Find Academic Supervisors

Marco DorigoView profile

Professor

• Swarm Intelligence
• Artificial Intelligence
• Robotics
• +3 more

Marco Dorigo is a Full Professor (part-time) at the Department of Computer Science, Faculty of Electrical Engineering, Computer Science and Mathematics, University of Paderborn since 2011. He is also a Research Director (Directeur de Recherches) at the IRIDIA laboratory, Universite Libre de Bruxelles since 2004. His academic career includes various research roles at institutions such as IDSIA in Switzerland and postdoctoral positions at ULB. His research focuses on Swarm Intelligence, Artificial Intelligence, and Robotics, with particular emphasis on optimization algorithms inspired by natural systems, such as Ant Colony Optimization. He has contributed significantly to the development of swarm robotics and self-organizing systems. Notable awards include the ERC Advanced Grant (2010), Cajastur International Prize for Soft Computing (2007), and the Prix Wernaers 2012 for the "Swarmanoid, The Movie" . He is a member of multiple prestigious organizations, including Academia Europaea and the IEEE. He has supervised over 12 PhD students and 40 MSc students. His research has been supported by grants such as the ERC Advanced Grant, and he has contributed to projects like the Swarm-Bot robotics system. He leads research at the IRIDIA laboratory, focusing on swarm intelligence, and has been involved in initiatives like the Swarm-Bots project, exploring self-organized robot colonies.

• Fish Locomotion
• Functional Morphology
• Bioinspired Robotics
• +5 more

Brooke Flammang is an Associate Professor in the Department of Biological Sciences at the New Jersey Institute of Technology (NJIT) . Her research focuses on the functional morphology and biomechanics of aquatic organisms, with an emphasis on fish locomotion, bioinspired robotics, and evolutionary adaptations. She leads federally funded projects including NSF grants on remora adhesion systems, flying fish robotics, and endangered marine organism telemetry. Key areas of expertise include: Biomechanics of swimming and flying fish Adhesive mechanisms in remoras Bioinspired robotic designs Evolutionary functional morphology Recent work involves developing amphibious energy harvesting systems and studying the hydrodynamics of flying fish models. She has published extensively on topics ranging from shark denticle orientation to robotic fish tail design, with over 45 peer-reviewed articles and significant media coverage for her innovative conservation-focused projects. Notable collaborations include: BRC-BIO Grant (2025-2028) : Duck foot morphology and swimming ability NSF BioDesign Grant (2024-2027) : Remora-inspired telemetry devices FELS RAISE Grant (2019-2025) : Evolution of terrestrial locomotion models

• Smart Materials
• Soft Robotics
• Architecture
• +7 more

Martina Decker is an Associate Professor at the School of Art and Design at New Jersey Institute of Technology (NJIT), and formerly affiliated with the Hillier College of Architecture and Design. Her research focuses on smart materials, soft robotics, and adaptive design in architecture, emphasizing the integration of emerging technologies with sustainable building practices. She explores programmable matter, bio-inspired façade systems, and intellectual property challenges in architectural innovation. Her work bridges disciplines such as materials science, robotics, and environmental engineering, aiming to create climate-responsive and resilient architectural solutions. Notable contributions include studies on climate-adaptive building systems and the application of dielectric viscoelastomers in electromechanical systems. Media highlights include coverage of her collaboration on robotic design education and her exploration of climate resilience in architecture. Her research trends emphasize interdisciplinary approaches, blending computational methods with physical materials for adaptive structures and human-centric interfaces. Decker’s projects often involve cross-disciplinary teams, as seen in her work with collaborators like Anna Zarzycki and Gabor Hahn. No specific lab or team affiliation is explicitly mentioned in available texts.

• Experimental Aerodynamics
• High-speed Flow Measurements
• Active Flow Control
• +6 more

Dr Marco Debiasi is Research Fellow in Experimental Aerodynamics at Cranfield University’s Centre for Defence Engineering & Physical Science, UK. After graduating from the University of Padova, he earned an MS (1998) and PhD (2000) in Mechanical & Aerospace Engineering from University of California, Irvine. He subsequently led experimental programmes at Ohio State University, National University of Singapore (Head, Experimental AeroScience Group 2009-2017) and, since 2018, Cranfield University. Education PhD Mechanical & Aerospace Engineering, University of California, Irvine (2000) MS Mechanical & Aerospace Engineering, University of California, Irvine (1998) Degree (structural integrity/fatigue), University of Padova Research Interests Dr Debiasi’s activities centre on experimental aerodynamics and flow control . Current themes include high-speed flow measurements, advanced sensors & actuators for active control, morphing aerodynamic surfaces, and aero-acoustic noise mitigation. His prior work spans micro air vehicle design, swept grid-fin development, plasma-based flow control, cavity-flow aeroacoustics and jet-noise reduction. Publication Trends Across more than 60 refereed works since 1998, a clear evolution is evident: early studies on supersonic-jet noise and cavity flows (1998-2006) transitioned to morphing-wing MAV technologies and smart-material actuators (2007-2017), followed by recent high-speed exhaust and installation-effect investigations (2018-present). The corpus integrates experimental fluid dynamics with emerging AI-driven data analysis, reflecting continuous adaptation to contemporary aerospace challenges. Current Supervision & Funding Dr Debiasi presently supervises PhD and MSc researchers at Cranfield University. Recent projects are supported by Reaction Engines Ltd., Rolls-Royce Plc and the Cranfield Air & Space Propulsion Institute (CASPI). Laboratory & Team He conducts experiments within the Aeromechanical Systems Group laboratories, leveraging Cranfield’s national-level wind-tunnel and high-speed flow facilities for defence and aerospace applications.

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.