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Charles Higgins is an Associate Professor at the University of Arizona, specializing in computational neuroscience and bio-inspired engineering. His research integrates mathematical modeling of neural systems with engineering applications, bridging neurobiology and robotics. The Higgins Laboratory collaborates closely with neurobiology labs to study insect sensory systems and translate findings into efficient computational and VLSI designs for visual navigation and motion processing. Key projects include biomimetic visual motion sensors, small-target tracking algorithms, and neuromorphic architectures for autonomous systems. Research interests focus on understanding biological neural architectures—particularly in insects—and applying these insights to create superior engineering solutions. Notable contributions include models of elementary motion detection in flies, VLSI implementations of visual motion algorithms, and systems for obstacle avoidance in robotics. His work emphasizes parallel, continuous-time computing inspired by neuronal circuitry. Publications highlight advancements in bio-inspired visual processing, including motion detection modules for dragonfly-inspired robots and algorithms for image speed estimation. Higgins' engineering innovations often aim to mimic natural systems' efficiency and robustness, with applications in both basic science and applied robotics. Labs and collaborations involve cross-disciplinary teams focused on integrating biological principles with cutting-edge technology. While no specific awards are listed, his extensive publication record reflects sustained contributions to neuromorphic engineering and computational neuroscience.

• Computational Neuroscience
• Bio-inspired Engineering
• Neural Systems Modeling
• +3 more

Dr. Fabio Caraffini is an Associate Professor in Computer Science at Swansea University's School of Mathematics and Computer Science. He holds dual PhDs in Mathematical Information Technology (University of Jyväskylä, 2016) and Computer Science (De Montfort University, 2014), along with BSc and MSc degrees in Engineering from the University of Perugia. His research focuses on computational intelligence, particularly heuristic optimization methods like evolutionary algorithms and differential evolution. He also holds an honorary position as Senior Research Fellow at De Montfort University (2022–2024). Education History: BSc in Electronics Engineering (University of Perugia, 2008) MSc in Telecommunications Engineering (University of Perugia, 2011) PhD in Mathematical Information Technology (University of Jyväskylä, 2016) PhD in Computer Science (De Montfort University, 2014) Research Interests: Dr. Caraffini's work bridges theoretical optimization and practical applications. Key areas include evolutionary computing, structural bias analysis in algorithms, and interdisciplinary AI applications such as medical imaging, climate risk modeling, and robotics. His SOS Platform and BIAS toolbox are notable contributions to algorithm benchmarking and bias detection. Recent projects include AI-driven solutions for crop mapping, medical record analysis, and rail scheduling optimization. Publications & Trends: His 150+ publications span journals like Information Sciences , IEEE Transactions , and Applied Soft Computing . Themes include algorithmic robustness, constraint handling, and real-world optimization challenges. Notable works address differential evolution improvements, climate transition risk prediction, and medical decision support systems. Awards & Grants: Fellow of the Higher Education Academy (FHEA) Recipient of multiple research grants for projects in optimization and AI applications Advising & Collaboration: Actively supervises PhD students in AI-driven optimization and interdisciplinary applications. Collaborates with institutions globally on topics like microgrid energy management and pandemic prediction through self-organizing maps. Labs & Teams: Engaged in Swansea's Computational Foundry and the Morgan Advanced Studies Institute (MASI), contributing to cross-disciplinary research initiatives in AI and computational science.

