Alice C Helliwell is an Assistant Professor in Philosophy at Northeastern University London, specializing in AI art and computational creativity. Her research addresses philosophical questions about machine creativity, AI ethics, and the aesthetics of AI-generated art. She holds a PhD from the University of Kent and has held roles including Interim Director of the Doctoral Research School at NU London (2023-24). Her current projects include a Visiting Fellowship at Friedrich-Alexander-Universität exploring AI responsibility frameworks. Education includes: PhD in History and Philosophy of Art (University of Kent) MA in History and Philosophy of Art (University of Kent, Paris) PGCert in Occupational Psychology (Birkbeck, University of London) MA(Hons) in Philosophy and Psychology (University of Edinburgh) Her research spans: Philosophy of technology Creativity theory Applied AI ethics Landscape of AI ethics in creative industries Recent publications focus on AI alignment problems, cluster accounts of art, and Wittgensteinian analyses of AI governance. She co-edited volumes on Wittgenstein and AI (2024) and authored key works linking Darwinian creativity models to computational systems. Awards include the Paris Scholarship and Vice Chancellor’s Scholarship. Professional roles include Associate Editor at AI & Society (2024–present) and Trustee of the British Society of Aesthetics. Teaching focuses on AI/data ethics and aesthetics at NU London, with supervision of dissertations in AI art, technology ethics, and aesthetics. She holds Fellowship of Advance HE (2024).
Associate Professor Vic Ciesielski is affiliated with RMIT University's School of Computing Technologies. His research focuses on Artificial Intelligence, Evolutionary Computing, Computer Vision, and Genetic Programming, with applications in areas like robot soccer and aesthetic analysis of images. He has supervised projects including efficient neural architecture search and off-line handwritten text recognition. His work bridges computational techniques with creative fields such as art history and digital media. Key research interests include machine learning, data management, and graphics/augmented reality. He actively contributes to conferences like GECCO and IJCNN, publishing on topics ranging from neural architecture optimization to sensor-based activity recognition. His research often integrates evolutionary algorithms with deep learning methodologies. He can be contacted via vic.ciesielski@rmit.edu.au and has an ORCID identifier: 0000-0001-7273-9566 .
George V. Lauder is the Henry Bryant Bigelow Professor of Ichthyology at Harvard University, affiliated with the Museum of Comparative Zoology (MCZ) and designated as a Harvard College Professor. He is currently on leave for Spring 2025 and not accepting graduate students for the 2025-2026 academic year. His research focuses on biorobotics, the biomechanics of vertebrate movement (particularly fishes), and evolutionary morphology. Key areas include robotic models of fish locomotion, quantitative flow visualization of shark and ray-finned fish dynamics, and the fluid mechanics of aquatic movement. Education: Not explicitly listed in the provided text. His work bridges biology and engineering, emphasizing interdisciplinary approaches such as robotics to explore ecological and evolutionary questions. Recent studies highlight biomimetic shark skin analysis, tuneable stiffness in robotic fish, and the functional morphology of dermal denticles. Collaborations span fluid dynamics, material science, and theoretical biology. Publications emphasize robotics as a comparative tool, biomimetic design, and the integration of experimental and computational methods. While no awards are explicitly listed, his roles as MCZ Curator and Harvard College Professor reflect institutional recognition. Advising is paused temporarily, but his lab (Lauder Lab) continues research on fish locomotion, robotics, and biological fluid mechanics. The lab is located at 26 Oxford Street, Cambridge, MA, under MCZ facilities.
Nicolas Cambier is a Visiting Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Science's Artificial Intelligence department and the Network Institute. His research focuses on swarm robotics, collective behavior, and evolutionary systems. He explores topics like emergent communication, modular robotics, and prosociality in robotic swarms. Key areas include task-driven language evolution, adaptive decision-making, and environmental interaction in constrained environments. His work bridges theoretical models with practical implementations, emphasizing self-organization and cultural evolution in synthetic systems. Recent contributions address challenges in heterogeneous swarms, skill acquisition in modular robots, and decision-making without prior knowledge. He collaborates widely, with publications in IEEE Robotics and Automation Letters, Nature Communications, and top conferences like GECCO and Distributed Autonomous Robotic Systems. Research interests span robotics, artificial intelligence, and evolutionary computation, with applications to both theoretical frameworks and real-world robotic systems. His studies often involve agent-based simulations and embodied evolution approaches to understand complex collective phenomena.
