education: B.Sc. (Zhejiang University), M.Eng. and Ph.D. (McGill University). Research interests span space robotics autonomy, multibody dynamics, human-robot interaction, and intelligent systems. Over 300 peer-reviewed publications and 20+ patents highlight contributions to robotics control, orbital mechanics, and biomedical applications. Notable grants include Air Force-funded projects on space servicing technologies, NASA initiatives for CubeSat systems, and Ohio Department of Higher Education robotics grants. Awards include the Distinguished Researcher Award (2024) and recognition for technical innovation in robotics simulation. Lab activities include developing autonomous lunar infrastructure systems (CableCat), CubeSat testbeds (HABSat), and robotics for on-orbit servicing. Collaborations span industry (Martian Sky Industries) and government agencies (AFRL, ONR).

Mohsen AlirezaeiView profile

Assistant Professor

• Automated Vehicles
• Cooperative Systems
• Control Systems
• +3 more

Mohsen Alirezaei is a part-time Assistant Professor at Eindhoven University of Technology's Mechanical Engineering department, specializing in vehicle dynamics and control. He concurrently serves as a Fellow Scientist at Siemens Industry Software and Services. His academic background includes a PhD in Mechanical Engineering (2011) from an unspecified institution, followed by a postdoc at Delft University of Technology (2012). Previously, he held roles as Senior Scientist at TNO Automotive (2012–2019) and part-time Assistant Professor at TU Delft (2015–2019). Research interests focus on automated and cooperative vehicles, including adaptive cruise control, collision avoidance, and state estimation. His work aligns with UN Sustainable Development Goals, emphasizing safer transportation systems. Key collaborations include studies on neural network-based behavior estimation during occlusion and criticality measures for automated vehicle testing. Education: PhD in Mechanical Engineering (Robotics & Control), 2011 Postdoc, Delft University of Technology, 2012 Awards: No explicitly stated scientific awards found. Grants/Advising: Supervised 8 works but no student names listed. Active in industry-academia collaborations via Siemens and TNO. Labs/Teams: Research involves Siemens' automotive software teams and TU/e's vehicle dynamics group.

Maria KingView profile

Associate Professor

• Bioaerosol Sampling
• Pathogen Tracking
• Airborne Pathogen Detection
• +3 more

Maria King is an Associate Professor at Texas A&M University with dual affiliation in the College of Agriculture & Life Sciences and College of Engineering. Her research focuses on bioaerosol science, pathogen detection technologies, and antimicrobial resistance mechanisms. King develops innovative methods for dynamic bioaerosol sampling and pathogen tracking, including wetted wall cyclones, airflow modeling, and autonomous biosamplers. Her expertise spans aerosol microbiology, antimicrobial resistance mechanisms, pathogen detection systems, and nanoparticle monitoring. Current projects include airborne pathogen surveillance, aerosolization stress responses, and microbial transmission in agricultural/industrial settings. Awards: Professor of the Year Teaching Excellence Award (2013-2014) Appreciation of Dedicated Service Award (2015)

Paal EngelstadView profile

Professor

• Machine Learning
• Wireless Communications
• Renewable Energy Systems
• +4 more

Paal Engelstad is a Professor at the University of Oslo, affiliated with the Section for Autonomous Systems and Sensor Technologies at the Institute of Transport Economics (ITS). He holds a full-time academic position. His research focuses on machine learning, wireless communications, renewable energy systems, and network security, with applications in IoT, reinforcement learning, and graph neural networks. His work addresses challenges in energy forecasting, autonomous systems, and secure information exchange. Key research interests include: Deep learning for solar and wind energy forecasting Graph neural networks and their applications in recommendation systems and network analysis Non-orthogonal multiple access (NOMA) in IoT and wireless networks Reinforcement learning for autonomous systems and control Security classification and anomaly detection in networks His recent publications highlight contributions to probabilistic solar irradiance forecasting, graph-based wind prediction models, and reinforcement learning algorithms for autonomous vehicles. He collaborates extensively with international researchers and has led projects like DESSI (Distributed Energy System and Security Infrastructure). Engelstad is involved in the following initiatives: Development of secure cross-domain information exchange frameworks Advances in energy-efficient IoT and sensor networks Applications of machine learning in cybersecurity and network optimization His research lab focuses on interdisciplinary solutions bridging transport economics, energy systems, and intelligent sensor technologies.

