جستجوی استاد راهنمای دانشگاهی

Brett J. Borghettiمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۱۲ مورد دیگر

Dr. Brett J. Borghetti is a Professor of Computer Science in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT), Graduate School of Engineering and Management, Wright-Patterson AFB, OH. He was promoted to Professor in July 2022, following prior appointments as Associate Professor (2017) and Assistant Professor (2008/2013). His expertise lies in artificial intelligence, machine learning, deep learning, cybersecurity, and human-machine teaming. Education: Ph.D. in Computer Science, University of Minnesota, Twin Cities (2008) M.S. in Computer Systems, Air Force Institute of Technology (1996) B.S. in Electrical Engineering, Worcester Polytechnic Institute (1992) Dr. Borghetti's research focuses on applying machine learning to physical science sensors (hyperspectral, seismic, RF), cybersecurity, and enhancing human-machine team performance. He teaches graduate courses in machine learning, AI, data security, and algorithm design, and advises numerous MS and PhD students in areas such as sensor exploitation, cognitive workload, and cyber situational awareness. His recent publications demonstrate strong trends in deep learning for multimodal sensor fusion, nuclear security, and neuroergonomics. Scientific Awards: AETC Educator of the Year (2021, Civilian) AFIT Ezra Kotcher Teaching Award (2021) AFIT Teaching Excellence Award (2019) AF STEM Outstanding Science and Educator Award (2015) Multiple Eta Kappa Nu Outstanding Instructor Awards Air Force Meritorious Service Medal and other military honors Dr. Borghetti has advised numerous graduate students and led research projects with significant funding and applications in defense and national security. He has directed research in AI-driven sensor analysis, cyber defense systems, and adaptive automation. His work often involves collaboration with national labs and DoD agencies. He has contributed to major research initiatives in human factors, cyber intruder detection, and machine learning for operational environments. Labs and Research Teams: His work is associated with AFIT's research in cyber security, sensor exploitation, and human-machine systems. He collaborates with teams working on the Cyber Intruder Alert Testbed (CIAT), neuroergonomic modeling, and machine learning for defense applications.

• Compassion at work
• Mindfulness at work
• Organisational justice
• +۷ مورد دیگر

Samantha Su-Hsien Sim is an Assistant Professor at Nova School of Business and Economics (NOVA SBE) in Portugal, where she teaches Organisational Behaviour and Human Resource-related courses. She is affiliated with the Leadership for Impact Centre at Nova SBE and the Mindfulness Initiative at Singapore Management University, and serves as a faculty adviser for the student-led Nova Mindfulness Club. Doctorate in Business, Singapore Management University Bachelor in Social Science, Singapore Management University Master in Social Science, Tilburg University Her research centers on compassion and mindfulness in the workplace, organisational justice, and cross-cultural differences. She investigates how compassion influences workplace behavior and leadership, and how mindfulness affects cooperation and negotiation outcomes. Her work bridges organizational psychology and management, with implications for employee well-being, ethical leadership, and inclusive organizational cultures. Her recent publications explore mindfulness-based training, corporate well-being programs, and algorithmic fairness in employment. The research spans topics like psychological well-being, negotiation dynamics, and public policy, showing a strong interdisciplinary focus on human-centered organizational practices. Published in top journals including Journal of Applied Psychology , Academy of Management Journal , and Organizational Behavior and Human Decision Processes She advises student research through the Nova Mindfulness Club and contributes to research grants related to leadership, mindfulness, and organizational justice. Her collaborative network includes scholars from Singapore, Europe, and North America, reflecting her cross-cultural research orientation. She is active in research centers focused on leadership impact and mindfulness, contributing to both academic and practical applications in organizational settings.