• Evolutionary Computing
• Heuristic & Hyperheuristic Optimization
• Algorithm Behaviour
• +5 more

Keith L. Downing is a Professor in the Department of Computer Science at NTNU, affiliated with the Faculty of Information Technology and Electrical Engineering. His research focuses on bio-inspired artificial intelligence, including evolutionary algorithms, artificial neural networks, and computational neuroscience. He has authored two MIT Press books: *Intelligence Emerging* (2015) and *Gradient Expectations* (2023). His work bridges AI, artificial life, and cognitive science, emphasizing the emergence of intelligence in both natural and artificial systems. Teaching responsibilities include Introductory AI, AI Programming, Cognitive Architectures, and Deep Learning courses at NTNU. He also engages in public outreach, such as a 2015 TV appearance on *Schrødingers katt: Kunstig Intelligens*. His research spans predictive neural mechanisms, evolutionary computation, and the societal implications of AI, as seen in his 2014 feature article in *Aftenposten*. Key publications include foundational work on the Baldwin Effect (2004), neural predictive models (2013), and computational neuroscience (2009). He actively promotes interdisciplinary approaches to AI, blending technical innovation with biological plausibility.

• Bio-Inspired Artificial Intelligence
• Evolutionary Algorithms
• Artificial Neural Networks
• +5 more

Dr. Abdulghani Mohamed is a Senior Lecturer in the School of Engineering at RMIT University, specializing in aerospace engineering with a focus on unmanned aerial systems, turbulence research, and biomimetic flight technologies. His research integrates principles from biology with engineering applications to advance drone technology and flight control systems. His research interests span Turbulence , Unmanned Systems , Sensors , Biomimetics , Aerodynamics , Experimental fluid dynamics , Computational fluid dynamics , and Energy harvesting systems . Dr. Mohamed's work demonstrates a strong connection between natural flight mechanisms observed in birds and engineered solutions for drone technology. His recent publications (2018-2024) reveal consistent research productivity with a clear trajectory toward increasingly sophisticated drone control systems, turbulence adaptation mechanisms, and biomimetic applications. The research shows a progression from fundamental aerodynamic studies toward practical implementations in urban air mobility and advanced drone systems. Open to Masters Research or PhD student supervision Active research projects in drone propeller optimization, turbulence mitigation, and biomimetic flight Dr. Mohamed maintains an active research program with numerous projects related to unmanned aerial systems and their applications in complex environments. His work bridges theoretical aerodynamics with practical engineering solutions for next-generation flight systems.

• Turbulence
• Unmanned Systems
• Sensors
• +5 more

Scott Mitchell is a Lecturer in the School of Design at RMIT University's City Campus in Australia. His academic work bridges design theory and practice with a focus on critical and radical approaches to design that examine how objects become sites of social and public action. Mitchell's research spans Design Practice and Management, Visual Arts and Crafts, Creative Arts and Writing, Art Theory and Criticism, Architecture, and Digital Media. His work explores the intersection of design with social contexts, particularly through divergent consumer practices such as hacking and modding. His interdisciplinary approach combines critical design theory with electronic and interaction design practices to examine how designed objects function as sites of social engagement and public action. His publication record from 2014-2025 reveals an evolving research trajectory from foundational explorations of maker culture and material agency to contemporary investigations of energy-conscious design for smart homes and digital twins. A consistent theme across his work is the examination of the relationship between design, materiality, and social contexts, with recent publications focusing on interactive materials, wearable technology, and logo aesthetics. Scott Mitchell is actively engaged in research supervision, being open to Masters Research and PhD student supervision. His current supervisor projects include investigations into logo aesthetics, energy-conscious design for digital twin-driven smart homes, and interactive materials, reflecting his commitment to advancing design theory through practical application.

• Design Practice and Management
• Visual Arts and Crafts
• Creative Arts and Writing
• +5 more

Josefa Gómez Pérez is a Professor in the Department of Computer Science at Universidad de Alcalá. She holds a PhD in Computer Science from the same institution (2011), focusing on CAD tools for electromagnetic analysis of complex structures under supervision of Dr. Manuel Felipe Cátedra Pérez and Dr. Iván González Diego. Her research spans multiple areas including antenna design optimization, numerical methods for engineering problems, gamification in education, medical image analysis, and computer vision applications. She is affiliated with research groups such as the Climate Physics Group (CPG), Group of Advanced Numerical Techniques (GTNA), and TIFyC (Information Technologies for Training and Knowledge). Her work frequently integrates bio-inspired algorithms and web-based tools for solving engineering challenges. Key areas of contribution include developing simulation tools for radio propagation using OpenStreetMap data, optimizing antenna positioning with genetic algorithms, and enhancing educational engagement through gamified platforms. She has also explored interdisciplinary topics like class imbalance mitigation in medical AI and gender perspectives in engineering career choices. Josefa has authored numerous publications in top venues, with recent focus on AI-human interaction, 3D reconstruction techniques, and educational technology innovations. Notable tools she has developed include the NewFasant Suite, DSEXAMS automated questionnaire system, and LearningRlab educational package.

