جست‌وجوی استاد و پژوهشگر

• Collective Robotic Construction
• Swarm Robotics
• Soft Robotics
• +۴ مورد دیگر

Kirstin Petersen is an Associate Professor in the Department of Information Science at Cornell University's Bowers College of Computing and Information Science. She leads the Collective Embodied Intelligence Lab, focusing on collective robotic systems that exhibit emergent intelligent behaviors through local interactions. Her research interests center on collective robotic construction, swarm robotics, soft robotics, and human-robot interaction. Petersen's work explores how groups of simple robots can collaborate to build complex structures, with applications ranging from construction to agriculture. She investigates the principles of embodied intelligence, where the physical form and environment of robots contribute to their capabilities, reducing the need for complex centralized control. Her publication trends show a consistent focus on distributed robotic systems, with recent work expanding into agricultural robotics, human-drone interaction, and novel actuation methods using phase-changing materials. Her research bridges theoretical principles of collective behavior with practical implementations in soft and modular robotic systems. Petersen has advised numerous graduate students who have become prominent researchers in robotics, including Steven Ceron, Nialah Wilson-Small, and Jiahe Chen. Her lab has secured funding for projects related to swarm construction, agricultural monitoring, and soft robotic systems. She leads the Collective Embodied Intelligence Lab at Cornell, which brings together researchers from computer science, mechanical engineering, and biology to develop novel approaches to collective robotic systems. The lab emphasizes both theoretical foundations and practical implementations, with projects ranging from tiny modular robots to agricultural drones.

• Machine Learning
• Computer Vision
• Signal Processing
• +۶ مورد دیگر

Giacomo Boracchi is a researcher at the Polytechnic University of Milan , focusing on machine learning, computer vision, and signal processing. His work spans anomaly detection, change detection in data streams, 3D imaging, and biomedical applications. Key Collaborations : Diego Carrera, Luca Magri, Cesare Alippi Industries : Embedded systems, medical imaging, environmental monitoring Recent research explores adaptive Kalman filtering for battery estimation, zero-shot anomaly detection, and explainable AI for vision-language models. Publications highlight applications in waste sorting, histological data generation, and cardiac monitoring. His technical focus includes convolutional networks, ensemble learning, and domain adaptation. Boracchi's work bridges theoretical advancements with real-world systems in fraud detection, semiconductor manufacturing, and wearable health devices.

Twan Stoffersمشاهده پروفایل

پژوهشگر

• Fish Ecology
• Freshwater Biodiversity
• River Ecology
• +۶ مورد دیگر

Dr. Twan Stoffers is a Postdoctoral Researcher at the Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, affiliated with the Community and Ecosystem Ecology Department. His work focuses on fish ecology, freshwater biodiversity, river restoration, and conservation biology. He leads the Aquatic Ecogeography research group and actively contributes to projects like BioAgora, which bridges scientific research with policy and societal needs. His expertise includes fish population dynamics, elasmobranch biology, and transboundary conservation strategies. Research Interests: Ontogenetic shifts in fish populations Habitat heterogeneity and connectivity in river systems Conservation of migratory fish species Ecological impacts of river restoration policies Global swimways for freshwater biodiversity Publications highlight his work on river restoration efficacy, shark conservation, and policy interfaces. He has collaborated extensively across Europe and the Caribbean, emphasizing stakeholder collaboration for effective conservation. Current projects include analyzing the EU Nature Restoration Law’s implementation challenges and advancing science-policy dialogue through BioAgora. Key Achievements: Published in high-impact journals like Nature Ecology & Evolution and Conservation Biology Developed frameworks for assessing river restoration longevity Promoted transboundary conservation strategies for migratory fish

