جست‌وجوی استاد و پژوهشگر

• Robotics
• Evolutionary Robotics
• Artificial Evolution
• +۶ مورد دیگر

Leni Le Goff is a Lecturer at the School of Computing, Engineering and the Built Environment , Edinburgh Napier University. Her research bridges robotics , evolutionary computation , and environmental sustainability . Key research interests include: Evolutionary design of robot morphologies and controllers Integration of individual and cultural learning in artificial evolution Application of autonomous systems for terrestrial biodiversity monitoring Optimization frameworks for robotic policy search Manufacturability constraints in morpho-evolution Transdisciplinary collaboration between ecologists and roboticists Recent publications highlight her work on: Developing generalized early stopping criteria for policy search Mapping fitness landscapes in morpho-evolution Assessing robotic solutions for ecological surveying Overcoming hierarchical optimization challenges in coevolution Creating biodegradable and deployable robotic systems Evaluating manufacturability trade-offs in evolved robot designs Active in the Autonomous Robot Evolution (ARE) project, she collaborates with leading researchers like Prof Emma Hart and Prof Karen Diele. Her work receives funding from EPSRC and the Carnegie Trust , focusing on real-world deployment challenges and computational efficiency improvements.

Marcos Gridi-Pappمشاهده پروفایل

استاد

• Acoustic Communication
• Animal Behavior
• Evolutionary Biology
• +۶ مورد دیگر

Marcos Gridi-Papp is a Professor in the Department of Biological Sciences at University of the Pacific, specializing in the study of acoustic communication systems in animals. His research investigates the interplay between hearing, vocal anatomy, and communication behavior, with a focus on frogs and crickets. He also teaches courses related to biological sciences and advises biology and pre-dental majors. PhD in Integrative Biology, University of Texas, Austin (2003) MS in Ecology, State University of Campinas, Brazil (1997) BS in Biological Sciences, State University of Campinas, Brazil (1994) Gridi-Papp's research explores how anatomical structures influence vocal performance and auditory sensitivity. His lab investigates: Laryngeal morphology and vocal control in túngara frogs Auditory tuning mechanisms and ultrasound sensitivity Environmental impacts on communication strategies Physiological and behavioral adaptations in vocal systems Signal complexity evolution and middle ear mechanics Eustachian tube control and acoustic reflexes Recent research trends focus on: Bioacoustic adaptations in amphibians Behavioral responses to environmental changes Anatomical constraints on vocalization Acoustic signal optimization Frequency modulation mechanisms Multi-component call structures His lab offers research opportunities in anatomy, electrophysiology, animal behavior, and computational methods, supporting students with credit hours and technical training.

Tanja Kaiserمشاهده پروفایل

پژوهشگر

• Multi-Robot Systems
• Evolutionary Robotics
• Autonomous Intelligent Mobile Robot Systems
• +۴ مورد دیگر

Tanja Kaiser is a Senior Researcher in the Department of Computer Science & Artificial Intelligence at the University of Technology Nuremberg, Germany. She leads a junior research group and serves as an Ada Lovelace Distinguished Research Fellow at ScaDS.AI Dresden/Leipzig and Technische Universität Dresden. Her work spans evolutionary robotics, swarm intelligence, and collective behavior in autonomous systems. Dr.-Ing., Computer Science, University of Lübeck (2022) M.Sc., Computer Science, Technical University of Berlin (2017) B.Sc., Computer Science, DHBW Stuttgart (2014) Kaiser focuses on multi-robot systems and surprise minimization in swarm robotics. Her research explores evolutionary algorithms, self-organization, and autonomous decision-making, with applications in UAV tracking and onboard manipulation behaviors. Recent publications emphasize dynamic collective behaviors and task-independent behavior characterization. Kaiser’s scientific contributions include awards like the Bernd Fischer Prize (2023). She actively contributes to academic equity as a representative for the equity of women in sciences and arts at the University of Technology Nuremberg.