Greg Bryant is a Professor and Chair in the Department of Communication at the University of California, Los Angeles (UCLA). His research focuses on cognitive science, vocal communication, and social behavior, integrating acoustic analyses, perception experiments, and cross-cultural field studies. Key research areas include evolutionary psychology, nonverbal communication, verbal irony, music perception, and infant-directed speech. His recent publications explore volitional laughter, vocal features in social judgments, and the cultural evolution of music. Media coverage of his work highlights topics such as animal laughter, affiliation detection in colaughter, real vs. fake laughter perception, and vocal changes during ovulation. He teaches courses like the Evolution of Interpersonal Communication and Communication Theory.
Dr. Danesh Tarapore is an Associate Professor at the University of Southampton specializing in robotics and AI. He focuses on human-robot interaction, swarm intelligence, and autonomous systems. His current research involves developing resilient robotic teams and optimizing learning algorithms for constrained environments. He supervises 6 PhD students in the iPhD MINDS and Computer Science programs. Dr. Tarapore's work bridges theoretical advancements with practical applications in autonomous navigation, multimodal dataset creation, and quality-diversity optimization. His publications span conferences like HRI and journals in robotics and AI. He collaborates with institutions like the University Hospital Southampton and the Boldrewood Innovation Campus. Research Interests: Human-robot collaboration, swarm systems, machine learning, and adaptive control Key Contributions: HRI-SENSE dataset, evolutionary subset selection algorithms, forest navigation frameworks Grants and Funding: Active projects in multi-agent systems and resilient robotics Dr. Tarapore maintains active roles in the robotics community through conference participation and interdisciplinary collaborations.
Pawel Ladosz is a Lecturer in Engineering Systems for Robotics at the Department of Mechanical and Aerospace Engineering, The University of Manchester. His research focuses on applying machine learning and computer vision to mobile robots, particularly in extreme environments such as total darkness or cluttered spaces. He is actively involved in developing autonomous navigation systems, wireless signal mapping, and high-level decision-making for robotic swarms. He teaches courses including Robotic Systems Design Project and Autonomous Mobile Robots. Education: PhD in Establishing and Optimising Unmanned Airborne Relay Networks (Loughborough University, 2014–2019) MEng in Aerospace Engineering (The University of Manchester, 2010–2014) Research Interests: Ladosz’s work emphasizes reinforcement learning for robotics, vision-based autonomous systems, and exploration in challenging environments. His projects often intersect with UN Sustainable Development Goals, contributing to innovations in robotic autonomy and sensor networks. Awards: He received the 2nd Autonomous Flying Technology Competition award in 2021, recognizing his contributions to autonomous flight systems. His research has also led to the establishment of the Centre for Robotic Autonomy in Demanding and Long-Lasting Environments (CRADLE), fostering cross-disciplinary collaborations. Grants & Projects: As Principal Investigator in the Aerospace Engineering initiative (2010–2035), he explores UAV communication networks and trajectory planning. His work addresses urban environment challenges, including relay positioning and signal prediction. Labs/Teams: Ladosz contributes to CRADLE, advancing robotic autonomy in extreme scenarios. His lab focuses on integrating AI and robotics for real-world applications.
