جستجوی استاد راهنمای دانشگاهی

Jacob Joshua Shilaمشاهده پروفایل

استادیار

• Sustainable Aviation
• Environmental Impacts of Aviation
• Techno-Economic Analysis
• +۲ مورد دیگر

Dr. Jacob Joshua Shila serves as an Assistant Professor in the School of Aviation at Bowling Green State University (BGSU), Ohio, focusing on sustainable aviation solutions through research in environmental impact mitigation, sustainable fuels, and techno-economic modeling for aircraft and airport operations. His work bridges engineering, economics, and policy to develop financially viable green aviation technologies. Education: Ph.D. in Aviation Technology, Purdue University (2017) M.S. in Aviation and Aerospace Management, Purdue University (2014) B.S. in Aerospace Engineering, Missouri University of Science and Technology (2012) Dr. Shila's research centers on sustainable aviation fuels, Advanced Air Mobility (AAM) infrastructure and workforce development, and aviation sustainability education. He investigates techno-economic optimization of emerging technologies, emphasizing real-world applicability for reducing environmental footprints while maintaining industry profitability. His industry background at Volkswagen of North America in emissions modeling informs his applied research approach. Recent publications reveal strong interdisciplinary trends, particularly in AAM integration into airport systems, biofuel economics (e.g., camelina and pennycress-derived jet fuels with by-product valorization), and educational adaptations for sustainable aviation. Studies frequently employ case-based methodologies and computational modeling to address regulatory compliance, infrastructure readiness, and skill gaps in emerging aviation sectors. Scientific Awards: No scientific awards mentioned in the provided text. Dr. Shila actively mentors students as faculty advisor for the BGSU chapter of the American Association of Airport Executives (AAAE), emphasizing practical application of concepts and career development. His teaching philosophy prioritizes clear communication of objectives and real-world relevance, extending mentorship beyond the classroom. While specific grant funding details are absent, his prior industry experience in emissions simulations provides critical context for his research on sustainable aviation transitions.

Lisa Miracchiمشاهده پروفایل

استادیار

• Philosophy of Mind
• AI Ethics
• Robotics Ethics
• +۴ مورد دیگر

Lisa Miracchi Titus is an Assistant Professor of Philosophy at the University of Denver, previously serving as an Associate Professor with tenure at the University of Pennsylvania. She is an IEEE Tech Ethics Ambassador and member of the IEEE SA Working Group on the Ethics of LAWS. Her research focuses on the nature of intelligence, AI ethics, and the integration of ethical considerations into AI development. She holds a Ph.D. in Philosophy (with a Cognitive Science certificate) from Rutgers University and an AB in Philosophy from Harvard. Her work bridges philosophy, cognitive science, robotics, and ethics, addressing questions about intelligent systems, agency, and ethical AI applications. She received an NEH grant for her book project on effective and ethical intelligence research, emphasizing feminist and social justice perspectives. Education: Ph.D. in Philosophy (Rutgers, 2014), A.B. in Philosophy (Harvard, 2009). Previous positions include Bersoff Assistant Professor at NYU and tenure-track roles at Penn. She is committed to academic diversity, having led wellness initiatives for graduate students and participated in LGBTQ+ advocacy. Her research also explores the ethical implications of AI’s feminization and the future of human-AI collaboration. Research Interests: Philosophy of AI, ethics of robotics, embodied cognition, and feminist approaches to technology. She advocates for interdisciplinary collaboration to ensure AI systems align with ethical, social, and cognitive science principles. Her current projects include the integration of ethical frameworks into AI design and the societal impacts of AI labor. Awards and Fellowships: National Endowment for the Humanities Grant (2022), NEH Fellowship (2021). Her work appears in journals like Journal of Philosophy , Philosophical Studies , and Frontiers in Neurorobotics . Labs and Collaborations: Affiliated with the GRASP Lab (Robotics) and MindCORE (Cognitive Science) at Penn, and now contributes to Denver’s interdisciplinary initiatives. She balances academic rigor with personal advocacy for mental health, wellness programs, and LGBTQ+ inclusion in academia.