• Female Entrepreneurship
• Real Estate Management
• Service Management
• +۲ مورد دیگر

Michela Mari is an Associate Professor of Economics and Business Management at the Department of Management and Law, Faculty of Economics, University of Rome Tor Vergata. She serves as Deputy Coordinator of the Master's Degree in Real Estate Economics and Management and the Departmental Research Center "Scientific Observatory on Female Entrepreneurship - OSIF," and is a Faculty Member of the PhD in Management. Since 2018, she has chaired the "Female Entrepreneurship" Track at the European Academy of Management Conference (EURAM) and has been an active member of the Global WEP Network since 2017. Her research centers on Female Entrepreneurship , Real Estate Management , and Service Management , with particular focus on work-family conflict dynamics, virtual retail environments, and public-private partnerships. Her interdisciplinary approach bridges business strategy with gender studies and urban development, resulting in publications in leading journals such as International Entrepreneurship and Management Journal , Cities , and The Service Industries Journal . She has pioneered research on Italian female entrepreneurs' experiences and global STEM entrepreneurship barriers. Analysis of her publication trends reveals strong thematic continuity in gender-focused business research since 2011, with increasing emphasis on sustainability and digital transformation in recent years. Her work consistently addresses practical implications for policy and management while maintaining rigorous academic standards. Mari's scientific recognition includes: borsa di studio per giovani ricercatori, XXXIII Convegno Nazionale AIDEA 2010 for corporate governance research As PhD faculty and OSIF Research Center Deputy Coordinator, she actively mentors emerging scholars in female entrepreneurship research while collaborating with international networks like Global WEP to shape policy frameworks. Her editorial leadership in special journal issues demonstrates scholarly influence beyond traditional publication metrics. She directs the Departmental Research Center "Scientific Observatory on Female Entrepreneurship - OSIF," which conducts empirical studies on gendered business practices and advises policymakers on women's economic empowerment initiatives through evidence-based research.

Joy O'Keefeمشاهده پروفایل

دانشیار

• Bat Ecology
• Wildlife Conservation
• Human-Wildlife Interactions
• +۴ مورد دیگر

Joy O'Keefe is an Associate Professor at the University of Illinois Urbana-Champaign within the School of Integrative Biology and Department of Natural Resources and Environmental Sciences. She leads the Human-Wildlife Interactions Lab and holds additional affiliations with the Prairie Research Institute. Primary Affiliation: School of Integrative Biology Department: Natural Resources and Environmental Sciences Institute: Prairie Research Institute Dr. O'Keefe's research focuses on understanding bat ecology in human-altered landscapes, particularly examining: Roosting and foraging behaviors Mitigation strategies for bat conservation Thermal ecology of artificial roosts Wildlife trade impacts and solutions Acoustic monitoring techniques Effects of climate and disease on bat populations Her recent work addresses critical conservation challenges such as: Ending online ornamental bat trade Optimizing bat box thermal conditions Assessing white-nose syndrome impacts Improving habitat suitability modeling Dr. O'Keefe collaborates extensively with: USDA Forest Service National Park Service State wildlife agencies Private landowners

Andrea Frommelمشاهده پروفایل

استادیار

• Sustainable Aquaculture
• Climate Change
• Fish Physiology
• +۵ مورد دیگر

Andrea Frommel is an Assistant Professor in Applied Biology and Chair in Sustainable Aquaculture at the University of British Columbia's Faculty of Land and Food Systems. She leads research at the intersection of climate change, fisheries science, and sustainable aquaculture practices, with particular emphasis on early life stages of commercial fish species. Her educational background includes a BSc from the University of California at Santa Cruz, an MSc from the University of Southern Denmark, and a PhD from the Hemholtz Center for Ocean Research in Kiel, Germany. This international training has informed her interdisciplinary approach to aquatic research. Dr. Frommel's research focuses on three interconnected areas: the effects of climate change (particularly ocean acidification and warming) on commercial fish species; the development of alternative sustainable feeds for aquaculture; and optimizing fish welfare practices in aquaculture systems. Her work examines species-specific and life-stage-specific responses to environmental stressors, with implications for both wild fisheries management and aquaculture production. Her recent publications reveal a strong emphasis on understanding how combined climate change stressors affect fish physiology during critical life stages, particularly during the transition from freshwater to seawater in salmonids. She has made significant contributions to understanding how fish species vary in their resilience to ocean acidification, with important implications for stock assessment models and aquaculture production management. Dr. Frommel actively collaborates with the Hakai Institute, Department of Fisheries and Oceans, local NGOs, government agencies, industry partners, and international research institutions. She welcomes graduate students interested in projects related to sustainable aquaculture, climate change impacts on fisheries, and fish physiology under changing environmental conditions. She directs the Aquaculture and Climate Change Lab, which investigates how environmental stressors affect commercial fish populations and develops mitigation strategies to enhance the sustainability of aquaculture operations. Current projects include examining how kelp can mitigate ocean acidification effects, researching alternative feed ingredients, and studying local variability in coastal systems that may provide resilience to climate change.