Qianwen LiView profile

Assistant Professor

• Intelligent Transportation Systems
• Vehicle Automation
• Traffic Safety and Efficiency
• +4 more

Dr. Qianwen (Cami) Li is an Assistant Professor in the School of Environmental, Civil, Agricultural and Mechanical Engineering (ECAM) at the University of Georgia. She leads the Cooperative Automated Mobility Innovations (CAMIs) Lab, focusing on enhancing transportation safety and efficiency through automation, vehicle communication, electrification, and smart infrastructure integration. Her work spans theoretical modeling, simulation tools, and real-world experimentation in connected and automated vehicle systems. Education details are not explicitly stated in the provided text, but her title indicates a doctoral degree. Her research emphasizes cutting-edge topics such as trajectory optimization for modular buses, safety-aware neural networks for AVs, and energy consumption analysis in transit systems. She has contributed to foundational studies on mixed traffic dynamics, pedestrian safety through roadway lighting, and policy frameworks for ACES (Automated, Connected, Electric, Shared) transportation systems. Dr. Li’s publications (15 most recent listed) highlight her expertise in CAV technologies, traffic modeling, and infrastructure integration. She has developed datasets for AV-traffic light interactions and pioneered methods to identify automated vehicles in mixed traffic using machine learning. Her work also addresses challenges like nighttime pedestrian crash modeling and optimal evacuation planning for electric vehicles. While no specific awards or grants are listed, her lab’s focus on cooperative automated mobility suggests active engagement in funded research projects. The CAMIs Lab collaborates on real-world applications, such as Florida’s ACES roadmap and trajectory control experiments for platooned vehicles.

• Robotics
• Mechanical Systems
• Aerospace Engineering
• +5 more

Laura Salamina is a Fixed-Term Assistant Professor at the Politecnico di Torino within the Department of Mechanical and Aerospace Engineering (DIMEAS) . Her work bridges robotics, mechanical design, and aerospace applications, with a focus on inflatable structures and human-robot collaboration. Research Groups: Mechatronics and Servosystems Teaching: Digital Twins for Mechanical Systems Prognostics, Product Components (Materials and Design) Her research explores robotics for planetary exploration , collaborative manipulation , and digital twin technologies . Recent work includes inflatable robotic arms for space debris removal, spherical planetary rovers, and safety frameworks for industrial robotics. Publications highlight interdisciplinary applications in aerospace, recycling, and energy systems. Key trends in her publications include: Inflatable deployable/retractable structures for aerospace Human-robot collaboration in industrial settings Digital twins for predictive maintenance and leak detection Gyroscopic control systems for planetary rovers Labs/Teams: Active member of the Mechatronics and Servosystems research group.

John P. WikswoView profile

Professor

• Biomagnetism
• Systems Biology
• Microfluidics
• +6 more

John P. Wikswo is the University Distinguished Professor at Vanderbilt University, holding appointments in Biomedical Engineering, Molecular Physiology & Biophysics, and Physics. He founded the Vanderbilt Institute for Integrative Biosystems Research and Education (VIIBRE) in 2001, which has become a leader in microfluidic organs-on-chips and systems biology tools. B.A. in Physics, University of Virginia (1970) M.S. and Ph.D. in Physics, Stanford University (1973, 1975) For 47 years, he has pioneered biomagnetic measurements in cardiology, including the first detection of magnetic fields from single axons and cardiac virtual electrode effects. His current work focuses on autonomous robot scientists like Genesis, integrating microfluidics with AI for yeast chemostat studies, and microphysiological systems for drug discovery and toxicology. His 250+ publications and 47 patents span biomedical instrumentation , microfabrication , and interdisciplinary education via the SyBBURE program, which has mentored over 400 students. Awards include the 2017 R&D 100 Award and fellowships in seven societies.

• Autonomous Ships
• Maritime Cybernetics
• Collision Avoidance
• +5 more

Morten Breivik is an Associate Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), and an affiliated researcher at NTNU's SFI Autoship. His work spans autonomous maritime technology, societal cybernetics, and coastal development initiatives. 2016-2024: Member of Teknologirådet 2013-2021: Former Head of Department (Instituttleder) at NTNU's Department of Engineering Cybernetics 2013-2023: Associated researcher at NTNU's SFF AMOS Breivik leads cutting-edge research in autonomous ship technology, including: World's first autonomous electric ferries for urban waterways (Zeabuz spin-off) Revitalizing Norwegian coastal regions through technology-driven solutions Developing Nyhavna 5.0 as a high-tech maritime cluster Founding the new discipline of Societal Cybernetics His work focuses on autonomous vessels with 15+ recent publications covering collision avoidance, trajectory planning, docking control, and human-machine teaming. The research integrates control systems, maritime autonomy, and urban transport optimization. Projects include: Autoteaming : Human-machine collaboration for autonomous ferry operations Kystutviklingssenter : Government-funded coastal development pilot in Kirkenes Nyhavna 5.0 : High-tech maritime cluster in Trondheim Societal Cybernetics : Modeling complex societal phenomena