• Cybersecurity
• Explainable AI (xAI)
• Machine Learning
• +۵ مورد دیگر

Aleksandra Pawlicka is a prominent researcher specializing in cybersecurity , explainable AI , and disinformation detection . Her work bridges ethical considerations with technical innovations in network security and AI applications , particularly focusing on the intersection of human-robot collaboration , fake news analysis , and IoT vulnerabilities . Key research areas: Cybersecurity Ethics, AI Explainability, Disinformation Mitigation Notable collaborations: Marek Pawlicki, Rafal Kozik, Michal Choras Her publications analyze xAI challenges in intrusion detection, machine learning for network security, and ethical dilemmas in cybersecurity. She contributes to projects like ULTIMATE (robotic AI) and SWAROG (fake news detection), emphasizing transparency and practical implementation. Recent work explores adversarial attacks against AI systems , few-shot learning for cybersecurity, and neuro-symbolic reasoning for trustworthy AI. Her 2023 study on ChatGPT's impact on scientific communication highlights evolving technological and ethical landscapes in academic practices.

• Artificial Intelligence
• Automated Planning
• Temporal Reasoning
• +۴ مورد دیگر

Alfonso Emilio Gerevini is a prominent researcher in artificial intelligence with over 30 years of continuous academic contributions. His work spans theoretical foundations of automated planning to practical healthcare applications, with recent publications demonstrating significant impact in both traditional AI domains and emerging interdisciplinary areas. His research interests focus on automated planning systems , temporal reasoning , and multi-agent coordination , with recent expansion into healthcare applications using machine learning techniques. Gerevini has made fundamental contributions to planning algorithms, particularly in width-based search, case-based planning, and privacy-preserving multi-agent planning. His work on PDDL (Planning Domain Definition Language) has been influential in standardizing planning representations. Analysis of his 15 most recent publications reveals a strategic evolution from core planning research toward impactful healthcare applications, particularly during the COVID-19 pandemic. While maintaining his expertise in planning algorithms, he has successfully integrated machine learning techniques to address real-world medical challenges including radiology report analysis, prognosis prediction, and lab test interpretation. His work demonstrates exceptional versatility across both theoretical and applied domains of artificial intelligence. Gerevini maintains a robust collaborative network, primarily with Italian researchers including Ivan Serina, Alessandro Saetti, and Luca Putelli. His publications appear consistently in top-tier AI venues including Artificial Intelligence journal, Journal of Artificial Intelligence Research, and AAAI/ICAPS conferences. The collaborative patterns suggest he leads a significant research group focused on advancing planning systems while applying them to critical real-world problems.

• Model Engineering
• Web Engineering
• Process Engineering
• +۹ مورد دیگر

Gerti Kappel is a full professor at the Institute of Information Systems Engineering at TU Wien, affiliated with the Business Informatics Group (BIG). Since 2020, she has served as Dean of the Faculty of Informatics at TU Wien, previously holding the role of Dean’s team member responsible for research, diversity, and financial affairs (2016–2019). She previously held a full professorship in computer science (database systems) and led the Department of Information Systems at Johannes Kepler University Linz (1993–2001). Her research focuses on Model Engineering, Web Engineering, and Process Engineering, particularly in cyber-physical production systems. She has co-authored influential works such as UML@Work (2005), UML@Classroom (2015), and Web Engineering (2006). Key projects include leadership roles in Vienna Informatics Living Lab (2018–2019), MPM4CPS (2014–2019), and ARTIST (2012–2015), addressing topics like model versioning, cloud architecture modeling, and inter-organizational systems. Her recent articles explore circular systems engineering, IoT-based simulation environments, and model-driven approaches for time-series analytics and cloud applications. She actively contributes to academic governance, including managing the Office of the Dean (E199-01) and overseeing faculty services. Her work emphasizes bridging theory and practice through collaborative frameworks like ERPEL and TROPIC . Grants: Projects funded by Austrian Research Promotion Agency, European Cooperation in Science and Technology, Vienna Business Agency, and others. Advising: Supervised over 15 graduate theses, including recent works on model-driven techniques for railway planning, debugging frameworks for modeling tools, and cloud-based IDEs. Labs/Teams: Leads research within the Business Informatics Group (BIG) and collaborates with the Vienna Informatics Living Lab for applied systems engineering.