• Photonics
• Laser Technology
• Machine Learning
• +۵ مورد دیگر

Professor Robert Eason is a leading academic at the University of Southampton, specializing in photonics and laser technology. His research spans interdisciplinary areas combining Machine Learning , Medical Diagnostics , and Microfluidics . Research Interests : Eason focuses on AI-driven laser applications, including deep learning for phototherapy , autonomous laser machining , and low-cost paper-based diagnostic devices . His work bridges photonics with biomedicine and advanced manufacturing. Recent Publications : His 2025 article in Scientific Reports explores AI simulations for psoriasis treatment, while 2024-2022 works address laser-controlled microfluidics, deep learning in microscopy, and reinforcement learning for laser machining. Supervision : He supervises PhD student Georgia Mourkioti in laser-based research projects. External Roles : Eason has served as a speaker at international conferences including the International Symposium on Laser Precision Microfabrication (2018), LAISER (2019), and Deep Learning for Control of Light-Matter Interactions (2022).

• Human-Computer Interaction
• Social Media Analysis
• AI-Mediated Communication
• +۵ مورد دیگر

Mor Naaman is a Professor at Cornell University specializing in Human-Computer Interaction, Social Media Analysis, and AI-Mediated Communication. With a prolific publication record spanning over two decades, his research focuses on how people interact with social computing systems, particularly examining trust, information exposure, and community dynamics in online environments. His research interests span several interconnected domains: Human-Computer Interaction with emphasis on social media platforms, AI-Mediated Communication examining how AI systems influence human communication patterns, Misinformation Detection and analysis of information ecosystems, Location-Based Social Networks and community awareness systems, and Trust in Online Systems. His work often bridges technical and social aspects of computing, with publications appearing in top venues like CHI, CSCW, and ICWSM. Analysis of his recent publications (2022-2025) reveals a strong focus on the emerging challenges of AI in social contexts, particularly examining AI-generated content, trustworthiness evaluations of AI systems, and the social implications of generative AI. His research shows consistent interest in understanding community dynamics across platforms like Reddit, Facebook, and Twitter, with recent work examining hyperlocal communities, news consumption patterns, and cross-cultural aspects of AI-mediated communication. Mor Naaman has mentored numerous students and collaborators, including Xiao Ma, Yiqing Hua, and Marianne Aubin Le Quéré, who frequently appear as co-authors on his publications. His work demonstrates strong interdisciplinary connections between computer science, social science, and communication studies. His research methodology typically combines large-scale data analysis of social media platforms with user studies and system design, contributing both theoretical insights and practical applications for designing more effective social computing systems. Recent projects have examined AI writing assistants, community governance of AI content, and the cultural implications of AI-mediated communication.

Soumaya Cherkaouiمشاهده پروفایل

استاد

• Artificial Intelligence
• Telecommunications Networks
• Quantum Computing
• +۶ مورد دیگر

Soumaya Cherkaoui is a Full Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. Previously, she served as a Full Professor at Université de Sherbrooke and held industrial roles as an aerospace project manager. Her research integrates artificial intelligence with telecommunications, focusing on quantum computing, frugal edge intelligence, and applications in connected vehicles and IoT. Current Position: Full Professor, Polytechnique Montréal Prior Academic Role: Full Professor, Université de Sherbrooke Industry Experience: Aerospace Project Manager Research Interests: Convergence of AI and communications, quantum computing for networking, frugal intelligence at the edge, and applications in autonomous vehicles, industrial IoT, and smart grids. She leads government and industry-funded projects, including a $6 million quantum initiative in 2025. Recent Publication Trends: Her 2025–2024 work emphasizes quantum-enhanced anomaly detection (via QGANs), Open RAN slicing with quantum optimization, and reinforcement learning for secure cognitive radio networks. Topics span 5G/6G, vehicular networks, and zero-trust architectures. Scientific Awards: IEEE Communication Society Distinguished Lecturer (2020) ACM Mirela Notare Award (2023) IEEE Bio-Inspired Computing STC Leadership Award (2023) N2Women: Stars in Networking and Communications (2023) Best Paper Awards at IEEE ICC 2017, IEEE LCN 2021, ICCSPA 2024 Advising and Grants: Supervised 3 Master's students in 2024, with research on quantum GANs and federated learning for vehicular networks. Secured grants like the $6 million quantum project (2025) and participated in CFI-QC government funding (2022). Editorial and Leadership: Served as Associate Editor for IEEE, Wiley, and Elsevier journals. Chaired conferences like IEEE LCN 2019 and IEEE ICC2025, and held leadership roles in IEEE Communications Society committees.