Assoc. Prof. Dr. Ayhan Gün is an Associate Professor in the Department of Electrical and Electronics Engineering at Kütahya Dumlupınar University's Faculty of Engineering. With a career spanning over two decades, he has held various academic positions including Research Assistant, Assistant Professor, and currently Associate Professor since 2024. His extensive administrative experience includes serving as Head of the Control and Command Systems Department (2007-2021) and various leadership roles in university-industry collaboration initiatives. Dr. Gün completed his Bachelor's degree at Near East University (1991-1996), Master's at Dumlupınar University (1998-2001), and PhD at Eskişehir Osmangazi University (2001-2007). His research focuses on control systems, mathematical modeling, artificial neural networks, robotics, SCADA, PLC programming, electromechanical systems, nonlinear control, fuzzy logic, optimization techniques, automation, biomechanics, and mechatronics. His recent publications demonstrate a consistent research trajectory in control engineering, with particular emphasis on optimization algorithms applied to quadrotor control, inverted pendulum systems, and electrical motor design. His work bridges theoretical control concepts with practical implementations in robotics and power systems. A significant portion of his research involves applying swarm intelligence and evolutionary algorithms to solve complex control problems. Bilim, Sanayi ve Teknoloji Bakanlığı Kurumsal Kapasitenin Arttırılması (2016) BİLİM SANAYİ VE TEKNOLOJİ BAKANLIĞI Çift Beslemeli İndüksiyon Generatörü Tasarımı ve İmalatı (2016) Dr. Gün has supervised multiple graduate students and managed numerous research projects, including the current 'Robotic Arm Design and Implementation for Patients with Hemiparetic Arms' project. His external roles include serving as an expert witness for judicial institutions, project referee for TÜBİTAK, and publication reviewer for IEEE Transactions. He has also contributed to regional development through his work with Kütahya Governorship's Planning and Development Board.
Burak Kurkcu is an Assistant Professor in the Department of Electrical and Computer Engineering at Santa Clara University's School of Engineering. He previously served as an Assistant Professor at Hacettepe University and as a Senior Control System Design Engineer at Aselsan Inc. Education: Ph.D., TOBB University of Economics and Technology (2019) M.S., TOBB University of Economics and Technology (2015) B.S., Istanbul Technical University (2010) Research Interests: Dr. Kurkcu specializes in robust control systems, soft robotics, switched neural networks, and autonomous systems. His work focuses on disturbance estimation, simultaneous learning algorithms, and control of nonlinear systems. Recent Publication Trends: His research includes soft pneumatic actuator modeling, disturbance observer-based control methods, and evolutionary optimization for state-space models. Key themes involve soft robotics, autonomous control, and computational intelligence applications. Scientific Awards: IEEE Turkey Ph.D. Thesis Award (2020) Editorial Roles: Associate Editor for TIMC, Measurement and Control , and Turkish Journal of Electrical Engineering and Computer Science . Principal Investigator for defense-related control system projects.
Maria Leonilde Rocha Varela is an Associate Professor with Habilitation at the School of Engineering, University of Minho, Portugal, where she also serves as a Senior Researcher at the Algoritmi Research Centre. She has been an integrated member of the Algoritmi Research Centre since 2012 and works in the Department of Production and Systems. Dr. Varela earned her degree in Production Engineering from the University of Minho in 1994, completed a Master's in Computer Integrated Production at DPS-UMinho in 1999, and received her Ph.D. in Production and Systems from the University of Minho in 2007. Her primary research focuses on Manufacturing Management, particularly Production Planning, Control and Optimization, and Collaborative Paradigms, Networks and Decision Making Models. She maintains extensive international collaborations with institutions worldwide including the National Institute of Industrial Engineering, VSB-Technick Univerzita Ostrava, University of Belgrade, and others. Her research spans Web Applications and Services for supporting Engineering and Production Management, with increasing emphasis on Artificial Intelligence, Robotic Process Automation, and Industry 4.0/5.0 applications. She has made significant contributions to scheduling algorithms, optimization techniques, and decision support systems for manufacturing environments. Analysis of her recent publications reveals a strong trend toward integrating Artificial Intelligence with traditional manufacturing processes, particularly in Robotic Process Automation applications. Her research increasingly focuses on sustainable manufacturing practices, with numerous publications addressing energy efficiency, environmental sustainability, and resource optimization. There is a clear emphasis on multi-objective optimization approaches to solve complex manufacturing problems, particularly in distributed job shop scheduling. Her work demonstrates an evolution from traditional production planning methods to more advanced AI-driven approaches for Industry 4.0 and 5.0 environments. Dr. Varela has held significant academic leadership roles, currently serving as the director of the master's course in Engineering and Quality Management at DPS-UMinho. She previously coordinated the industrial management and systems subgroup from 2012 to 2021 and was part of the steering committee for the master's course in systems engineering between 2016 and 2019. She has successfully supervised more than 70 MSc projects, with over 15 currently ongoing, focusing on Production and Systems Engineering. Her supervision encompasses collaborative management models, traditional decision approaches, and web-based platforms incorporating AI techniques. She coordinates research projects including 2 concluded Ph.D. projects and 6 ongoing ones. She collaborates as a research member in several R&D projects with national and international industrial enterprises and institutions, and in international Erasmus projects. Dr. Varela is an active participant in the academic community, serving on editorial boards of several international journals and as a member of organizing and scientific committees for numerous international conferences. She is a member of several prestigious research networks including the Euro Working Group of Decision Support Systems (EWG-DSS), Institute of Electrical and Electronics Engineers (IEEE), Industrial Engineering Network, and the Institute of Industrial and Systems Engineers (IISE).
