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Aamir AhmadView profile

Professor

• Aerial Robotics
• Multi-Robot Systems
• Deep Learning
• +7 more

Aamir Ahmad is a Tenure-track Professor (Flugrobotik) and Deputy Director (Research) at the Institute of Flight Mechanics and Control, Faculty of Aerospace Engineering and Geodesy, University of Stuttgart. He also leads the Robot Perception Group (RPG) at the Max Planck Institute for Intelligent Systems in Tübingen. His research focuses on aerial robotics, multi-robot systems, deep reinforcement learning, formation control, and perception-driven navigation. He leads the Flight Robotics Group (FRG) and Robot Perception Group (RPG), which are part of the Cyber Valley and IMPRS-IS initiatives. His work includes developing autonomous aerial systems for tasks like motion capture, environmental monitoring, and cooperative target tracking. Key projects include AirCap (aerial human motion capture) and GRADE (generating dynamic environments for robotics). Research interests span reinforcement learning for autonomous systems, SLAM algorithms, and bio-inspired robotics. Notable contributions include autonomous multi-rotor landing on moving platforms, viewpoint-driven airship formations, and synthetic data-driven wildlife tracking. Ahmad has secured grants such as the EU H2020-funded DeepField project. He advises PhD students through the IMPRS-IS program and offers postdoc and research positions. His groups collaborate with institutions globally and engage in open-source software development for robotics.

Andreas KarrenbauerView profile

Research Fellow

• Combinatorial Optimization
• Algorithm Engineering
• Computational Interaction
• +3 more

Andreas Karrenbauer is a Senior Researcher in the Algorithms and Complexity department at the Max Planck Institute for Informatics, Saarbrücken (since 2013). He also serves as CEO of andaminika GmbH (since 2018). His research focuses on combinatorial optimization, algorithm engineering, and computational interaction, with applications in OLED displays, user interface design, and distributed systems. He holds a PhD from Saarland University (2007) and a Master's in Physics from Saarland University (2007). Key research interests include: Integer Programming, Combinatorial Optimization, Algorithm Engineering, and Computational Interaction. His work bridges theoretical computer science and practical applications, such as optimizing keyboard layouts (e.g., AZERTY redesign) and sensor systems. He has collaborated on projects like the European Laboratory for Learning and Intelligent Systems (ELLIS) and the Saarland Informatics Campus. Selected awards include a 2005 best paper award for 'Packing a Trunk - now with a Twist'. His research has been published in venues like Theoretical Computer Science , SIAM Journal on Computing , and Nature Communications . He advises on doctoral research and contributes to collaborative initiatives such as the International Max Planck Research School on Trustworthy Computing.

• Data Science
• Machine Learning
• Evolutionary Algorithms
• +4 more

Sibylle Sager-Müller is a Lecturer at the Lucerne School of Computer Science and Information Technology, part of Lucerne University of Applied Sciences and Arts (HSLU). She holds a Dipl.-Ing. in Mechanical Engineering from the University of Stuttgart and a Dr. sc. techn. from ETH Zürich, where she received the ETH Medal and ECCOMAS Prize. Her professional experience includes roles as a simulation engineer at Robert Bosch GmbH and as a Product Owner for Explainable AI projects in Powertrain Solutions. She has held visiting fellowships at Stanford University, California Institute of Technology, and NASA Ames Research Center. Education: Dipl.-Ing. Maschinenbau, Universität Stuttgart Dr. sc. techn. ETH Zürich (awarded ETH Medal & ECCOMAS Prize) Professional Experience: Simulationsingenieurin, Robert Bosch GmbH Product Owner for Explainable AI (AI in Powertrain Solutions), Bosch Visiting Fellowships: Stanford, Caltech, NASA Ames Her research focuses on data science , evolutionary algorithms , and optimization techniques , with applications in autonomous systems, fluid dynamics, and AI. Recent work emphasizes explainable AI (xAI) dashboards for computer vision and optimization of flow systems using stochastic and bio-inspired methods. Key projects include developing AI-assisted offering processes, analyzing transport company performance via geo-localized data, and studying customer behavior in e-bike sharing systems. Her publications span over two decades, with a strong emphasis on evolutionary strategies, machine learning, and their engineering applications. Awards: ETH Medal (ETH Zurich), ECCOMAS Prize, and recognition for contributions to computational methods in applied sciences. Advising & Grants: Extensive experience in project leadership across Bosch and academic collaborations, though specific grant details are not detailed in the provided text. She contributes to interdisciplinary teams in AI development and leads research on smart transportation systems and fluid dynamics optimization.