Jeffery D. Weirمشاهده پروفایل

استاد مدعو

• Operations Research
• Decision Analysis
• Risk Analysis
• +۶ مورد دیگر

Dr. Jeffery D. Weir is an Adjunct Professor in the Department of Operational Sciences at the Air Force Institute of Technology (AFIT). A former U.S. Air Force officer, he specializes in decision analysis, risk analysis, and multi-objective optimization, with applications spanning military logistics, energy systems, and transportation modeling. His research addresses complex operational challenges such as aircraft scheduling, RNA foldability prediction, and cost analysis for military installations. Doctor of Philosophy (Ph.D.), Industrial Engineering & Operations Research, Georgia Institute of Technology, 2002 Master of Science (M.S.), Operations Research, Air Force Institute of Technology, 1995 Bachelor of Science in Electrical Engineering (B.S.E.E.), Georgia Institute of Technology, 1988 Dr. Weir's research bridges theoretical and applied domains, focusing on metaheuristics, data envelopment analysis, and robust optimization. His recent work includes RNA structure prediction frameworks, multi-modal distribution networks, and energy model recommendation systems. His publications span journals like BMC Bioinformatics , European Journal of Operations Research , and IEEE Transactions on Evolutionary Computation , reflecting interdisciplinary expertise in computational biology, military logistics, and building energy systems. Scientific awards include the Toulmin Medal for best article in 2004. He has received grants from the Defense Intelligence Agency, United States Transportation Command, Air Force Materiel Command, and other military organizations. Dr. Weir is a member of the Institute for Operations Research and the Management Sciences (INFORMS), Military Operations Research Society, and Institute of Industrial Engineers. His work emphasizes practical decision support tools for military personnel and resource management.

• Fuzzy Logic Systems
• Artificial Intelligence
• Model-Based Predictive Control
• +۶ مورد دیگر

Professor Mahdi Mahfouf holds the Chair in Intelligent Systems at the University of Sheffield's School of Electrical and Electronic Engineering . He obtained his MPhil (1988) and PhD (1991) in Control Systems from the same institution. After postdoctoral research (1992-1996) on Leverhulme-funded projects in Model-Predictive Control and Fuzzy Logic, he progressed through academic ranks at Sheffield to Full Professor (2005). Recipient of the IEE Hartree Premium Award (1992) and MEDIPEX Innovation Award (for ICU Decision Support Systems) Over 370 publications, including 130+ journal papers Head of the Intelligent Systems Research Laboratory Research Themes His work spans fundamental research in Fuzzy Logic (modelling, control), Neural-Fuzzy Systems, Self-Organising Control, and Evolutionary Optimization, alongside applied domains in pharmaceutical manufacturing, aerospace systems, biomedical engineering (ICU monitoring), and intelligent transportation. Recent publications focus on hybrid AI for pharmaceutical processes , type-2 fuzzy control systems , and machine learning in manufacturing metrology . Lab initiatives include multistage process monitoring and human-machine interaction systems for stress management.

Robin Purshouseمشاهده پروفایل

استاد

• Computational Modelling of Complex Social Systems
• Agent-Based Modelling
• Machine Learning
• +۶ مورد دیگر

Professor Robin Purshouse is a leading academic at the University of Sheffield , currently serving as Professor of Decision Sciences in the Department of Automatic Control and Systems Engineering within the School of Electrical and Electronic Engineering . With a career spanning academia and industry, his work bridges computational modelling , optimization , and systems science to address complex challenges in public health and engineering. His research has been pivotal in developing mechanisms for agent-based modelling and evolutionary multi-objective optimization . Education: PhD in Control Systems (2004), MEng in Control Systems Engineering (1999) from the University of Sheffield Professor Purshouse's research focuses on computational modelling of complex social systems , decision analytics for population health policy , and Bayesian optimization . He has pioneered the integration of machine learning and uncertainty quantification in social science simulations, with notable projects like the Sheffield Alcohol Policy Model and CASCADE initiative. His work spans interdisciplinary domains, including health economics , policy evaluation , and engineering design . Recent publications highlight his expertise in agent-based modelling for smoking/vaping dynamics , intersectional disparities in alcohol consumption , and inclusive economy frameworks . He has secured substantial funding (exceeding £16 million) through grants from NIH , CRUK , UKPRP , and MRC , including his role as co-PI in the HealthMod cluster. His contributions to multi-objective optimization and evolutionary algorithms have advanced methodologies in both engineering and public health domains. Scientific Awards: ESRC Future Research Leaders Award (2012-2015) As a co-developer of the Liger optimization environment , Purshouse has fostered open-source tools for complex decision-making. He leads the SIPHER consortium for systems science in public health and serves on editorial boards for journals like Environmental Modelling & Software . His teaching includes Agent-Based Modelling (ACS6132), and he maintains professional memberships in the Association for Computing Machinery and Research Society on Alcohol .

