جست‌وجوی استاد و پژوهشگر

• Robotics
• Human-Robot Interaction
• Swarm Robotics
• +۵ مورد دیگر

Michael A. Goodrich is a Professor in the Department of Computer Science at Brigham Young University, with an extensive research career spanning over two decades in robotics, human-robot interaction, and swarm intelligence. His work bridges theoretical foundations with practical applications, particularly in autonomous systems and multi-agent coordination. His research interests focus on Robotics , Human-Robot Interaction , Swarm Robotics , Artificial Intelligence , and Autonomous Systems . Goodrich's work explores how humans and robots can effectively collaborate, with particular emphasis on proficiency assessment, resilience, and communication in human-robot teams. His research has significant applications in search and rescue operations, swarm robotics, and autism therapy. Analysis of his recent publications reveals a strong focus on robot self-assessment capabilities, swarm behavior optimization, and resilience in multi-agent systems. His work increasingly integrates formal methods with practical robotics applications, creating frameworks for robots that can assess their own capabilities and communicate this information effectively to human teammates. Among his notable contributions are frameworks for robot proficiency self-assessment using assumption-alignment tracking, methods for designing resilient swarm behaviors, and formalizations of resilience for goal-oriented agents. His work has been published consistently in top venues including IEEE Transactions on Robotics, ACM Transactions on Human-Robot Interaction, and International Journal of Robotics Research. Dr. Goodrich has advised numerous students who have become active researchers in the field, including Aadesh Neupane, Daqing Yi, Xuan Cao, and Puneet Jain. His collaborative work spans multiple institutions and has practical applications in wilderness search and rescue, autism therapy, and multi-robot coordination systems.

• Gene Editing
• CRISPR-Cas Systems
• Induced Pluripotent Stem Cells
• +۵ مورد دیگر

Pranam Chatterjee is an Assistant Professor at the RNA Therapeutics Institute, UMass Chan Medical School, affiliated with the T.H. Chan School of Medicine. He holds a PhD in Media Arts and Sciences from MIT, with prior degrees in Computer Science and Molecular Biology. His research focuses on CRISPR-Cas systems, gene editing tools, and stem cell differentiation, particularly in reproductive medicine contexts. Chatterjee’s work includes developing novel genome editing technologies like PTM-Mamba and engineered Cas9 variants, as well as advancing methods for human oogonia-like cell specification and ovarian support cell co-cultures. His publications span topics in molecular biology, biotechnology, and computational biology, with contributions to improving CRISPR specificity, SARS-CoV-2 detection, and stem cell culture techniques. Chatterjee collaborates widely, including with institutions like Harvard and MIT, and his research has been highlighted in multiple news outlets and patents. His lab at the RNA Therapeutics Institute emphasizes interdisciplinary approaches, combining computational modeling with experimental biology to address challenges in genome editing, regenerative medicine, and disease modeling. While no formal awards are listed, his work has garnered significant citation impact, especially in CRISPR-Cas9 engineering and stem cell differentiation studies.

• Digital Work
• Gig Economy
• Platform Economy
• +۳ مورد دیگر

Nicola Bjerg Ens is a Postdoc in Digital Business Innovation at IT University of Copenhagen, specializing in the digital transformation of work through ethnographic approaches. Her research centers on platform labor, gig economy dynamics, and digital hustling, with a focus on worker experiences in digitally mediated work environments. Her research profile reveals deep engagement with labor market transformations in digital contexts, particularly examining normative control mechanisms, content creation practices, and precarity in platform work. She employs ecological ethnography to analyze how workers navigate digital hustling ecosystems, with attention to gendered dimensions and resilience erosion. Recent publications (2021-2024) demonstrate consistent output in top venues like New Media & Society and Information Systems Journal , revealing thematic progression from gendered platform selling to control dynamics and methodological innovations in digital ethnography. Her work bridges digital humanities, social sciences, and information systems research. Scientific recognition includes significant Mendeley readership (68 for control dynamics paper) and social media mentions, though no formal awards are documented. As a recent PhD graduate from Copenhagen Business School (2024), she shows no current evidence of student advising or major grant leadership. Her work operates within the Digital Business Innovation research environment at ITU, suggesting collaborative engagement with digital transformation scholars.