Leah Findlaterمشاهده پروفایل

دانشیار

• Accessibility
• Human-Centered AI
• Human-Computer Interaction
• +۳ مورد دیگر

Leah Findlater is an Associate Professor in the Department of Human-Centered Design & Engineering at the University of Washington (College of Engineering). She also holds adjunct and affiliate appointments in Computer Science & Engineering and Disability Studies, respectively, and serves as Associate Director of UW CREATE (Center for Research and Education on Accessible Technology and Experiences). Since 2021, she has led a research team in AI and accessibility at Apple. Her research focuses on creating adaptive technologies that accommodate individual needs, particularly for people with disabilities. Key areas include touchscreen personalization, machine learning interfaces, and sound recognition systems for deaf and hard-of-hearing users. Funding sources include NSF, DoD, and major tech companies. Recent work explores AI-driven tactile graphics, visual privacy management for blind users, and sound recognition systems. Her research combines lab studies, field deployments, and qualitative methods. NSF CAREER Award (2014) She advises through the Inclusive Design Lab, emphasizing mixed-methods research and collaborations with disability communities.

Pouya Bashivanمشاهده پروفایل

استادیار

• Computational Neuroscience
• Machine Learning
• Artificial Neural Networks
• +۶ مورد دیگر

Pouya Bashivan is an Assistant Professor in the Department of Physiology at McGill University's Faculty of Medicine. His research focuses on developing computational models to explain and regulate neural responses during visual tasks requiring memory, combining machine learning, neuroscience, and cognitive science. Education : Ph.D. in Computer Engineering (2016), Postdocs in Machine Learning (2020) and Computational Neuroscience (2016-2020) His lab investigates: Topographical neural networks for visual cortex simulation Massively-multitask models for prefrontal cortex Saccade-driven visual exploration models Predictive hippocampus models for episodic memory Recent publications explore adversarial robustness, memory-augmented networks, and brain-state decoding. Current projects emphasize causal models, brain-AI alignment, and translating computational neuroscience into therapeutic applications. The lab is located in the McIntyre Medical Sciences Building, Room 1117, Montreal, Quebec.

Liadh Kellyمشاهده پروفایل

استادیار

• Applied Artificial Intelligence
• Intelligent Search
• Ubiquitous Computing
• +۳ مورد دیگر

Liadh Kelly is an Assistant Professor in the Department of Computer Science at Maynooth University's Faculty of Science & Engineering. She supervises PhD students in applied artificial intelligence, focusing on intelligent search, ubiquitous computing, and multimodal information access. She is affiliated with the ADAPT SFI Research Centre, SFI Centre for Research Training in Foundations of Data Science, and Human Health Institute. BSc in Computer Science MSc (Research) in Computer Science PhD in Computer Science Her research explores context-sensitive retrieval and evaluation methodology in AI-driven systems. Key areas include ubiquitous computing for personal data analysis, deep learning classification for mental wellness indicators, and multimodal lifelogging integration. Recent publications focus on urban mental wellbeing classification , contextual cue analysis , and AI-driven health search systems . Articles address smart city applications , consumer health search , and cross-lingual medical retrieval . Professional roles include Doctoral Consortium Chair at ECIR 2023 and Programme Committee member for SIGIR and ICWSM conferences. She leads grants for 4-year PhD studentships with stipend and fee coverage.