Marc Toussaintمشاهده پروفایل

استاد

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

Marc Toussaint is Full Professor leading the Learning & Intelligent Systems Lab at TU Berlin's EECS Faculty. His research integrates machine learning, optimization, and AI reasoning to solve fundamental robotics problems like physical reasoning and human-robot interaction. He holds a physics diploma from University of Cologne and PhD from Ruhr-Universität Bochum. Key research themes include: Task-motion planning integration Reinforcement learning for robotics Physical simulation and control Probabilistic inference methods Recent publications focus on efficient kinodynamic planning, belief space planning under uncertainty, and neural policy learning. He develops open-source robotic tools like the 'robotic python package' used in academic courses worldwide. Toussaint collaborates with Amazon Robotics and MIT CSAIL, and has held positions at Max Planck Institute and University of Stuttgart.

Flora Salimمشاهده پروفایل

استاد

• Machine Learning
• Time-series Analysis
• Spatio-temporal Data Mining
• +۵ مورد دیگر

Flora Salim is a Professor in the School of Computing Technologies at RMIT University. She serves as co-Deputy Director of the RMIT Centre for Information Discovery and Data Analytics (CIDDA) and an Associate Investigator of the ARC Centre of Excellence in Automated Decision Making and Society. Her research focuses on human behavior modeling, machine learning with time-series and spatio-temporal data, and edge AI applications in IoT and wearables. Flora has secured over $10M in research funding from ARC, industry partners, and government bodies. Notable awards include the 2021 PACM IMWUT Distinguished Paper Award, 2019 Humboldt-Bayer Fellowship, and RMIT's 2018 Research Impact Award. She leads the CRUISE research group and has held visiting professorships at the University of Kassel and University of Cambridge. Editorial roles: Associate Editor of PACM on IMWUT, Area Editor of Pervasive and Mobile Computing Steering Committee member of ACM UbiComp Her work bridges ubiquitous computing and machine learning, with applications in urban analytics, mobility, and health monitoring. Recent projects include self-supervised learning for multimodal data and forecasting with heterogeneous time-series. Supervision areas: Deep learning for sensor data, explainable AI, and wearable-based emotion sensing Teaching programs: Master of Artificial Intelligence and Master of Data Science

• Native American Studies
• Alaska Native Studies
• Indigenous Feminism
• +۵ مورد دیگر

Shari M. Huhndorf serves as the Class of 1938 Professor of Native American Studies within UC Berkeley's Department of Ethnic Studies. A Yup'ik scholar raised in Alaska, her work bridges academic research and Indigenous community engagement, focusing on Alaska Native sovereignty, cultural representation, and gendered land relations. She holds significant leadership roles including Chair of the Repatriation Committee at the National Museum of the American Indian. Her educational foundation includes: Ph.D. in Comparative Literature, New York University M.A. in Comparative Literature, New York University B.A. in English, University of Redlands Huhndorf's research interrogates the inseparability of Indigenous cultural systems from territorial sovereignty, with particular emphasis on Alaska Native communities. Her scholarship examines literary and visual representations through decolonial and feminist frameworks, analyzing how Indigenous peoples resist colonial erasure through cultural production. Current projects include a community-based history of the Alaska Native Claims Settlement Act developed with Roy Huhndorf. Analysis of her 15 most recent publications reveals consistent engagement with Indigenous land sovereignty, cultural resilience, and gendered spatial politics. Her work demonstrates evolving focus from foundational critiques of 'going native' tropes toward contemporary analyses of corporate tribalism and Indigenous health sovereignty, always centering Alaska Native epistemologies. Her honors include: Canadian Women's Studies Association Outstanding Scholarship Prize Alaska Federation of Natives President's Award UC Berkeley Distinguished Teaching and Mentor Awards Guggenheim, Ford, and Woodrow Wilson Fellowships As a dedicated mentor, Huhndorf has guided numerous graduate students while securing major research funding. Her current ANCSA project exemplifies community-engaged scholarship. Institutional affiliations span Berkeley's Center for Race and Gender, Joseph A. Myers Center for Research on Native American Issues, and the Designated Emphasis in Gender and Women's Studies. She actively shapes national discourse through service on the National Museum of the American Indian Board and previously chaired the MLA's Twentieth-Century American Literature Division. Her decade-long service with the CIRI Foundation demonstrates sustained commitment to Alaska Native educational advancement.