Wen Yeمشاهده پروفایل

استادیار

• User Experience Design
• Empathy-Driven Design
• Wearable Technology
• +۳ مورد دیگر

Wen (Vivian) Ye is an Assistant Professor of Practice in the Department of Design at the University of Texas at Austin. She holds dual Master of Fine Arts degrees from the University of California–Davis and the Marangoni Institute in Italy. Her academic role combines teaching design thinking and advanced design studio courses with industry experience from roles as a fashion designer at VERO MODA and a global fashion buyer for Armani. Her research focuses on user experience, empathy-driven design, and wearable technology, emphasizing cross-disciplinary collaboration. Ye actively participates in National Science Foundation (NSF) projects aimed at improving transportation and power systems through electric vehicles and clean energy solutions. She designs educational materials for these initiatives, bridging academic and industrial applications. Her work highlights innovation in sustainable technology and human-centered design principles. Her recent publications span data science code generation, neural network adaptation, and uncertainty quantification in machine learning. These contributions address foundational challenges in AI and computational methodologies, reflecting her dual expertise in design and technical systems.

Manuel Maarekمشاهده پروفایل

دانشیار

• Cybersecurity
• Computer Security
• Secure Programming
• +۶ مورد دیگر

Manuel Maarek is an Associate Professor at the School of Mathematical & Computer Sciences, Heriot-Watt University, specializing in Computer Science. His research focuses on cybersecurity, secure programming, and educational technologies, particularly leveraging serious games and collaborative methodologies for enhancing security awareness. His work integrates formal methods with practical applications, addressing topics like Bitcoin transaction analysis, developer-centric security training, and blockchain privacy. He has co-authored over 29 peer-reviewed publications and received awards including the 2018 Teaching Excellence Award and the 2022 EICC Best Paper Award. Key Research Themes: Cybersecurity Education, Secure Programming Practices, Cryptocurrency Analysis, Game-Based Learning Collaborations: Active in international collaborations, particularly in cybersecurity co-design and blockchain forensics Maarek’s recent projects include the 'Serious Slow Game Jam' methodology for cybersecurity education and investigations into large language models for student feedback. He actively contributes to improving software engineering education through integrated learning platforms like Canvas and GitLab.

• Artificial Intelligence
• Neuroscience
• Robotics
• +۳ مورد دیگر

Madeleine Bartlett is a Research Fellow at the University of Waterloo, affiliated with the Post Doctoral Scholars and Visitors groups. Her work bridges neuroscience and artificial intelligence, focusing on biologically plausible algorithms and their applications in robotics and human-robot interaction. Her research explores how neural mechanisms inspire computational models for reinforcement learning, action representation, and social signal processing. Key areas include integrating biological constraints into machine learning systems and developing robots capable of interpreting human social cues, particularly for therapeutic applications in autism spectrum disorder (ASD). Her publications highlight contributions to continuous action representations in basal ganglia models, biologically-based memory systems for reinforcement learning, and statistical rigor in human-robot interaction studies. She has also pioneered methods for estimating engagement in social HRI using novel neural architectures like Legendre memory units. While no formal awards or grants are listed, her work demonstrates significant innovation at the intersection of neuroscience-inspired AI and socially assistive robotics. She contributes to advancing robots as therapeutic tools through validated autonomous systems that mimic human guidance patterns observed in ASD therapy contexts.

Pengyu Nieمشاهده پروفایل

استادیار

• Software Engineering
• Machine Learning
• Program Analysis
• +۲ مورد دیگر

Dr. Pengyu Nie is an Assistant Professor at the University of Waterloo's Cheriton School of Computer Science. His research enhances developer productivity through machine learning techniques for software testing, code maintenance, and program analysis. Specific interests include execution-guided test completion, code-comment co-evolution, and multilingual programming systems. Current projects investigate LLM-based code editing in computational notebooks, multilingual code co-evolution, and test generation for exceptional behaviors. Research outputs include tools like pytest-inline for Python testing and Roosterize for Coq lemma suggestions. Awards include the Margarida Jacome Dissertation Award (2023) and ACM SIGSOFT Distinguished Paper Awards (2023, 2019). He leads the UW-SWaG research group and advises PhD/master's students on software engineering and ML projects.