Sara Bernardiniمشاهده پروفایل

استاد

• Artificial Intelligence
• Automated Planning
• Robotics
• +۴ مورد دیگر

Professor Sara Bernardini is a leading academic in Artificial Intelligence at the University of Oxford's Department of Computer Science, where she holds a joint appointment as a Tutorial Fellow at Mansfield College. Her research specializes in decision-making for autonomous systems, automated planning, and robotics, with applications in extreme environments like space missions, nuclear decommissioning, and offshore energy. She bridges theoretical AI with real-world challenges through projects funded by Innovate UK, EPSRC, NERC, and the Alan Turing Institute. Her research interests span: Autonomous Systems : Developing agents that support humans in complex cognitive tasks. Automated Planning : Algorithms for goal recognition, pathfinding, and multi-agent coordination. Robotics : Solutions for subterranean exploration, offshore wind farms, and UAV operations. AI Safety : Risk-aware autonomous systems and interpretable decision-making. Bernardini's publications emphasize algorithmic robustness in path planning, multi-agent coordination , and real-world AI deployments . Recent work explores goal legibility in uncertain environments, energy-efficient robotics, and AI education tools. Her 65+ papers in top venues (e.g., AIJ, JAIR, ICAPS) show a trend toward safety-critical applications and human-AI collaboration. Awards & Leadership: ICAPS-2020 Best Paper Honorable Mention Executive Council Member, Association for the Advancement of Artificial Intelligence (AAAI) Program Chair, International Conference on Automated Planning and Scheduling (ICAPS 2024) Associate Editor, Artificial Intelligence Journal She leads interdisciplinary teams for projects like autonomous offshore wind farm maintenance and modular robots for extreme environments. As Principal Scientist at the UK National Oceanography Centre, she advanced marine robotics. She mentors PhD candidates and collaborates globally (e.g., NASA Ames, MIT).

Sara Magliacaneمشاهده پروفایل

استادیار

• Causality
• Causal Representation Learning
• Causality-inspired Machine Learning
• +۴ مورد دیگر

Sara Magliacane is an Assistant Professor at the University of Amsterdam , affiliated with the Amsterdam Machine Learning Lab (AMLab) and the Informatics Institute . She also holds a Research Scientist position at the MIT-IBM Watson AI Lab and has been an ELLIS Scholar since 2022. Education PhD in Artificial Intelligence (2017), VU Amsterdam MSc in Computer Engineering (2011), Politecnico di Milano BSc in Computer Engineering (2008), Università degli Studi di Trieste Research Focus : At the intersection of Causality and Machine Learning , her work addresses Causal Representation Learning from high-dimensional data (images, sequences) Causal Discovery in latent confounder scenarios Causality-inspired Reinforcement Learning for robustness and adaptability Neurosymbolic AI for theoretical guarantees Publication Trends : Her recent work explores Factored adaptation in non-stationary environments (NeurIPS 2022) Temporal causal identifiability (ICML 2022) Binary interaction-based causal discovery (UAI 2023) Safe exploration in visual RL (HSCC 2021) Structure learning lower bounds (NeurIPS 2020) Scientific Recognition : ELLIS Scholar (2022–present) Spotlight presentations at ICML 2022 and ICLR 2022 Advising & Collaborations : Currently supervising 6 PhD students at the University of Amsterdam and AUMC, with 12 alumni advisees. Collaborates with researchers at MIT-IBM Watson AI Lab, Simons Institute, and TUM.