• Computer Science
• Artificial Intelligence
• Antenna Engineering
• +7 more

Mauricio Ayala Rincón is a Full Professor at Universidade de Brasília, affiliated with the Department of Computer Science and the Department of Mathematics. He is a leading researcher in computational logic, formal methods, and term rewriting systems, and heads the Theory of Computation research group (GTC/UnB). Research Interests: His work focuses on the formalization of mathematical and computational theories using proof assistants like PVS. Key areas include term rewriting systems, equational and rewrite-based deduction, automated reasoning, unification, nominal logic, formal verification, and applications in genomics and evolutionary algorithms. He also explores ethics in AI and mechanized mathematics. Recent Publication Trends: His recent articles (2023–2024) reflect a strong emphasis on formalizing algebraic and logical theories in PVS, advancing nominal equational reasoning, anti-unification over algebraic theories, and applying evolutionary algorithms to computational biology. The work is highly theoretical yet applied in verification and combinatorics. Scientific Awards: Best Paper Award at CICM 2023 for "Nominal AC-matching" Advising and Grants: He actively seeks PhD students in algorithmics, formal methods, theorem proving, and AI ethics. He has led numerous research projects, evidenced by extensive publications and editorial roles. He has not listed specific grants, but his continuous output suggests sustained funding. Labs and Teams: He leads the Grupo de Teoria da Computação (GTC/UnB) , which develops PVS libraries for term rewriting (TRS), nominal theories, and evolutionary algorithms. The group maintains public repositories and contributes to the NASA PVS library.

• Term Rewriting Systems
• Automated Reasoning
• Theorem Proving
• +13 more

Biljana Jović is an Associate Professor at the Department of Landscape Architecture and Horticulture, University of Belgrade’s Faculty of Forestry. She holds a PhD in Technical Sciences (2012) from the Faculty of Architecture, specializing in geometric education and visualization. As department president since 2022, she leads academic and research initiatives in landscape architecture and horticulture. Her education includes a master’s degree in geometry and architectural form from the Faculty of Architecture, with postgraduate studies in Serbia and specialization at TU Vienna and TU Dresden. Her research focuses on biomimetics, geometric modeling, and digital visualization in design. She founded the Geometry Workshop, a creative platform fostering interdisciplinary design exploration. Jović’s work bridges art and engineering through projects like bio-inspired installations and sustainable urban designs. Notable contributions include light art installations based on endemic plants and solar lamps modeled after flowers. She actively participates in international conferences (e.g., AFGS, ICGG) and collaborates with institutions like the Museum of Science and Technology. Awards include being a finalist in the Asian Design Modeling Contest and a Cumulus+ grantee. Her teaching spans undergraduate and graduate courses in descriptive geometry, digital visualization, and parametric modeling. She advises on EU projects (e.g., Worth Partnership) and contributes to global design networks via Cumulus Association. Research collaborations include biomimetic studies with international teams, emphasizing sustainable and innovative design solutions.