• Wave Energy Conversion
• Machine Learning Applications
• Structural Analysis
• +2 more

Masoud Masoumi serves as Adjunct Professor in Mechanical Engineering at the Albert Nerken School of Engineering, The Cooper Union. His research integrates mechanical engineering principles with machine learning applications, focusing on renewable energy systems, structural analysis, and wave propagation phenomena. Key research domains include: Machine learning applications for wave energy conversion and offshore wind farms Computational modeling of ultrasonic wave propagation in structures Stress prediction in mechanical components using convolutional neural networks Fluid dynamics in biomass energy systems Development of wave energy converters for marine applications Masoumi's extensive publication record demonstrates consistent innovation in applying computational methods to renewable energy challenges, particularly in optimizing wave energy systems and developing predictive maintenance frameworks for offshore infrastructure. Recent work emphasizes data-driven approaches for ocean energy harvesting and structural health monitoring.

Brendan HarmonView profile

Associate Professor

• Computational Design
• Spatial Science
• Robotics
• +5 more

Brendan Harmon is an Associate Professor and Emerson Womack Professor in the Department of Landscape Architecture at Louisiana State University's College of Art & Design. He holds graduate degrees from Harvard Graduate School of Design, University of Oxford, and North Carolina State University. His research integrates spatial science, computational design, and robotics to explore ecological-technological interfaces. Research interests include robotic landscape processes, point cloud modeling for heritage conservation, climate resilience, erosion modeling, and geospatial analytics. His work advances open science and education for equitable knowledge access, including a 3D scanned heritage landscape repository. Recent publications focus on computational design innovations (2020-2025), with trends in sustainable technology, digital heritage, ecological robotics, and environmental simulation. Awards include the Emerson Womack Professorship for distinguished contributions to landscape architecture. He leads projects in computational ecology and maintains active collaborations in geospatial technology. No advising or grant details were provided in the source material.

John Howard LongView profile

Professor

• Biomechanics
• Evolutionary Robotics
• Vertebrate Physiology
• +1 more

John Howard Long is Professor of Biology and Cognitive Science at Vassar College, holding the John Guy Vassar Chair. His interdisciplinary research combines biomechanics, robotics, and evolutionary biology to study vertebrate locomotion. Collaborating with institutions like Duke University and Shriners Hospital, he employs robotics and physics-based simulations to reconstruct early vertebrate evolution. His work has been funded by the National Science Foundation and Office of Naval Research, with undergraduates contributing significantly to international publications and presentations. Author of 'Darwin’s Devices: What Evolving Robots Can Teach Us About the History of Life' Created Great Courses lecture series on Robotics

• Evolutionary Algorithms
• Genetic Programming
• Semantic-Based Genetic Programming
• +7 more

Dr. Edgar Galván is an Associate Professor in the Department of Computer Science at Maynooth University, Faculty of Science & Engineering. He holds a PhD in Computer Science from the University of Essex and has held senior research roles at institutions like University College Dublin and Trinity College Dublin. His research focuses on Evolutionary Algorithms, Genetic Programming, and their applications in optimization, games, and circular economy challenges. Education : PhD in Computer Science, University of Essex MSc (Hons) in Artificial Intelligence (Research), University of Veracruz BSc (Hons) in Computer Science, University of Veracruz Research Interests : Dr. Galván pioneers work in semantic-based Genetic Programming, neutrality and locality in evolutionary algorithms, and applications in combinatorial optimization and energy systems. He also explores AI-driven solutions for the circular economy, including material reuse and policy design. Grants & Projects : REBUILD (€449,879): Reimagining buildings as material banks for the circular economy (2024–2027) VISION (€149,874): Circular business models to reduce virgin material use in construction (2023–2026) Stochastic Bio-inspired Evolutionary Algorithms (€267,000): Dynamic optimization problems (2014–2017) Awards : Top 1% of researchers in Genetic Programming (UCL, 2020) Elected member of Mexico’s National Research System (2015) Marie Curie Fellowship (Irish Research Council, 2014) Professional Activities : Chair of ACM Genetic and Evolutionary Computation Conference committees, Programme Committee member for IEEE Congress on Evolutionary Computation, and Scientific Adviser for research councils in Ireland, France, and Mexico.

• Bio-inspired artificial intelligence
• Genetic programming
• Neural networks
• +3 more

Dennis Wilson is an Assistant Professor in AI and Data Science at ISAE-SUPAERO. He holds roles as co-organizer of the Supaero Reinforcement Learning Initiative (SuReLi) and head of the Data & Decision Sciences Master’s program. He is part of the Decision Systems research group within the Department of Complex Systems Engineering. Education: PhD from Institut de Recherche en Informatique de Toulouse (IRIT) on artificial neural network design principles Prior work in the Anyscale Learning For All group at MIT’s CSAIL, focusing on wind farm optimization using evolutionary strategies Research interests include bio-inspired AI, genetic algorithms, neural networks, and evolutionary approaches to machine learning. His work bridges theoretical foundations with applied problems in complex system optimization. Grants and advising: No specific grants mentioned, but actively involved in curriculum leadership and research coordination through SuReLi and DISC groups. Labs/Teams: Member of the Decision Systems group and co-leads the SuReLi initiative.