• Analog and mixed-signal integrated circuit design
• Computer-aided design (CAD) of electronic circuits
• Design automation (EDA)
• +۵ مورد دیگر

Georges Gielen is Full Professor in the Department of Electrical Engineering (ESAT) at KU Leuven, Belgium, and part-time Research Director at imec. He has held multiple leadership roles including Chair of ESAT Department (2012-2013, 2020-2024) and Vice-Rector for Science, Engineering & Technology (2013-2017). His academic career spans over 30 years at KU Leuven, progressing from Assistant to Full Professor. His research focuses on analog and mixed-signal integrated circuit design automation , with expertise in CAD tools, design optimization, sensor interfaces, and neuromorphic systems. His work bridges hardware design with machine learning, particularly in hardware-efficient AI implementations and biomedical applications. He has pioneered techniques for automated analog circuit sizing, topology synthesis, and reliability-aware design in nanometer CMOS. Gielen has received numerous accolades including the IEEE CAS Mac Van Valkenburg Award (2015), IEEE CAS Charles Desoer Award (2020), and EDAA Achievement Award (2021). He holds an ERC Advanced Grant AnalogCreate and is an IEEE Fellow since 2002. As a prolific scholar, he has chaired major conferences including DATE (2006), ICCAD (2007), and ESSCIRC (2017). He has graduated over 55 PhD students through the MICAS research group at KU Leuven, currently supervising 13 doctoral candidates. His research team collaborates extensively with imec and industry partners on cutting-edge projects in carbon-aware AI accelerators, uncertainty-aware design, and neuromorphic sensor interfaces.

Nathan Fiskمشاهده پروفایل

استادیار

• Cybersecurity Education
• Online Safety
• Behavioral Cybersecurity
• +۷ مورد دیگر

Nathan Fisk is an Assistant Professor at the University of South Florida College of Education , specializing in cybersecurity education . His research bridges educational theory with cybersecurity practice, focusing on behavioral aspects, policy analysis, and socio-technical systems. Key research themes include: Understanding user motivations for adopting cybersecurity practices Designing privacy-preserving data collection methods Examining economic stressors' impact on online scam susceptibility Critiquing digital inequality in medical fundraising platforms His recent work explores AI-driven cybersecurity awareness campaigns and anti-oppressive pedagogies in online learning environments. Scientific Awards : EAGER grant (2021) for SaTC AI-Cybersecurity research Contact: fisk@usf.edu

• International Arbitration
• Mediation
• Alternative Dispute Resolution
• +۵ مورد دیگر

Marta Gonzalo Quiroga serves as a faculty member at King Juan Carlos University's School of Law, specializing in Private International Law with extensive contributions to international arbitration, mediation systems, and the intersection of artificial intelligence with legal frameworks. Her academic profile spans over two decades of scholarly work, thesis supervision, and active engagement in legal reform initiatives across European and Latin American jurisdictions. Her research focuses on the evolving landscape of Alternative Dispute Resolution (ADR) mechanisms, with particular emphasis on how artificial intelligence transforms family law arbitration, sustainable development goal integration in mediation practices, and cross-border legal harmonization. Recent publications demonstrate a strategic pivot toward technology's role in legal systems, examining AI applications in international arbitration while maintaining foundational work in traditional mediation frameworks and private international law. Academic leadership is evidenced through her direction of four doctoral theses addressing critical gaps in mediation practices across Ecuador, Spain, and Mexico, with research outputs contributing to emerging frameworks like the University Coexistence Law and transnational mediation protocols. Her collaborative work extends to European regulatory frameworks, particularly in developing standardized mediation practices across jurisdictions while addressing cultural and systemic differences. Professional engagement includes significant contributions to collective works on international dispute resolution, with recent chapters addressing psychosocial risks in digital-age conflict resolution and technological innovations in workplace mediation. Her scholarly impact is reflected in a publication record spanning 25 journal articles, 48 collective work contributions, 11 books, and consistent engagement with contemporary legal challenges through both theoretical and practical lenses.