Prof. Dr. J. Ellers is a Full Professor at the Faculty of Science, Vrije Universiteit Amsterdam , and a member of the Amsterdam Institute for Life and Environment . His research focuses on understanding how an individual’s phenotype is shaped by interactions between genes, genome, and environment , employing molecular, physiological, and experimental tools within an evolutionary framework. Ellers contributes to the Netherlands Society of Evolutionary Biology (NLSEB) as a co-founder and serves as Vice-Chair of the Dutch Biology Council , advocating for biology research and education in the Netherlands. Research Interests: Ellers explores the intersection of evolutionary biology, ecology, and environmental science , with key themes in phenotypic plasticity, urbanization effects on species, trait-based ecology, and adaptive signaling . His work spans soil fauna dynamics, invasive species impacts, and metabolic adaptations , emphasizing interdisciplinary approaches to link mechanisms with ecological and evolutionary outcomes. Recent Publications highlight trends in urban ecology, climate change impacts, and trait evolution . Notable studies examine how noise and light pollution alter animal communication , high-sugar diets affect microbiomes , and robot morphologies reflect biological systems . His research also addresses data interoperability through initiatives like ShareTrait and global soil arthropod assessments . Scientific Contributions: Ellers advocates for open-access publishing and interdisciplinary climate change experiments. His leadership in the Dutch Biology Council and co-founding of NLSEB reflect sustained commitment to scientific policy and community engagement. Supervised 23 PhD theses and teaching courses like Ecosystem Services and Scientific Advocacy underscore his mentorship and educational impact.
Tom Mitchell is a Professor of Audio and Music Interaction at the University of the West of England (UWE), Bristol . As leader of the Creative Technologies Laboratory , his research focuses on interactive technologies for creative expression, blending computer science, music, and artificial intelligence. He is the principal investigator for the UKRI Future Leaders Fellowship project "Sensing Music Interactions from the Outside-In" and co-investigator for the Bridge , a £3M creative technology facility. His research spans digital musical instrument design , GPU-accelerated audio processing , and sonification of scientific data . Recent work includes accessibility improvements in virtual environments, AI-driven DMI development, and interdisciplinary collaborations like the MiMU Gloves with Imogen Heap. He also contributes to robotics teleoperation through auditory feedback systems. Selected publications highlight trends in GPU acceleration for audio , generative AI in musical contexts , and human-robot collaboration via sonification. As a software developer , he specializes in C++ and the Juce library , with applications in live performance systems and scientific visualization projects like Soma and danceroom Spectroscopy . UKRI Future Leaders Fellow Active in AHRC and WECA-funded projects Best paper nominations at EvoMUSART and International Faust Conference Mitchell collaborates with institutions including the Bristol Robotics Laboratory , Computer Science Research Centre , and Pervasive Media Studio . His work bridges academic research with commercial applications through ventures like May Productions and x-io Technologies.