• Software engineering
• Safety critical systems
• Formal methods
• +۷ مورد دیگر

Ana Lucia Caneca Cavalcanti is a Professor of Computer Science at the University of York, leading the SER research group with expertise in formal methods for safety-critical systems. Her work bridges theoretical software engineering with practical applications in robotics and autonomous systems, emphasizing verification and reliability. BSc in Computer Science, Universidade Federal de Pernambuco, Brazil (1987) MSc in Computer Science, Universidade Federal de Pernambuco, Brazil (1990) DPhil in Computer Science, Oxford University (1997) Her research centers on formal methods, safety-critical software engineering, and real-time systems, with recent focus on robotics. She develops semantic frameworks for refining and verifying complex systems, particularly in adaptive robotic control. Her methodologies address concurrency, object-orientation, and tooling to ensure correctness in high-stakes environments like autonomous vehicles. Current publications reveal a cohesive trend: applying process algebra and architectural patterns to robotic software verification. This work targets safety assurance in adaptive systems, integrating formal semantics with physical robot modeling to mitigate risks in autonomous decision-making. Scientific recognition includes: Royal Society Wolfson Research Merit Award She directs major funded initiatives including RoboSapiens (European Commission, 2024-2026) on human-robot symbiosis, DOMINOS (EPSRC, 2024-2025) for AI disruption mitigation, and the UK Trustworthy Autonomous Systems Verifiability Node (EPSRC, 2020-2024). These projects involve industrial collaborations with Labman Automation and RoboTest, focusing on verifiable safety frameworks. As SER research group lead, she oversees a team advancing formal verification techniques for next-generation autonomous systems, with active partnerships in the High Integrity Systems ecosystem at York.

Fenglong Maمشاهده پروفایل

دانشیار

• Data Mining
• Health Care Informatics
• Machine Learning
• +۵ مورد دیگر

Fenglong Ma is an Associate Professor at Pennsylvania State University, affiliated with the Institute for Computational and Data Sciences and the Center for Socially Responsible Artificial Intelligence. His research focuses on data mining, healthcare informatics, machine learning, natural language processing, and multimodal learning. He holds a Ph.D. from the University at Buffalo (2019) and degrees from Dalian University of Technology. His work addresses challenges in federated learning, medical AI, adversarial robustness, and multimodal systems. Key contributions include innovations in quantization for large language models, federated knowledge injection, and medical vision-language benchmarking. Recent publications explore topics like collaborative fairness in federated learning, robust medical vision-language models, and adversarial attack mitigation. His research bridges theory and practical applications in healthcare, cybersecurity, and personalized recommendation systems. He leads the PSU Data Science Lab and collaborates on projects involving AI ethics, multimodal data integration, and scalable medical foundation models.

• Behavioral Economics
• Big Data
• Computational Social Science
• +۶ مورد دیگر

Giuseppe Alessandro Veltri is a Full Professor at the University of Trento's Department of Sociology and Social Research. His expertise spans Behavioral Economics, Big Data, Computational Social Science, and Social Psychology. He currently teaches courses such as 'Big Data' and 'Social Dynamics Lab' within the Data Science and Previsione Sociale programs. His research focuses on understanding human behavior through digital methodologies, including studies on vaccine hesitancy, darknet markets, and the psychological aspects of pandemics. Veltri is also actively involved in designing computational tools like TextualLLMap to analyze societal biases in AI systems. His work bridges theoretical frameworks with empirical data, emphasizing interdisciplinary approaches to social science challenges. Research interests include the application of computational methods to study risk perception, online behavior, and policy design. Recent studies explore how behavioral insights can improve public health strategies during crises and how transparency in digital platforms influences consumer decisions. Veltri's contributions also extend to methodological innovations, such as optimizing online experiments and addressing gaps in cognitive sociology.

• Criminology
• Gender studies
• Law in context
• +۴ مورد دیگر

Heather Melton is an Associate Professor in the Department of Sociology and Criminology at the University of Utah, affiliated with the College of Social and Behavioral Sciences. She has held academic positions since 2001, including Assistant Professor (2001–2008) and her current role since 2008. Her research focuses on criminology, gender studies, law in context, legal systems, and education systems. Her work addresses issues like sexual assault, domestic violence, racial disparities in criminal justice, and institutional responses to crime. Notable publications include studies on Clery Act compliance, marijuana legalization impacts, and intimate partner sexual assault using unsubmitted sexual assault kits. She has received prestigious teaching awards such as the Calvin S. & JeNeal N. Hatch Prize (2025) and the College of Social and Behavioral Sciences Superior Teaching Award (2011). Melton has led grants like the 'Domestic Violence in the Age of Covid-19' (2020–2021) and the 'Sexual Assault Kit Initiative' (2016–2019). Her teaching spans courses on criminology, women and crime, and murder in America, reflecting her commitment to education and advocacy. Key Research Themes: Sexual violence dynamics, criminal justice reform, victim advocacy, and policy analysis. Professional Service: Served on the Executive Board of the ASC Division of Women and Crime (2009–2010).

