جستجوی استاد راهنمای دانشگاهی

Cathy van Dyckمشاهده پروفایل

دانشیار

• Health Care
• Organizational Behavior
• Error Management
• +۳ مورد دیگر

Dr. Cathy van Dyck is an Associate Professor at the Vrije Universiteit Amsterdam (VU), holding positions in the Faculty of Social Sciences and Humanities, Department of Organization Sciences, as well as dual appointments at the Network Institute and the Organization & Processes of Organizing in Society (OPOS) research group. Her work focuses on organizational behavior, error management, and patient safety in healthcare settings. She is also the owner of The cat's Eye in Amsterdam since 2013. Her research explores how organizations handle errors, particularly in healthcare environments, emphasizing crew resource management (CRM) training, safety culture, and psychological safety. She has conducted studies in intensive care units (ICUs) and emergency departments, analyzing team dynamics and communication strategies. Her work also addresses professional identity threats and organizational learning mechanisms. Over 15 years, her articles consistently investigate error management frameworks, CRM implementation, and trust dynamics in teams. Recent studies highlight the importance of explicit communication in clinical settings and the mediating role of cognitive focus on task performance. Her research bridges aviation safety practices with healthcare, examining cross-industry applications. While no scientific awards are explicitly mentioned, her contributions to patient safety and organizational learning are recognized through her extensive publication record and collaborative activities. She has supervised 7 PhD theses and actively participates in academic activities such as lectures and editorial work, focusing on error management, trust, and safety culture. Dr. van Dyck is affiliated with multidisciplinary research teams including the Network Institute, which emphasizes innovation in complex societal challenges, and the OPOS group, dedicated to understanding organizational processes. Her teaching includes courses on policy communication and organizational issues, reflecting her expertise in translating research into actionable insights.

Ralph-Günther Holzمشاهده پروفایل

دانشیار

• Computer Science
• Cybersecurity
• Network Security
• +۳ مورد دیگر

Ralph-Günther Holz is an Associate Professor at the Digital Society Institute and the Department of Design and Analysis of Communication Systems. His work focuses on cybersecurity, network security, and federated learning. He is recognized for contributions to transport layer security, DNS dependencies, and cloud detection mechanisms. With an h-index of 14 and 886 citations, his research spans from foundational network protocols to applied security solutions. Recent collaborations include studies on Australian DNS dependencies and Dutch critical infrastructure security. His research interests include analyzing network vulnerabilities, optimizing secure communication in federated learning, and leveraging DNS records for cloud detection. Key contributions include work on web crawler security, dependency graph analysis, and threat intelligence. Holz has supervised one documented research project, contributing to applied networking and security domains. His work aligns with UN Sustainable Development Goals related to infrastructure resilience and digital inclusion. He frequently publishes in top venues like PAM, DSN, and CNSM, focusing on practical security solutions for modern communication systems.

Amanda Selwoodمشاهده پروفایل

پژوهشگر

• Healthy Brain Ageing
• Twins Research
• Cognitive Science
• +۳ مورد دیگر

Dr Amanda Selwood is a Researcher at the Centre for Healthy Brain Ageing (CHeBA) within the School of Psychiatry at UNSW Sydney. She coordinates the Older Australian Twins Study (OATS), focusing on distinguishing genetic and environmental influences on healthy brain aging. Her PhD in Human Cognition and Brain Science from Macquarie University explored collaborative remembering in twins and siblings. Prior roles include health services research at the Australian Institute of Health Innovation and memory research at UNSW Art & Design. Her research interests span healthy brain aging, twin methodologies, cognitive science, and gerontology. Education: PhD in Human Cognition and Brain Science, Macquarie University Research Focus: Dr Selwood’s work examines behavioral and environmental factors influencing cognitive aging, leveraging twin studies to disentangle genetic and social determinants. She investigates memory enhancement technologies for older adults and contributes to improving surgical patient outcomes through health services research. Her interdisciplinary approach bridges cognitive science, clinical psychology, and healthcare policy. Awards & Recognition: No scientific awards explicitly mentioned in available texts. Advising & Grants: No formal advisees listed. Contributions include protocol development for large-scale studies and ethical governance frameworks in healthcare research. Labs & Teams: Core member of the Older Australian Twins Study (OATS), collaborating with CHeBA’s multidisciplinary team to advance dementia research and healthy aging strategies.

Rishee Jainمشاهده پروفایل

دانشیار

• Urban Sustainability
• Building Energy Efficiency
• Data Analytics
• +۳ مورد دیگر

Rishee Jain is Associate Professor of Civil and Environmental Engineering at Stanford University. His research develops data-driven solutions for urban sustainability challenges at the intersection of civil engineering, data science, and social science. The Stanford Urban Informatics Lab focuses on: (1) Socio-spatial dynamics of commercial building energy use, (2) Data-driven urban building benchmarking, (3) Sustainability planning in built environments, (4) Coupled urban system dynamics using machine learning. Recent projects analyze agricultural expansion impacts on biodiversity and economic valuation in forest-agriculture landscapes. Publications demonstrate a strong focus on urban building energy modeling (UBEM), machine learning applications for sustainability, occupant behavior analytics, and equity dimensions of energy systems. Recent work increasingly incorporates generative AI, wearable sensors, and spatial justice frameworks.