Aldeida Aleti is a Professor in the Department of Software Systems & Cybersecurity at Monash University. Her research focuses on Automated Software Engineering, leveraging AI and optimization techniques for tasks like software design, testing, and repair. She has held roles including Chief Examiner for units like FIT4002 and FIT5136, and has contributed to teaching FIT3077 and FIT1008. Education: PhD in Software Engineering (Swinburne University of Technology, 2012), Master of Computer Engineering (Polytechnic University of Tirana, 2008), and Bachelor Honours in Computer Engineering (Yildiz Technical University, 2005). Research Interests: Automated software engineering, fitness landscape analysis, optimization, and search-based techniques. She leads projects like RAISE (Responsible AI Software Engineering) and collaborates on quantum computing and healthcare AI initiatives. Awards include the FIT Dean's Award (2016), Best Paper Awards (2015, 2011), and the Heidelberg Laureate Forum invitation (2014). She has been a grant assessor for the Australian Research Council since 2015. Advising: Accepting PhD students in AI-driven software engineering, optimization, and automated testing. Active in committees like the Faculty Research Committee and Early Career Researcher committee.
Hans Jonas Fossum Moen is an Associate Professor with a 20% appointment at the Department of Technology Systems, University of Oslo (UiO), and holds a 100% position as a researcher at the Norwegian Defence Research Establishment (FFI). His primary affiliation is with the Section for Autonomous Systems and Sensor Technologies. He is based at the Kjeller campus, with a visiting address at Gunnar Randers Road 19 and a postal address at Postboks 70. His research focuses on advancing autonomous systems and sensor technologies, particularly in the domains of swarm robotics, multi-agent coordination, and optimization algorithms. Key areas include UAV navigation, distributed localization in IoT networks, radar detection enhancement, and adaptive control systems for multi-functional swarms. He emphasizes the integration of biological principles into robotic systems, as evidenced by his participation in the ICRA 2018 Workshop on Swarms. His publications consistently highlight contributions to swarm intelligence, with a focus on improving data quality and efficiency in robotics applications. He has collaborated extensively with colleagues such as Kyrre Glette, Oleg Yakimenko, and Jan Dyre Bjerknes, exploring topics ranging from task allocation in multi-agent systems to evolutionary algorithms for filter optimization. His work bridges theoretical computer science with practical engineering challenges in autonomous systems. No scientific awards have been explicitly mentioned in the provided texts. Moen’s advising and grants narrative indicates no listed advisees or active grant projects, though his 20% UiO position suggests potential involvement in academic supervision. His primary research activities are embedded within FFI and the Autonomous Systems section at UiO, contributing to interdisciplinary efforts in sensor technologies and robotic systems.
David Fouhey is an Assistant Professor at New York University, jointly appointed between the Courant Institute of Mathematical Sciences (Computer Science) and the Tandon School of Engineering (Electrical and Computer Engineering). He previously held positions at the University of Michigan and was a postdoctoral researcher at UC Berkeley. His research focuses on learning-based computer vision, particularly in 3D reconstruction, AI for science, and human-object interaction. Education: PhD in Robotics from Carnegie Mellon University (2013-2018) Bachelor of Arts in Computer Science from Middlebury College (2007-2011) Research Interests: His work spans 3D reconstruction from images , AI-driven scientific measurement (e.g., solar physics, evolutionary ecology), and human interaction modeling . Notable projects include Stereo4D for 3D motion analysis and SyntheticIA for solar magnetogram fusion. Recent Articles: Recent work emphasizes interdisciplinary applications of vision (e.g., bird morphology analysis) and robust 3D techniques like Perspective Fields for camera calibration. His 2025 Nature Scientific Data paper on bird skeletal traits highlights his AI-for-science focus. Grants & Collaborations: Secured a NASA grant for heliophysics tools and collaborates with institutions like NASA’s SDO mission and the Astrophysical Journal. Labs & Teams: Leads a NYU research group focused on vision and robotics, with active collaborations in astrophysics and ecology.
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