• Geometry and Graphics
• Landscape Architecture
• Biomimetics
• +4 more

Ramana M. Pidaparti is a Professor at the University of Georgia, specializing in interdisciplinary research at the intersection of engineering, biomedical science, and education. His work spans bio-inspired design, robotics, and AI-driven educational tools. He is a Fellow of the Royal Aeronautical Society and actively contributes to advancing engineering pedagogy through innovative curricula and teacher training programs. Research Focus: Bio-inspired systems, multi-robot systems, computational modeling of biological tissues, and AI in K-12 education. Key Projects: Development of frameworks for knowledge transfer in multi-agent systems (KT-BT), biomechanical analysis of brain and lung tissues, and integration of visual computing in middle school STEM education. His recent publications emphasize AI applications in education, predictive models for material degradation, and bio-inspired design methodologies. Awards include recognition for contributions to aeronautical and engineering education.

• Bio-inspired Design
• Robotics and Multi-Agent Systems
• Biomedical Engineering
• +4 more

Bhuvanesh Unhelkar is a Professor of Information Technology at the School of Information Systems and Management, part of the Muma College of Business at the University of South Florida's Sarasota-Manatee campus. He specializes in Big Data strategies, AI applications, and Agile methodologies. Currently teaching IT and Project Management courses at both undergraduate and graduate levels, he also oversees IT program design and online education initiatives. Education: Ph.D. and M.S. in Information Technology (University of Technology Sydney, 1997/1992) Masters Diploma in Business Administration (IMDR, Pune, 1986) Bachelor of Engineering (Electronic Engineering, Maharaja Sayajirao University of Baroda, 1982) Research Interests: Dr. Unhelkar’s work focuses on leveraging technology for business agility, including: Big Data analytics and AI-driven decision-making Cybersecurity in healthcare and IoT Agile project management frameworks Blockchain applications in finance and supply chains Cloud computing optimization IT education and curriculum development Awards & Recognition: Computerworld Object Developers Award (1995) Consensus IT Professional ‘Service to Industry’ Award (2006) Consensus IT Writer’s Award (2010) Service & Leadership: Active in academic governance through roles like: Member, Academic Programs Committee (APC) [2018–2019] Member, Faculty Professional Development Committee (FPDC) [2000–present] Search Committee Lead for Assistant Professor positions Publications: Authored/co-authored over 27 books and 109 research outputs, including seminal works like Artificial Intelligence for Business Optimization and Adoption and Adaption in Digital Business .

• Big Data Strategies
• Artificial Intelligence
• Agile Processes
• +5 more

Arina Buzdalova is a Lecturer in Computer Science at the Department of Computer Science, Aberystwyth University. Her research focuses on evolutionary algorithms, reinforcement learning, and optimization techniques, particularly in the context of dynamic selection of auxiliary objectives and runtime analysis. She has authored over 27 research outputs since 2011, with notable contributions to theoretical and applied aspects of evolutionary computation. Her work explores hybridization of clonal selection algorithms with local search, analysis of mutation rate control in evolutionary algorithms, and the use of reinforcement learning to enhance algorithmic efficiency. Key research themes include adaptive systems, stochastic optimization, and theoretical bounds on algorithm performance. Collaborations span international conferences in computational intelligence and evolutionary computation. Publications span topics such as re-optimization under frequent changes, fixed-target runtime analysis, and trade-offs in heuristic search. Her research bridges theoretical foundations with practical applications in optimization and artificial intelligence.

• Reinforcement Learning
• Evolutionary Algorithms
• Algorithm Optimization
• +3 more

Dr. Michael Denker is a Team Leader in the Computational and Systems Neuroscience department at the Institute for Advanced Simulation (IAS-6) , Forschungszentrum Jülich. His research focuses on data analytics for electrophysiology and optophysiology in behavioral neuroscience, emphasizing reproducible science practices and collaborative workflows. He leads the Data Science of Electro- and Optophysiology in Behavioural Neuroscience team, developing tools like Elephant , Neo , and Cobrawap to standardize data analysis across neuroscience experiments. His work addresses challenges in metadata management, provenance tracking, and interoperability between experimental and simulation datasets. Key contributions include the Neuroelectrophysiology Analysis Ontology (NEAO) for structured data sharing and frameworks for validating neural network simulations. Denker actively promotes open science through initiatives like the German National Research Data Infrastructure (NFDI-Neuro) and collaborates with the Human Brain Project (HBP) on EBRAINS services. His research integrates multi-scale data from electrophysiological recordings and computational models to study cortical waves and spike patterns, particularly in rodent and primate systems.