Jat Singhمشاهده پروفایل

استاد پژوهش

• Algorithmic Accountability
• AI Governance
• Data Privacy & Protection
• +۶ مورد دیگر

Dr. Jat Singh is a Research Professor at the University of Cambridge's Department of Computer Science and Technology (Computer Laboratory), leading the Compliant and Accountable Systems research group. His interdisciplinary work bridges computer science and law, focusing on technology's legal and regulatory compliance, governance of AI/ML systems, and ethical data practices. He co-chairs the Trust & Technology Initiative and is a Fellow of the Alan Turing Institute. Education: PhD in Computer Science (Distributed Systems & Security) from the University of Cambridge, with prior legal studies. Professional background includes roles in IT services, a medical IT startup, and consulting, emphasizing governance-intensive sectors like healthcare and judiciary. Research interests include accountability in AI, IoT compliance, data justice, and ethical algorithmic systems. Notable projects include RAInS (accountability in AI), legally-compliant IoT frameworks, and data governance in modern slavery contexts. His work explores transparency, fairness, and auditability in technology. Scientific Awards: EPSRC Fellowship and Alan Turing Institute Fellowship. Active in tech-policy advising, collaborating with governments, regulators, and civil society. Teaching: Leads the Technology, Law & Society module in the Advanced Computer Science MPhil. Supervises student projects on algorithmic accountability, security, and societal impacts of technology. Labs/Teams: Heads the Compliant & Accountable Systems Group and contributes to the Trust & Technology Initiative, advancing interdisciplinary research on technology's societal implications.

Pramod K. Varshneyمشاهده پروفایل

استاد

• Distributed sensor networks
• Data fusion
• Statistical inference
• +۴ مورد دیگر

Pramod K. Varshney is a Distinguished Professor at Syracuse University's Department of Electrical Engineering and Computer Science, within the College of Engineering & Computer Science. He also holds adjunct professorships at Upstate Medical University (Radiology) and Xidian University (China). His research focuses on distributed sensor networks, data fusion, machine learning, and signal processing, with applications spanning defense, healthcare, and IoT. Varshney has led over four decades of research funded by major agencies like DoD, NSF, and industry partners. Education: PhD (Electrical Engineering, University of Illinois, 1976), MS (1974), BS (1972). His research interests emphasize foundational aspects of data/information fusion, sensor networks, and AI-driven analytics. Notable contributions include pioneering work in distributed detection theory and secure inference in adversarial environments. Recent publications highlight advancements in federated learning, anomaly detection, and multi-target tracking. Varshney has been honored with prestigious awards such as the IEEE Fellow (1997), Yaakov Bar-Shalom Award (2018), and Syracuse University's Chancellor’s Lifetime Achievement Award (2023). He has advised numerous PhD and Master’s students, contributing to over 350 publications, including seminal books like Distributed Detection and Data Fusion (Springer, 1997). He has directed Syracuse's CASE (Center for Advanced Systems and Engineering) and actively collaborates with global institutions. His work bridges theoretical advancements with real-world applications in healthcare imaging, cybersecurity, and autonomous systems.

Victor Akinwandeمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Victor Akinwande is a doctoral researcher at Carnegie Mellon University's Computer Science Department under advisor J. Zico Kolter. His research focuses on robust machine learning systems, causal inference for global health applications, and advancing vision-language models through generative modeling techniques. He holds an MSc in Information Technology (CMU, 2016–2018) and a BSc in Computer Science from the University of Ilorin (2011–2015). His work spans key areas including adversarial robustness, generalization bounds for prompt-based learning, and causal effect estimation in public health. Notable contributions include HyperCLIP (2024), AcceleratedLiNGAM (2024), and foundational work on subset scanning for anomaly detection in health data (2020–2022). Victor has been recognized with an Outstanding Paper Award (ICLR 2024 workshop) and a Distinguished Paper Award Nomination (AMIA 2022). His research bridges theoretical machine learning advancements with practical applications in global health systems and AI safety.

William Sandersمشاهده پروفایل

استاد

• Cybersecurity
• Formal Modeling
• Network Security
• +۲ مورد دیگر

Dr. William Sanders is a Professor in the Computer Science Department at Carnegie Mellon University, with affiliated appointments in the Office of the President. His research develops formal methods for cybersecurity, including tools like CyberSAGE for security argument evaluation and techniques for assessing cyber-physical infrastructure vulnerabilities. Research Focus Key areas include: Security metrics and risk assessment frameworks Intrusion detection for software-defined networks Cyber-physical system protection (power grids, IoT) Formal verification of network protocols His work integrates game theory, stochastic modeling, and machine learning for adaptive security. Theoretical Contributions Developed ADVISE meta model formalism for security quantification and ontological frameworks for threat modeling in critical infrastructure.