• Explainable Artificial Intelligence
• Machine Learning
• Data Clustering
• +۴ مورد دیگر

Nicolas Labroche serves as a Researcher in the Department of Computer Science at the Polytechnic School of the University of Tours. He is affiliated with the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT) within the UFR of Sciences and Technology. His academic work spans multiple research domains with significant contributions to machine learning methodology and applications. His primary research focuses on Explainable Artificial Intelligence , particularly for medical applications where model interpretability is critical. He has pioneered methods in clustering of local attributive explanations and discernibility in medical ML models . Additional expertise includes exploratory data analysis through mathematical programming for comparison queries, time series forecasting for environmental monitoring, and preference-based explanations in recommender systems. His work bridges theoretical computer science with practical applications in healthcare, environmental science, and business intelligence. Analysis of his publication trends reveals consistent innovation in making data exploration more efficient and interpretable. Recent work emphasizes user-centric explainability (2024-2025), mathematical optimization for analytics (2022-2023), and synthetic data generation (2022). His research demonstrates strong interdisciplinary connections between computer science, medicine, and environmental science. His laboratory affiliation with LIFAT provides the infrastructure for his computational research. While specific grant details aren't public, his publication record indicates sustained research productivity across multiple European-funded projects focused on data science applications.

Romain Raveauxمشاهده پروفایل

دانشیار

• Image Analysis
• Machine Learning
• Structural Pattern Recognition
• +۵ مورد دیگر

Romain Raveaux is an Associate Professor at the LIFAT Computer Science Laboratory, University of Tours, affiliated with Polytech Tours. His research focuses on Image Analysis, Machine Learning, Structural Pattern Recognition, Graph Matching, Graph Neural Networks, Discrete Optimization, Reinforcement Learning, and Transfer Learning . Email: romain.raveaux@gmail.com , romain.raveaux@laposte.net Address: 64 av. Jean Portalis, Tours, France, 37200 Phone: +33 (0)2 47 36 14 27 Research Interests Graph Matching and Neural Networks Discrete Optimization for Pattern Recognition Transfer Learning in Graph-Based Models Historical Document Analysis Scientific Trends His recent work bridges Graph Neural Networks with Mixed-Integer Programming , focusing on Image Semantic Segmentation and Graph Cycle Detection . Earlier studies emphasize Genetic Algorithms for graph classification and Graph Edit Distance optimization in pattern recognition.

• Fungal Evolution
• Population Genetics
• Mitochondrial DNA Variation
• +۳ مورد دیگر

Jianping Xu is a Professor in the Department of Biology at McMaster University, specializing in the ecology and evolutionary genetics of fungi. His research explores evolutionary mechanisms in fungal populations from environmental, clinical, and host-associated contexts. Institution: McMaster University Department: Biology Research Overview: Integrates microbiology, molecular genetics, and quantitative approaches to study fungal evolution. Research Interests include: Population genetics of human and animal fungal pathogens Mitochondrial DNA variation and inheritance Development of biomarkers for fungal identification Microbiome impacts on host health Publication Trends show focus on fungal pathogenesis, environmental adaptation, and genomic analyses across species like Cryptococcus , Aspergillus , and agricultural fungi. Teaching & Outreach connects to McMaster's biology programs, with research stories highlighting fungal-based innovations (e.g., mushroom plastics) and clinical studies on drug-resistant pathogens.