Francesca TroianiView profile

Researcher

• Neural Engineering
• Optical Coherence Tomography (OCT)
• Computational Neuroscience
• +3 more

Francesca Troiani is a Researcher at Imperial College London's Department of Electrical and Electronic Engineering within the Faculty of Engineering. She holds an Honorary Research Associate position in the Next Generation Neural Interfaces (NGNI) group at the Centre for Bio-inspired Technology. Her academic journey includes a BSc and MSc in Physics from the University of Trieste (2008-2013), followed by a PhD at Imperial College London (2014-2018). Her research focuses on developing optical methods for neural interface applications, particularly using time-domain optical coherence tomography (OCT) for compound action potential recording. She has contributed to computational neuroscience studies on grid cells and spatial representations in hyperbolic surfaces during postgraduate work at SISSA. Francesca is also actively involved in public engagement, leading STEM activities at the Wohl Reach Out Lab and coordinating exhibits at events like the Royal Society Summer Science Exhibition. She manages NGNI lab outreach initiatives including the Great Exhibition Road Festival participation and art-science collaborations.

• Bioinformatics
• Cryptography
• Genetic Algorithms
• +5 more

Mohammad Nassef is an academic researcher with a focus on interdisciplinary applications combining computer science, bioinformatics, and cryptography. His work spans multiple domains, including Developing bio-inspired algorithms for audio and image encryption Optimization techniques in genetic data analysis Automated scoring systems in educational software Edge detection methods for biomedical imaging Research Trends: His publications highlight a consistent integration of biological sequence modeling into computational algorithms, with recent work emphasizing cybersecurity, data compression, and machine learning applications in genetics. Collaborations with researchers like Ibrahim Farag, Amr Badr, and Monagi H. Alkinani indicate a networked approach to solving complex problems in data security and medical informatics.

• Materials engineering
• Nanophotonics
• Plasmonics
• +5 more

Dr. Muhammad Alam is an Assistant Professor in the Department of Electrical and Computer Engineering at Queen's University, Canada. He holds a PhD in Photonics (University of Toronto, 2012), MASc in Electromagnetics (University of Victoria, 2003), and BSc in Electrical Engineering (Bangladesh University of Engineering and Technology, 2000). His research focuses on advancing nanophotonics, plasmonics, and metasurface technologies for applications in energy, sensing, and optical systems. Education: PhD in Photonics, University of Toronto (2012) MASc in Electromagnetics, University of Victoria (2003) BSc in Electrical Engineering, Bangladesh University of Engineering and Technology (2000) Research Interests: His lab explores transformative nanophotonics applications, including plasmonic sensors, metasurface-based optical systems, and energy-efficient photonic devices. Key areas include solar azimuth prediction using bio-inspired polarization techniques, low-cost transparent solar absorbers, and quantum-optics metasurface arrays. Awards: Douglas R. Colton Medal for Research Excellence (2020) Over 371 citations (Google Scholar, 2023) Supervision and Grants: Current advisee: Dr. Zohreh Vafapour (Postdoctoral Fellow). His work has been supported by collaborations with institutions like NASA's Jet Propulsion Laboratory and Lawrence Berkeley National Laboratory. Labs/Teams: Research activities are conducted in Queen's Walter Light Hall labs, with affiliations to advanced photonics facilities. Ongoing projects bridge material science, optics, and engineering for real-world applications.

Joni DambreView profile

Professor

• Machine Learning
• Deep Learning
• Embedded AI
• +5 more

Joni Dambre is a full-time tenured Professor at Ghent University leading the AIRO research group within the Internet Technology and Data Science Lab (IDLab). She transitioned from digital hardware research to machine learning in 2008 after earning her MSc and PhD in Electrical and Computer Science Engineering from Ghent University. Her educational background includes: MSc in Electrical Engineering from Ghent University PhD in Computer Science Engineering from Ghent University Professor Dambre's research spans machine learning, deep learning, embedded AI implementations, robotics, and brain-inspired unconventional computing. Her work uniquely bridges theoretical foundations with practical applications, evidenced by her team's competitive success in Kaggle competitions. Key thrusts include photonic reservoir computing, sign language technology development, and human-AI interaction studies, with emphasis on both hardware-efficient implementations and societal impacts. Recent publications (2023-2025) reveal strong interdisciplinary convergence, merging machine learning with photonics for unconventional computing architectures while advancing sign language translation through projects like SignON. A notable trend involves expanding from technical implementations to human-centric AI research, including studies on human alignment with large language models and societal implications of AI deployment. No major scientific awards were mentioned in the provided text. Although specific student names were not listed, Professor Dambre leads the AIRO group and serves as principal investigator for significant projects including SignON and cREAtIve, indicating active research supervision and substantial grant funding from both academic and industry sources. The AIRO research group maintains a dual focus on foundational theory and real-world applications, with active projects spanning photonic neural networks for telecommunications, sign language recognition systems, and robotics platforms. Their work demonstrates consistent innovation in translating brain-inspired computing concepts into practical solutions while maintaining strong industry partnerships and competitive performance in applied machine learning challenges.