• Machine Learning
• Artificial Intelligence
• Robotics
• +۳ مورد دیگر

Charles L. Isbell Jr. is a Professor in the College of Computing at Georgia Institute of Technology. His work spans foundational research in artificial intelligence, machine learning, and robotics, with a focus on human-robot interaction, reinforcement learning, and educational technology. He leads efforts in scalable online education programs and contributes to policy discussions on AI's societal impact. Research Interests: Isbell's research emphasizes practical and theoretical advancements in AI systems, including Bayesian methods, multi-agent systems, and the ethical implications of AI. He explores how machines can learn from human interaction and adapt to complex environments. His recent work addresses challenges in robotics collaboration, scalable educational platforms, and the development of robust reinforcement learning algorithms. Publications Trends: His articles reflect a commitment to advancing AI through interdisciplinary approaches, with contributions to robotics collaboration (e.g., Nash equilibrium frameworks), scalable education systems, and foundational work in reinforcement learning and imitation learning. Recent collaborations include studies on machine learning systems engineering and long-term AI policy. Awards: No awards explicitly listed in the provided text. Advising & Grants: While specific grants are not detailed here, his extensive publication record indicates sustained research funding and mentorship of students in AI and robotics. His work on online education at scale highlights contributions to pedagogical innovation.

Mauricio Cantorمشاهده پروفایل

استادیار

• Behavioral Ecology
• Marine Ecology
• Animal Social Systems
• +۳ مورد دیگر

Mauricio Cantor is an Assistant Professor at Oregon State University's Department of Fisheries, Wildlife and Conservation Sciences, affiliated with the Marine Mammal Institute and the Marine Studies Initiative. He also holds non-tenured adjunct faculty roles at Universidade Federal de Santa Catarina (Brazil) and the University of the Witwatersrand (South Africa). His research focuses on behavioral ecology, linking theoretical models with empirical data to understand animal social systems, particularly in cetaceans. Cantor's work combines classical and innovative methods, addressing conservation challenges through interdisciplinary approaches. Education: PhD in Biology (Dalhousie University, 2016), MSc in Ecology (Universidade Federal de Santa Catarina, 2011), BSc in Biology (Universidade Estadual de Campinas, 2008). Research interests include social behavior in marine mammals, cultural transmission, human-animal cooperation, and conservation strategies. His recent work emphasizes the resilience of dolphin-fisher mutualisms and stakeholder engagement in marine conservation. Cantor leads the LABIRINTO research group, exploring intersections of animal behavior and human dimensions. Key collaborations span institutions globally, with a focus on cetacean ecology, network theory, and socio-ecological systems. His research has contributed to understanding sperm whale clans, dolphin social structures, and the impacts of anthropogenic stressors on marine life.

Anja Eggertمشاهده پروفایل

پژوهشگر

• Applied biological statistics
• Ecological statistics
• Ecosystem modeling
• +۴ مورد دیگر

Anja Eggert (PhD in Marine Biology) is a Researcher at the Leibniz Institute for Farm Animal Biology (FBN) , where she has served as Head of the Data Service Centre since 2025 and previously led the Service Group Statistical Consulting (2018–2024). Her work bridges biological research with advanced statistical methodologies. Education: Diplom in Biology (University of Rostock, 1990–1991) Exchange student (University of Maryland, USA, 1994–1995) Diplom in Biology (University of Bremen, 1991–1997) PhD in Marine Biology (University of Groningen, 1997–2001) Research interests focus on applied biological and ecological statistics , with a strong emphasis on numerical modeling of ecosystems and adaptation of organisms to environmental stress . Her work spans marine and agricultural systems, including: Biogeography, chemotaxonomy, and evolution of marine organisms Statistical analysis of heat stress impacts on livestock (goats, pigs, cows) Behavioral studies in pigs and goats related to social cognition Environmental monitoring and contamination assessment in marine ecosystems Publications reflect interdisciplinary trends in animal science , ecological statistics , and environmental adaptation . Key subfields include nutritional metabolism , reproductive biology , behavioral ecology , and climate impact studies . Professional activities include participation in projects such as: BMBF's Environmental monitoring for the delaboration of munition in the sea (UDEMM, 2016–2017) BMBF's Biological impacts of ocean acidification (BIOACID, 2016) EU-BONUS-Project Integrated carbon and trace gas monitoring for the Baltic Sea (INTEGRAL, 2017–2018) BMBF's Geochemistry and Ecology of the Namibian Upwelling System (GENUS, 2009–2015) Labs and teams include collaborations with institutions like the Leibniz Institute for Baltic Sea Research Warnemünde (IOW) and Helmholtz Centre for Ocean Research Kiel (GEOMAR) , alongside interdisciplinary work at FBN on data science and agricultural efficiency.