• Artificial Intelligence
• Database Systems
• Neurosymbolic Reasoning
• +۳ مورد دیگر

Alexander Beiser is a Researcher at TU Wien's Department of Databases and Artificial Intelligence, part of the Faculty of Informatics. His work focuses on neurosymbolic reasoning, logic programming systems like Answer Set Programming (ASP), and hybrid grounding techniques to optimize computational workflows. He teaches the 2025S Algorithms and Data Structures course (186.866) as a VU lecture. His research bridges formal methods with practical applications in AI, emphasizing user interaction frameworks (e.g., clinguin) and improving efficiency in logic-based systems. Key areas include advancing neurosymbolic integration with LLMs, optimizing ASP-driven systems through hybrid grounding, and developing tools for interactive logic programming. Recent contributions address bottlenecks in grounding processes via splitting and rewriting strategies, aiming to enhance scalability in complex reasoning tasks. Alexander is based at Favoritenstrasse 9, Room HA0302, and can be reached via alexander.beiser@tuwien.ac.at. His work reflects a blend of theoretical advancements and applied systems engineering in AI and database technologies.

David Robertsonمشاهده پروفایل

استاد آموزشی

• Particle Physics
• High-Performance Computing
• Quantum Field Theories
• +۳ مورد دیگر

David Robertson is a Teaching Professor in the Department of Physics & Astronomy at the University of Notre Dame. Previously, he served as a faculty member at Otterbein University from 2002 to 2024, where he chaired the Physics Department for twelve years and led initiatives in undergraduate research. He also served as Otterbein’s Director of Undergraduate Research and Creative Work from 2015 to 2019. His research focuses on theoretical physics, including elementary particle physics, computational tools for quantum field theories, and Hamiltonian approaches to strongly interacting systems. Education: B.S. (with Honors), University of California, Los Angeles, 1984 Ph.D., University of California, Santa Barbara, 1990 Research Interests: Dr. Robertson specializes in high-performance computing for precision calculations in quantum field theories, light cone formalism, and particle physics phenomenology. He emphasizes bridging theoretical advancements with practical computational methods. Awards: 2017 Otterbein University Teacher of the Year Advising & Grants: While his current role at Notre Dame is not detailed, his prior leadership in undergraduate research and teaching highlights a commitment to mentorship and institutional development. Grants and specific advising roles are not explicitly listed here.

• Data Science
• Artificial Intelligence Explainability
• Web Science
• +۵ مورد دیگر

Marco Brambilla is a Professor at Politecnico di Milano and a Lecturer at Università della Svizzera italiana (USI) . He leads the Data Science Lab at Politecnico di Milano's Department of Electronics, Information and Bioengineering (DEIB) and serves as director of Computer Science and Engineering B.Sc. and M.Sc. curricula . Research focus on data science, AI explainability, web science, crowdsourcing, model-driven development, and social media analytics Co-inventor of the OMG IFML standard and holder of 2 patents on crowdsourcing and multi-domain search Founder of four startups: WebRatio, Fluxedo, Servitly, and Quantia His recent publications explore: Graph-based Retrieval Augmented Generation for energy efficiency Human-AI interaction analysis through live streaming platforms Model-driven approaches for multiexperience AI interfaces Explainable AI with human-in-the-loop validation Scientific contributions include: Best paper awards at international conferences Associate editor role at SIGMOD Records Editorial contributions to the PERISCOPE H2020 project on pandemic impacts He actively participates in European research initiatives such as: TRIGGER project on EU global governance PERISCOPE for pandemic preparedness

Meltem Aksoyمشاهده پروفایل

دانشیار

• Sustainable Urban Development
• Social Housing Practices
• User Participation in Design
• +۷ مورد دیگر

Meltem Aksoy is an Associate Professor at the Department of Architecture, Istanbul Technical University. Her academic work spans urbanization processes, social housing practices, and digital design technologies, with a particular focus on user participation and ecological sustainability in the built environment. Current affiliation: Department of Architecture, Istanbul Technical University Research themes: Composite cities, informal settlements, parametric design, ambient intelligence Her research explores: Intersections of digital technologies and spatial perception Methodologies for participatory social housing Computational approaches to architectural decision-making Temporal-spatial dynamics in contemporary urbanization Recent publications demonstrate trends in: AI-assisted design negotiation frameworks Fuzzy logic applications in architectural performance Critical analyses of composite urban structures Evolution of home-street relationships She has supervised 33 graduate theses spanning topics from: Architectural essay films Political space narratives Smart facade technologies Urban data representation

Elena Vazquez Peñaمشاهده پروفایل

دانشیار

• Computational Design
• Smart Materials
• Adaptive Building Systems
• +۴ مورد دیگر