Daniel Boleyمشاهده پروفایل

استاد

• Numerical Linear Algebra
• Data Mining
• Machine Learning
• +۵ مورد دیگر

Daniel Boley is a Professor and Distinguished University Teaching Professor at the University of Minnesota, within the College of Science and Engineering, Department of Computer Science and Engineering. He serves as the Director of Graduate Studies for the Graduate Program in Data Science, which offers a Master's of Science and a Post-Baccalaureate Certificate. His office is located in Kenneth H. Keller Hall at 4-225C. Professor Boley's research spans computational methods in linear algebra, scalable data mining algorithms, and applications in systems biology and bioinformatics. His work focuses on scalable algorithms for convex optimization in machine learning, analysis of networks and graphs from metabolic biochemical networks, and wireless device networks. He has made significant contributions to numerical linear algebra methods for control problems, parallel algorithms, and iterative methods for matrix eigenproblems. His research interests also include algebraic models in systems and evolutionary biology, and biochemical metabolic networks. His recent publications demonstrate a strong focus on applying graph theory and network analysis to diverse domains including robot swarms, medical imaging (particularly for glioblastoma and COVID-19 diagnosis), and metabolic network analysis. His work bridges theoretical computer science with practical applications in biology and medicine, with a consistent emphasis on developing scalable computational methods. The trend shows increasing interdisciplinary collaboration, particularly with medical researchers. Distinguished Member by the ACM Top university award for post baccalaureate, graduate and professional education Distinguished University Teaching Professor title Professor Boley has advised numerous PhD students including Tatiana Lenskaia (2021), Shaozhe Tao (2018), Ham Ching Lam (2014), and others dating back to 1994. His research has been supported by various grants enabling work on scalable computation of elementary pathways through metabolic networks, Markov models of viral evolution, and scalable data mining algorithms for text analysis. He has developed software tools for clustering, dot plot visualization, and educational graphics. Professor Boley directs the Graduate Program in Data Science and has been involved in projects such as the Principal Direction Divisive Partitioning (PDDP) Project. His research group develops practical implementations of theoretical advances, including the PDDP clustering algorithm, Dot.py genome viewer, and various educational graphics tools for introductory programming courses. He maintains active collaborations across disciplines, particularly in bioinformatics and medical imaging applications.

Sahand Hormozمشاهده پروفایل

استادیار

• Systems Biology
• Computational Biology
• Single-Cell Analysis
• +۹ مورد دیگر

Sahand Hormoz is an Assistant Professor at Harvard Medical School and a faculty member in the Department of Data Science at Dana-Farber Cancer Institute. His research focuses on controlling biological systems to understand cell state transitions and develop technologies for single-cell analysis, synthetic biology, and organoid modeling. PhD in Applied Physics from Harvard University (advised by Michael Brenner) Postdoctoral work at Kavli Institute for Theoretical Physics (UCSB) and Elowitz Lab at Caltech Research Interests His lab combines high-throughput single-cell measurements with differential geometry and machine learning to analyze complex biological data. They engineer cells for lineage tracing, develop organoid systems, and aim to automate biological modeling to overcome human cognitive limitations in understanding life systems. Publication Trends Key areas in his recent work include: Computational methods for single-cell and lineage analysis Cancer evolution in myeloproliferative neoplasms Synthetic biology tools for DNA-based cellular memory Integration of machine learning with biological dynamics Applications in stem cell biology and microbial systems Development of microfluidic platforms Labs & Teams Hormoz Lab at Harvard Medical School collaborates with Dana-Farber's Data Science Department to advance quantitative biology approaches.

• Sustainable Aerospace Engineering
• Conceptual Aircraft Design
• Propulsion Systems
• +۳ مورد دیگر

Dr Albert Stevan van Heerden is a Lecturer in Aerospace Engineering at the James Watt School of Engineering, University of Glasgow. Previously, he was a Research Fellow at Cranfield University's Rolls-Royce University Technology Centre and Centres for Aeronautics and Propulsion and Thermal Power Engineering. He holds a PhD in Aerospace Engineering from Cranfield University, an MS in Aeronautics from California Institute of Technology (Fulbright scholar), and a BEng in Mechanical Engineering from the University of Pretoria. His research focuses on conceptual aircraft design , airframe and propulsion systems development , and technical/economic assessment of sustainable aerospace technologies . He employs deterministic and non-deterministic design methods, with a unique emphasis on evolvable aircraft family design for long-term relevance. His work spans traditional civil transport aircraft, electric aircraft , and hydrogen-powered aircraft systems. Key publications include advancements in set-based design techniques margin allocation strategies hydrogen propulsion systems thermal management frameworks uncertainty allocation methods . Scientific recognition includes Fellow of the Higher Education Academy (FHEA) Member of the Royal Aeronautical Society (MRAeS) . He also serves as Academic Adviser for the Commonwealth Scholarship Commission and Academic Ambassador for the James Watt School of Engineering. His teaching portfolio includes Thermodynamics 2, Aircraft Design 3, and Fluid Mechanics (University of Glasgow Singapore), reflecting his expertise in core aerospace disciplines.