• Artificial Intelligence
• Multi-Agent Systems
• Social Network Analysis
• +۵ مورد دیگر

Gita Reese Sukthankar is a Professor at the University of Central Florida, specializing in artificial intelligence, multi-agent systems, and social network analysis. Her work integrates machine learning, human-robot interaction, and collaborative systems to address challenges in decentralized task allocation, online community dynamics, and human-machine teaming. She has contributed to projects involving agent-based modeling, reinforcement learning, and ethical AI applications in open-source software and policy discourse moderation. Affiliations: University of Central Florida Key Research Areas: Multi-Agent Systems, Social Network Analysis, Reinforcement Learning, Human-Computer Interaction Her research explores topics such as conflict prediction in team dialogues, bot impact on GitHub workflows, and chess mastery analysis using language models. She has co-authored over 185 publications in top venues like AAAI, AAMAS, and IROS, often collaborating with researchers like Rahul Sukthankar, Katia Sycara, and Kiran Lakkaraju. Her work bridges theoretical AI advancements with practical applications in robotics, software development, and policy analysis, emphasizing ethical considerations and scalable solutions.

Andreas K. Engelمشاهده پروفایل

استاد

• Neuroscience
• Neurophysiology
• Brain-Computer Interfaces
• +۴ مورد دیگر

Prof. Dr. med. Andreas K. Engel serves as Director of the Institute of Neurophysiology and Pathophysiology at the Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf (UKE). His research focuses on neural oscillations, brain dynamics, and neurophysiological mechanisms in health and disease, particularly employing EEG, MEG, and brain stimulation techniques like tACS to study cognitive processes, motor control, and multisensory integration. Current affiliation: Institute of Neurophysiology and Pathophysiology, UKE Academic rank: Professor Email: ak.engel@uke.de Key research areas include: Neural oscillations and synchronization Neurodegenerative disease mechanisms (Parkinson's) Brain-computer interface development Neural coupling during social interactions Cortical network dynamics Neuromodulation techniques Recent publications demonstrate expertise in analyzing multisensory integration, phase-amplitude coupling, and applying stimulation methods to modulate cortical activity patterns. His work bridges computational neuroscience with clinical applications in movement disorders and cognitive impairments.

Zhen Liمشاهده پروفایل

دانشیار

• Power semiconductor devices
• Offshore wind energy systems
• Wide bandgap semiconductors
• +۳ مورد دیگر

Zhen Li is Associate Professor at Shandong University's School of Electrical Engineering, specializing in power semiconductor technologies and renewable energy systems. Her research focuses on reliability engineering for offshore wind energy conversion and wide bandgap semiconductor applications. Education: Details not provided in text. Research: Develops fault-tolerant control systems for wind power conversion, PMSM drives, and grid-tied converters. Her work integrates predictive control algorithms with neural network diagnostics to enhance power system resilience. Awards: 2024 IEEE-CIEEC Best Paper Award 2023 Excellence Award in Teaching (Shandong Province) Multiple IEEE conference best paper awards Leadership: Serves on committees for IEEE conferences and promotes women in engineering through teaching excellence initiatives.