Patrick Aloy CalafView profile

Research Professor

• Structural bioinformatics
• network biology
• network medicine
• +3 more

Dr. Patrick Aloy Calaf is an ICREA Research Professor and Principal Investigator at the Institute for Research in Biomedicine (IRB Barcelona) , leading the Structural Systems Biology lab. His academic journey includes a BSc in Biochemistry and an MSc in Biotechnology from the Autonomous University of Barcelona (UAB) , followed by a postdoctoral and staff scientist role at the European Molecular Biology Laboratory (EMBL) in Heidelberg, Germany. His research merges structural bioinformatics , network biology , and systems pharmacology to analyze macromolecular assemblies using 3D structures. He has pioneered Structural Systems Pharmacology , integrating chemical and structural data for drug development, and developed tools like 3did , IntSide , and NetAligner to model protein interactions and networks. Key research areas: 3D interactomes Peptide-mediated interactions Network medicine His 150+ publications in journals like Nature , Cell , and PLoS reflect broad impact, with over 17,500 citations. His work spans from yeast interactome modeling to human disease networks, emphasizing structural insights in biological complexity. The Structural Systems Biology lab under his leadership focuses on bridging computational models with experimental validation, advancing structural predictions for protein complexes and pathways.

Tsung-Chow SuView profile

Professor

• Fluid Mechanics
• Ocean Engineering
• Environmental Fluid Mechanics
• +9 more

Tsung-Chow (Joe) Su is a Professor in the Department of Ocean and Mechanical Engineering at Florida Atlantic University (FAU), located in Boca Raton, Florida. His research focuses on fluid mechanics, environmental engineering, and nanotechnology applications, with emphasis on fluid-structure interactions, piezoelectric shell vibrations, and energy-related systems. He has contributed extensively to the study of underwater robotics, scour protection for marine pipelines, and bioengineering solutions for pollutant capture. Education : Eng.Sc.D., Ocean Engineering, Columbia University (1974) M.S., Aeronautics, California Institute of Technology (1970) B.S., Civil Engineering, National Taiwan University (1968) Research Interests : Industrial and Environmental Fluid Mechanics Design Problems Involving Nanotechnology Fluid-Structure Interactions Piezoelectric Shell Vibrations Energy Systems and Undergraduate Research Recent Publications highlight advancements in underwater inflatable sonar arrays, scour mitigation for pipelines, and hybrid aerial-underwater robotic systems. His work bridges theoretical fluid dynamics with practical applications in marine infrastructure, pollution control, and autonomous systems. Teaching includes courses like Advanced Fluid Dynamics, Fluid Mechanics for Ocean Engineering, and Nanotechnology. Labs/Teams: His research involves collaborations in coastal engineering, robotics, and environmental fluid mechanics, though specific lab names are not explicitly stated in the provided texts.

• Cyber-Physical Systems
• Control Theory
• Secure-by-Construction Synthesis
• +3 more

Majid Zamani is an Associate Professor in the Computer Science Department at the University of Colorado Boulder, and a Guest Professor at Ludwig Maximilian University of Munich. He previously held an Assistant Professor position at the Technical University of Munich (2014–2019), leading the Hybrid Control Systems Group. His expertise spans verification and control of cyber-physical systems, secure-by-construction synthesis, and compositional analysis of interconnected systems. He holds a PhD in Electrical Engineering from UCLA (2012) and additional degrees from Sharif University of Technology and Isfahan University of Technology. Research Focus: Verification of safety properties, secure control synthesis, data-driven methods, and formal methods for stochastic systems. Notable contributions include barrier certificates, compositional verification, and abstraction-based control strategies. His work addresses challenges in autonomous systems, robotics, and safety-critical infrastructure. Major Awards: Recipient of the 2023 George S. Axelby Outstanding Paper Award, 2022 NSF Career Award, and ERC Starting/Proof-of-Concept Grants (2018/2023). Active in technical leadership roles, including serving on the IEEE CSS Technical Committee. Grants & Collaborations: Focused on NSF-funded projects exploring data-driven control and European initiatives in compositional system verification. His research bridges theoretical foundations with practical applications in robotics and autonomous systems.