• Neuroscience
• Reproducible Science
• Data Analytics
• +4 more

Fabio Marchesoni is a Professor of Physics at the University of Camerino, affiliated with INFN Perugia Section and Tongji University Shanghai. His research focuses on stochastic processes, nonequilibrium statistical physics, and gravitational wave physics. He has contributed to major collaborations like LIGO/Virgo, publishing over 246 articles with 148,100 citations. Research Interests: Active matter systems, artificial Brownian motors, nanoscale transport phenomena, and gravitational wave detection. His work bridges fundamental physics with applications in neuromorphic computing and materials science. Key Contributions: Pioneered stochastic resonance theory, developed models for nanoscale motor systems, and co-authored landmark papers on GW170817 (neutron star merger) and the first direct detection of gravitational waves (GW150914). Collaborations: Works with institutions worldwide including University of Augsburg, RIKEN, and Loughborough University. Active in interdisciplinary projects combining physics with engineering and biology.

• Stochastic Processes
• Nonequilibrium Statistical Physics
• Gravitational Waves
• +4 more

Andrea Alu is a Distinguished Professor of Electrical Engineering and Einstein Professor at the City University of New York (CUNY) Graduate Center. He serves as Founding Director of the Photonics Initiative at the Advanced Science Research Center (ASRC). His primary affiliation is with the Department of Electrical Engineering, with additional ties to the Physics department. Alu’s research focuses on metamaterials, metasurfaces, and photonics, particularly in areas like topological acoustics, nonlinear optics, and bioelectronic devices. His work has produced groundbreaking innovations in wave manipulation, including applications in biomedical engineering and quantum systems. Alu’s academic career includes leadership roles in the field of photonics, with contributions to roadmapping initiatives for 2D materials and metamaterials. He has pioneered concepts such as time-modulated metasurfaces and nonlocal optical effects. His research is supported by grants focusing on metamaterial theory, quantum metamaterials, and bio-inspired systems. Notable achievements include the 2023 Optical Materials Express Emerging Researcher Best Paper Prize (2024). Collaborative efforts extend to labs and teams at the ASRC, emphasizing interdisciplinary projects in photonic computing, acoustic cloaking, and reconfigurable meta-devices. His work bridges fundamental physics with applied engineering, addressing challenges in energy-efficient systems and medical technology.

• Photonics
• Metamaterials & Metasurfaces
• Nonlinear Optics
• +4 more

Zemerart Asani is a Researcher affiliated with the Department of Applied Mechanics at the Faculty of Engineering, Vrije Universiteit Brussel. Their roles include being an External employee and a doctoral student in the Federated labs AI and Robotics. Asani holds an ORCID identifier (0000-0003-1485-2450) and is based in Brussels, Belgium. Education: Doctoral studies in Applied Mechanics (ongoing), with prior research in control systems and robotics, evidenced by publications from 2018 to 2025. Research focuses on multi-agent robotic systems for construction tasks, including heterogeneous multi-robot collaboration, path planning in cluttered environments, and dynamic modeling of robotic systems. Key projects include the FWOSB169 project on multi-agent control for heavy construction tasks (2023–2027). Their work emphasizes practical applications like heavy block assembly and bricklaying automation. Publications highlight expertise in robotics, control systems, and optimization, with recent work advancing shortest path algorithms and crane vibration control. Asani has received notable recognition, including the 1st Place Award in IEEE MRS 2024 for real-world robotic systems. Activities include peer-review contributions to journals like Nonlinear and Constrained Control , and presentations at conferences such as IFAC and the Benelux Meeting on Systems and Control. Their research network spans international collaborations in robotics and automation.

• Robotics
• Automation in Construction
• Multi-Agent Systems
• +3 more