Kislaya Raviمشاهده پروفایل

پژوهشگر

• Multifidelity Uncertainty Quantification
• Gaussian Process
• Sparse Grids Methods
• +۲ مورد دیگر

Kislaya Ravi is a Doctoral Candidate at the Technical University of Munich (TUM), affiliated with the Chair of Scientific Computing within the TUM School of Computation, Information and Technology. She holds an M.Sc. in Computational Science and Engineering from TUM and degrees in Mechanical Engineering from the Indian Institute of Technology (BHU). Her research focuses on multifidelity uncertainty quantification, Gaussian processes, sparse grids methods, machine learning, and stochastic optimization. Education: M.Sc., Computational Science and Engineering, Technical University of Munich (202X) M.Tech., Machine Design, Indian Institute of Technology (BHU) (20XX) B.Tech., Mechanical Engineering, Indian Institute of Technology (BHU) (20XX) Research Interests: Kislaya’s work bridges computational methods and stochastic systems, emphasizing efficient uncertainty quantification techniques in physics and engineering. She explores multifidelity approaches to enhance computational efficiency in complex simulations and data-driven modeling. Teaching and Advising: Core instructor for Scientific Computing II and Algorithms for Uncertainty Quantification . Supervised multiple Master’s and Bachelor’s theses on topics like black-box optimization, surrogate modeling, and plasma instability analysis. Publications highlight contributions to multi-fidelity Gaussian processes, No-U-Turn sampling, and kinetic modeling. Her work appears in journals like Machine Learning: Science and Technology and conferences such as SIAM CSE and MCQMC.

Thomas Schmittمشاهده پروفایل

پژوهشگر

• Ecosystem Services
• Sustainability
• Environmental Science
• +۳ مورد دیگر

Dr. Thomas Schmitt is a Researcher at the Professorship of Ecological Services, University of Bayreuth, affiliated with the Faculty of Biology, Chemistry and Earth Sciences. His primary role involves research within the SusAlps project, focusing on sustainable grassland management in (pre-)Alpine Bavaria. He holds a M.Sc. in Global Change Ecology (University of Bayreuth) and a B.Sc. in Sustainability (Leiden University College). His research emphasizes ecosystem services valuation, land-use policies, and agent-based modeling. Prior roles include internships at WWF Germany and the Chamber of Commerce and Industry (IHK Nürnberg). Research Interests: Thomas Schmitt’s work bridges ecological and social dimensions of sustainability. He investigates how diverse actors perceive and value ecosystem services, particularly in alpine regions. His methodologies include agent-based modeling to simulate nitrogen fertilizer applications in grasslands and explore land-use trade-offs. Recent studies analyze synergies between recreation and agricultural practices, as well as improving agri-environmental policies through stakeholder engagement. Publications: His recent work spans agent-based modeling frameworks, spatial valuation of grassland services, and climate change perception studies. Key themes include biodiversity conservation, policy design, and educational tools for complex systems analysis. Affiliations: KIT-Campus Alpin collaborator, part of the Ecological Services research group at the University of Bayreuth.

Lisa Miracchi Titusمشاهده پروفایل

دانشیار

• Philosophy of Mind
• Artificial Intelligence Ethics
• Epistemology
• +۲ مورد دیگر

Lisa Miracchi Titus is a tenured Associate Professor of Philosophy at the University of Denver, with prior appointments at the University of Pennsylvania. Her research focuses on the nature of intelligence across biological and artificial systems, integrating epistemology, ethics, cognitive science, and AI. Her work examines foundational questions about agency, knowledge, and rationality, with applications to AI ethics, feminist philosophy, and social justice. Current projects include ethical frameworks for autonomous weapons, societal impacts of feminized AI interfaces, and complexity in cognitive systems. Recent publications critique statistical approaches in large language models (2023), develop virtue-based epistemic frameworks (2023), and advocate interdisciplinary research on gendered AI impacts (2022). Her monograph 'Wholly Intelligent' (under development) proposes integrated approaches to ethical AI research. Awards: National Endowment for the Humanities Fellowship supporting her monograph research. Advising & Service: Actively mentors underrepresented scholars, designed PhD wellness programs, and promotes LGBTQ+ visibility in academia. Collaborates with robotics labs (GRASP at UPenn) and contributes to AI policy discussions.