• Transportation Safety
• Automated Vehicles
• Human Factors in Transportation
• +۳ مورد دیگر

Rakotonirainy Andry is a Professor at Queensland University of Technology (QUT), affiliated with the Centre for Accident Research & Road Safety - Queensland (CARRS-Q). His research focuses on transportation safety, automated vehicles, human factors, and intelligent transportation systems (ITS). He leads interdisciplinary projects exploring driver behavior, connected vehicle technologies, and the societal impacts of automation. Key areas include accident prevention, human-vehicle interaction, and equity in transport systems. His work integrates machine learning, simulation studies, and behavioral analysis to address challenges in road safety. Notable contributions include studies on driver stress detection, automated vehicle acceptance, and the Australian Naturalistic Driving Study (ANDS). He collaborates with institutions globally, advancing innovations like connected vehicle pilots and multimodal AI for traffic safety. Research interests span automated driving systems, vulnerable road user protection, and policy implications of emerging technologies. His findings contribute to safer transportation policies and technologies, emphasizing both technical and human-centric perspectives.

Maryam Mehri Dehnaviمشاهده پروفایل

دانشیار

• High-Performance Computing
• Cloud Computing
• Machine Learning
• +۳ مورد دیگر

Maryam Mehri Dehnavi is an Associate Professor in the Department of Computer Science at the University of Toronto and a Principal Research Scientist at NVIDIA. She holds the Canada Research Chair in Parallel and Distributed Computing and leads the ParaMathics research group. Research focuses on high-performance computing , machine learning , sparse matrix optimizations , and compiler design for heterogeneous systems. Her work develops domain-specific languages , scalable numerical libraries , and auto-vectorization techniques for cloud and GPU platforms. Recent publications address LLM compression , sparse code translation , GPU kernel synchronization , and control flow optimization . Scientific recognition: Ontario Early Researcher Award (2021), NSF CRII Grant, NSERC New Frontiers in Research Fund. Current students: Mushegh Shahinyan , Martin Phan , Maryam Haghifam , and others. Former advisees: Kazem Cheshmi (NJIT), Zachary Blanco (MIT Lincoln Lab), Yuanxi Li (Amazon).

• Runtime Verification
• Formal Methods
• Concurrency Theory
• +۷ مورد دیگر

Adrian Francalanza is a Professor in the Department of Computer Science at the Faculty of Information and Communication Technology, University of Malta. His research is centered on formal methods, runtime verification, and concurrency, with a focus on monitorability and distributed systems. His research interests include: Runtime Verification and Monitor Synthesis Session Types and Protocol Safety Concurrency and Actor-Based Systems Branching and Linear-Time Temporal Logics Probabilistic and Decentralized Monitoring Formal Tools for Cyber-Physical and Distributed Systems The recent publications highlight a strong trend in theoretical and practical advances in monitorability, especially for branching-time and probabilistic systems. His work bridges theory with implementation, often resulting in tools like STMonitor and DetectEr. There is a clear emphasis on session types, runtime enforcement, and the verification of communication protocols in real-world systems such as REST APIs and SMTP. Scientific awards include: Distinguished Paper Award at ECOOP 2025 Best Paper Award at DisCoTec 2022 He has been actively involved in advising and organizing major academic events. He served as Program Chair for GandALF 2024 and 2025, FORTE 2024, and VORTEX workshops. He led a three-year project funded by Rannis on Theoretical Foundations for Monitorability in collaboration with Reykjavik University. He has received grants and recognition for developing practical tools such as DetectEr and STMonitor, which support runtime monitoring of Erlang and session-typed systems. He is associated with several research teams and labs, including: Runtime Verification and Monitorability Research Group at University of Malta Collaborators on the DetectEr project Developers of STMonitor and polyLarva tools International collaborators at Reykjavik University and beyond