Joo Heung Yoonمشاهده پروفایل

استادیار

• Machine Learning in Medicine
• Critical Care Medicine
• Hemodynamic Monitoring and Prediction
• +۳ مورد دیگر

Joo Heung Yoon, MD is an Assistant Professor of Medicine in the Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine at the University of Pittsburgh School of Medicine. His research develops machine learning models for predicting hemodynamic instability in critical care settings, with applications extending to space medicine environments. His educational background includes: MD from Catholic University of Korea, Seoul, South Korea (2002) Internal Medicine Internship at Maimonides Medical Center - SUNY Downstate (2007) Internal Medicine Residency at New York Medical College (2009) Research Fellowship at Massachusetts General Hospital / Harvard Medical School (2011) Research Fellowship at Beth Israel Deaconess Medical Center / Harvard Medical School (2014) Fellowship in Pulmonary and Critical Care Medicine at University of Pittsburgh School of Medicine (2017) Dr. Yoon specializes in identifying hidden pathologic patterns through machine learning, developing prediction models for shock, hemorrhage, and tachycardia using large-scale clinical data. His work bridges critical care medicine with AI, focusing on real-world ICU implementation through alert systems and user interfaces. He actively explores microgravity applications, aiming to create feasible prediction algorithms for resource-constrained space missions where timely high-stake decisions are critical. His publication trend (2018-2020) reveals consistent advancement in hemodynamic prediction models, transitioning from theoretical frameworks to practical implementation strategies. These works integrate supervised ML and deep neural networks to address circulatory shock, hemorrhage identification, and instability surrogates, demonstrating strong interdisciplinary collaboration between clinical medicine and engineering. Notable awards include: SCCM Gold Snapshot Award (2019) ATS Abstract Award (2018) Excellence in Clinical Service Award (2010) Partners in Excellence Award (2009) Richard D. Levere Teaching Award (2008) As Principal Investigator for NIH K23 grant GM138984 (2020-2025), Dr. Yoon leads research on machine learning-driven shock prediction models. He mentors medical students and house staff daily in the ICU, specializing in cardiopulmonary physiology teaching. His grant portfolio focuses on therapeutic strategies for circulatory shock in critically-ill patients, with strong industry-academic partnerships. Based at UPMC Montefiore, Dr. Yoon collaborates with Carnegie Mellon University's Machine Learning School and Pitt Engineering to develop clinical decision support systems. His team is designing graphic user interfaces for spaceflight applications where resource limitations demand highly efficient predictive analytics for hemodynamic crises.

• Media Linguistics
• Ethnomethodological Conversation Analysis
• Human-Machine Interaction
• +۶ مورد دیگر

Tim Moritz Hector is a Research Associate at the University of Siegen since 2020, affiliated with subproject B06. He completed his PhD in Applied Linguistics in April 2024 with a dissertation on voice assistants as conversational participants. His research focuses on media linguistics, ethnomethodological conversation analysis, human-machine interaction, linguistic praxeology, and cultural linguistics. Education: German (linguistics), political science, and educational science (2012–2019) at Münster and Bonn Academic roles: Student assistant (2015–2019), research assistant (2019), and current research associate Research Themes: Hector investigates voice user interfaces, domestication of smart technologies, and interactional practices between humans and AI systems. His work bridges linguistic analysis with digital media studies, focusing on how voice assistants reshape social practices in households. Article Trends: Recent publications emphasize smart speaker domestication , human-machine agency , voice interface practices , sensory smart home systems , and data practices in AI adoption . He explores how voice assistants become embedded in daily routines through linguistic and praxeological frameworks. Academic Affiliations: Member of the Society for Applied Linguistics (GAL) and German Cultural Studies Society (KWG). Former Wikimedia Deutschland e.V. board chair and UNO-Flüchtlingshilfe e.V. supervisory board member. Conference Contributions: Active in conferences like IPrA, Social Interaction, and COST networks. Key presentations include topics on multisensory interaction, invectives in voice technology use, and responsive smart home systems. Collaborations: Co-organized major conferences including Machine–Body–Space (2024) and Voice Assistants in Private Homes (2023) with interdisciplinary teams from Siegen, Bremen, and Brussels.