Elena Vazquez Peña is an Associate Professor at Umeå School of Architecture, Umeå University. She holds a Ph.D. in Architecture from Penn State and a professional degree from Universidad Nacional de Asunción. Her work bridges computational design, smart materials, and architectural innovation. She has pioneered research in adaptive building systems using bistable materials, shape memory alloys, and kinetic structures. Education: Ph.D. in Architecture, Pennsylvania State University Master of Science in Architecture, Pennsylvania State University Graduate Certificate in Additive Manufacturing, Pennsylvania State University Professional Degree in Architecture, Universidad Nacional de Asunción Research focuses on: Smart materials for adaptive buildings Computational tools for kinetic façade design Sustainable architectural technologies Parametric design methodologies Recent projects include developing shape-morphing devices with shape memory alloys and exploring low-cost acoustic solutions through origami patterns. Awards : 2023 ARCC Dissertation Award 2022 Rustum & Della Roy Innovation Award 2018 ARCC King Medal 2016-2018 Fulbright Scholar Teaching emphasizes project-centered learning using parametric design tools. Courses include Architecture Studio, Robotics in Architecture, and Shape Grammars. She leads the Digital Materials Research Group and collaborates on the UmArts Art & AI research project.

Susan Detmerمشاهده پروفایل

دانشیار

• Infectious Diseases
• Virology
• Swine Health
• +۳ مورد دیگر

Susan Detmer is an Associate Professor in the Department of Veterinary Pathology at the University of Saskatchewan. She specializes in molecular and phenotypic characterization of influenza A viruses and focuses on infectious diseases of swine, particularly porcine reproductive and respiratory syndrome (PRRS), influenza A, and porcine circovirus type 2. Dr. Detmer teaches undergraduate systemic pathology, necropsy rotations, and graduate mammalian pathology courses. Her research explores viral pathogenesis in swine, including maternal-fetal interface interactions during PRRSV infections, Brachyspira-associated colitis, and influenza A virus dynamics. She has contributed to diagnostic methods for swine respiratory pathogens and vaccine efficacy studies. Publications highlight her work on viral transmission mechanisms, placental pathology in infected gilts, and global influenza A virus migration. Her studies emphasize clinical and molecular approaches to understanding swine disease epidemiology, with a focus on improving diagnostic and preventive strategies. No scientific awards or grants are explicitly listed in the provided materials. She advises students in her courses but no formal advisee list is available.

• Computer Science
• Algorithm Theory
• Game Theory
• +۳ مورد دیگر

Professor Mavronicolas Marios is a faculty member in the Department of Computer Science at the University of Cyprus. His academic journey includes a Diploma in Electrical Engineering (Summa Cum Laude) from the National Technical University of Athens (1985) and a Ph.D. in Computer Science from Harvard University (1992). His research focuses on Algorithm Theory, Game Theory, Distributed Computing, Networking, and Internet Systems. He has held visiting positions at institutions such as the University of Connecticut and the University of Paderborn. Over 100 publications in top-tier venues highlight his contributions to computational complexity, Nash equilibria, and network security. His work bridges theoretical computer science with practical applications, emphasizing strategic decision-making and distributed systems. Research areas include the computational complexity of Nash equilibria, game-theoretic models for network security, and algorithmic challenges in distributed systems. He has explored topics like risk-averse equilibria, congestion games, and the structural properties of multi-player games. His recent work addresses decision problems in win-lose scenarios and the existence of equilibria under varying valuation functions.

Björn Annighöferمشاهده پروفایل

استاد

• Avionics Systems
• Self-Adaptive Systems
• Cybersecurity
• +۵ مورد دیگر

Björn Annighöfer is a Professor at the Institute of Aviation Systems (ILS) at the University of Stuttgart, where he serves as Managing Director. His work focuses on complex, digital, and safety-critical avionics systems, including self-adaptive platforms, cybersecurity, and AI-supported aerospace systems. Research interests include: Self-adaptive avionics platforms Model-based cybersecurity frameworks Integrated Modular Avionics (IMA) development Virtualization and middleware for safety-critical systems AI applications in aerospace Automated development and certification processes Recent publications highlight advancements in PLUG-AND-FLY avionics, security assessment using large language models, and domain-specific modeling tools. He leads a team of ~25 scientists at ILS, which operates modern labs, flight simulators, and research aircraft for testing.