• Planarian Regeneration
• Animal Behavior
• Biomimicry Engineering
• +3 more

Steffen Werner is an Assistant Professor in the Department of Experimental Zoology at Wageningen University. His research focuses on regeneration biology in planarians, animal behavior in insects (e.g., bumblebees), and biomimetic engineering principles. He collaborates on projects involving biomechanics, sensory-motor control, and robotics. His work bridges disciplines like developmental biology, entomology, and civil engineering. Education & Affiliations : PhD (Dr.rer.nat.) in Zoology Affiliated with the Wageningen Institute of Animal Sciences (WIAS) Research Interests : Planarian regeneration mechanisms and Wnt signaling pathways Insect locomotion and landing dynamics on moving surfaces Biomimetic design for sustainable construction materials Physiological scaling in flatworms and energy storage strategies Recent Projects : Co-promotor of a PhD project on Flight control and maneuverability of Dipteran insects (2023–present). Active in interdisciplinary collaborations, including bio-inspired robotics and biomimicry applications. Keynote Talks : Delivered talks on topics such as intraspecies allometries in planarians, phase transitions in RNAseq data, and physics-inspired models in biology (2023–2024).

Michael Adam LonesView profile

Professor

• Artificial Intelligence
• Machine Learning
• Optimization
• +3 more

Michael Adam Lones is a Professor in the Department of Computer Science at Heriot-Watt University's School of Mathematical & Computer Sciences and a member of the Edinburgh Centre for Robotics. With over 25 years of AI expertise spanning machine learning, optimization, and bio-inspired computing, his research focuses on AI dependability, robustness, and medical applications including Parkinson's disease management tools. Education: MEng, University of York (1999) PhD, University of York (2003) His research program centers on designing reliable AI systems through understanding limitations and improving practices, with significant clinical translation work in neurology. He actively disseminates knowledge via academic talks and his Substack publication Fetch Decode Execute, emphasizing practical AI implementation frameworks. Recent publications (2023-2025) demonstrate concentrated efforts in cybersecurity robustness, IoT threat detection, and educational AI applications, with recurring themes of model generalization challenges and adversarial resilience across domains. Scientific Awards: Best Paper Award (2025) Humies Gold Award (2018) Professor Lones supervises PhD students and contributes to UN Sustainable Development Goals through health-focused AI research. His extensive publication record (70+ outputs) and dataset development indicate substantial ongoing research activity despite specific grant details not being publicly enumerated. He maintains active collaboration through the Edinburgh Centre for Robotics and has co-developed significant datasets including Parkinson's disease clinical tools and Android malware detection resources, reflecting his interdisciplinary approach to real-world AI challenges.

Payam Nori ZadehView profile

Research Fellow

• Robotics
• Mobile Robot Navigation
• Computer Vision
• +3 more

Dr. Payam Nori Zadeh is a Research Fellow in AI and Robotics at the Queensland University of Technology (QUT) Centre for Robotics, a position he has held since May 2023. He actively collaborates on the pioneering Australia-USA joint project (AUSMURI) with institutions including MIT, Boston University, UNSW, and the University of Melbourne. Education: PhD in Computer Science from Victoria University of Wellington (2023), focusing on mobile robot navigation in outdoor terrains with slip and skid. Master’s in Robotics and Control from the University of Tehran, with thesis research on cooperative control of multiple mobile robots in cluttered environments. Dr. Nori Zadeh's research specializes in autonomous mobile robotics for challenging environments, integrating bio-inspired navigation strategies with advanced computer vision techniques for high-speed event cameras. His work addresses critical gaps in terrain adaptability and real-time perception: Mobile Robot Navigation under extreme slip/skid conditions in unstructured outdoor settings Computer Vision algorithms optimized for neuromorphic event cameras Bio-inspired control systems mimicking biological locomotion Cooperative multi-robot coordination in complex obstacle fields No public information is available regarding Dr. Nori Zadeh's student advising or grant funding activities. As a core contributor to the QUT Centre for Robotics, he operates within the AUSMURI project framework, leveraging international partnerships to advance autonomous systems research. Connect with Payam on his Scholar and LinkedIn profiles for further details about his research.