• Functional Genomics
• Genetic Networks
• CRISPR Screening
• +۳ مورد دیگر

Maximilian Billmann is Junior Professor at the University of Bonn's Institute of Human Genetics, developing computational methods for functional genomics and genetic network analysis. His research integrates CRISPR screens with machine learning to study cellular responses. Research Interests: Genetic interaction networks and pathway analysis CRISPR screen optimization and reproducibility Machine learning for functional genomics Mitochondrial function in disease Cancer signaling rewiring

• Neuroengineering
• Brain-Computer Interfaces (BCI)
• Human-Robot Interaction (HRI)
• +۳ مورد دیگر

Stefan Ehrlich is a Researcher at the Institute for Cognitive Systems (ICS) at the Technical University of Munich (TUM). His work focuses on neuroengineering, particularly non-invasive brain-computer interfaces (BCI) for human-robot interaction (HRI), neuroadaptive systems, and EEG-based neurotechnology. He collaborates closely with Prof. Gordon Cheng and contributes to projects involving error-related potentials (ErrPs), affective neurofeedback, and neuroprosthetics. His research integrates cognitive neuroscience principles with robotics to enhance human-machine collaboration and adaptive systems. Key research areas include: Development of passive BCI systems for real-time robotic adaptation Design of co-adaptive human-agent interfaces using neural signals EEG-based assessment of exoskeleton and humanoid robot performance Neuroimaging techniques for music-brain interactions His publications emphasize interdisciplinary approaches, combining neuromorphic engineering, machine learning, and social robotics. Ongoing work explores low-power neuromorphic hardware for EEG decoding and neurophysiological mechanisms underlying human-robot trust dynamics. Collaborations involve institutions like the Bernstein Center for Computational Neuroscience and industry partners in wearable robotics. Labs/Teams: Active contributor to the EEG Laboratory and projects like the Soft Wearable Robotics initiative. Engages in international conferences (IROS, IEEE EMBC) and co-organizes workshops on HRI and neurotechnology.

• Equine Behavior
• Animal Welfare
• Cognitive Ethology
• +۴ مورد دیگر

Prof. Dr. Konstanze Krüger-Farrouj serves as Professor of Horse Keeping and Animal Welfare Officer at Nürtingen-Geislingen University of Applied Sciences, maintaining active office hours at Campus CI3 in Nürtingen, Germany. Her institutional role integrates academic research with practical animal welfare oversight in equine management systems. Her research specializes in equine cognitive ethology with emphasis on sensory laterality, social learning mechanisms, and non-invasive welfare assessment. Key investigations explore how horses process environmental stimuli, transfer knowledge through observation, and exhibit behavioral asymmetries linked to emotional states—directly informing evidence-based training and husbandry practices that prioritize psychological well-being alongside physical health. Analysis of her 2021-2025 publications reveals consistent methodological innovation in measuring welfare through immunoglobulin A, laterality patterns, and problem-solving tasks. Recurring themes include human-horse communication dynamics, impacts of housing systems on stress physiology, and the cognitive implications of rider presence—demonstrating translational research bridging laboratory findings to practical equine management. No scientific awards were documented in available sources. While specific advisees aren't listed, her active supervision is evidenced by collaborative publications with institutional colleagues. Research infrastructure leverages the university's Lehr- und Versuchsbetriebe (LVB) agricultural facilities where experimental stables and pastures enable controlled behavioral studies. Current projects focus on predator-horse interactions and laterality-based welfare indicators, supported by ongoing publication output in specialized equine science journals. Her work operates within the university's agricultural research ecosystem, utilizing Lehr- und Versuchsgärten (LVG) facilities for ethological studies that examine natural behavior in semi-controlled environments, particularly investigating group dynamics and environmental enrichment strategies.