Liu Leqiمشاهده پروفایل

استادیار

• Large Language Models
• Human-Centered Machine Learning
• AI Ethics and Societal Impact
• +۳ مورد دیگر

Liu Leqi is an Assistant Professor in use-inspired AI at the University of Texas at Austin (UT Austin), specifically in the Department of Information, Risk, and Operations Management. He is a core member of the Machine Learning Laboratory and serves on the Graduate Studies Committee for both the Computer Science Department and the Oden Institute at UT Austin. His research focuses on controllable machine intelligence, human-centered ML frameworks, and evaluating the societal impacts of AI systems. Education: Ph.D. in Machine Learning, Carnegie Mellon University (2023), advised by Zachary Lipton Postdoctoral Researcher, Princeton Language and Intelligence (2023-2024) Bachelor’s degrees in Computer Science (Bryn Mawr College) and Mathematics (Haverford College), with a semester at AIT-Budapest (Spring 2016) Research Interests: Liu’s work spans three core areas: (1) foundational studies of generative AI systems, (2) designing human-centered ML models for healthcare, education, and recommenders, and (3) auditing the societal implications of large-scale AI. He emphasizes ethical and human-centric approaches to AI development. Awards: Open Philanthropy AI Fellow (2020-2023) Advising & Lab: Liu seeks motivated students to join his lab, focusing on large language model generalization. He advises through the lab website, fostering collaborative research environments.

E. Jin Leeمشاهده پروفایل

استادیار

• Data Analytics
• Machine Learning
• Disclosure
• +۱۲ مورد دیگر

Dr. E. Jin Lee is an Assistant Professor of Accounting at Bryant University's College of Business. Her teaching focuses on Financial Accounting, Managerial Accounting, Data Analytics (with Machine Learning), Artificial Intelligence in Accounting, Auditing, and Accounting Information Systems. She earned her Ph.D. in Accounting from Florida International University, where she received the external AGA Fellowship, and an MS in Accountancy from George Washington University, where she was awarded the Hyundai Scholarship. Education Ph.D., Florida International University MS, George Washington University Research Interests Data Analytics, Machine Learning Methods Disclosure, Individual Investors Empirical Capital Markets, Going Concern Opinion Audit Partner, Audit Lag, Financial Distress Financial Reporting, Mergers and Acquisitions Macroeconomic Effects, COVID-19 Impacts, Gender, Social Media Scientific Awards AAA International Accounting Section (IAS) Doctoral Consortium Fellowship (2021, 2020) Top 10% of Authors on SSRN by total new downloads (2020) Association of Government Accountants (AGA) Scholarship Award (2020) AAA Financial Accounting Reporting Section (FARS) Doctoral Consortium Fellowship (2019) AAA Journal of International Accounting Research (JIAR) Doctoral Consortium Fellowship (2019) Her research has been cited in The Wall Street Journal and Compliance Week , with one article published in the Journal of Behavioral Finance (2023). She has served as an editor and co-chair for the Strategic and Emerging Technologies (SET) Workshop at the American Accounting Association (AAA) annual meeting, program organizing co-chair for the Accounting Information Systems (AIS) Summer Doctoral Consortium, and judge for the Data Analytics Case Competition. She actively participates in academic service through reviewing and discussing papers in journals like the Managerial Auditing Journal and Journal of Emerging Technologies in Accounting .

• Operations Management
• Industry 4.0
• Strategic Management
• +۷ مورد دیگر

Andrea Chiarini is an Associate Professor at the University of Verona's Department of Management. He holds a PhD in TQM and Business Excellence from Sheffield Hallam University, UK, and has extensive experience in Operations Management, Industry 4.0, and Lean Six Sigma. He previously served as a professor at the University of Modena and Reggio and the University of Ferrara, and currently teaches at Bocconi University and other institutions. His research focuses on strategic operations, sustainability, and the integration of Industry 4.0 technologies. He is the CEO of Qualyco Srl, a spin-off specializing in AI and Industry 4.0 solutions. He serves on editorial boards for journals like Business Strategy and the Environment and has published over 50 articles on topics including supply chain resilience, Lean Six Sigma frameworks, and green HR practices. His work emphasizes operational excellence, digital transformation, and sustainable management practices in manufacturing and healthcare sectors. Research interests span CSR, logistics optimization, and innovation. His recent articles explore frameworks for Lean Six Sigma 4.0 and the impact of automation on employment. He advises on strategic management, performance measurement systems, and risk-based thinking in quality standards. Grants and collaborations include projects with ABB, Ferrari, and Tetrapak. He leads research groups on ICT adoption in healthcare and wine industries. His teaching modules cover business organization, innovation management, and industry 4.0 applications.

• Cloud Computing Security
• IoT Services
• Network Security
• +۵ مورد دیگر

Shao Ying Zhu is a Lecturer in Computing at the Department of Electronics, Computing and Mathematics. Their research focuses on network security, cloud computing, IoT systems, and medical image analysis. Key contributions include frameworks for secure IoT service orchestration in multi-cloud environments and comparative studies of IPv6 routing protocols. Publications span areas like SDN security solutions, big data analytics algorithms, and cloud assurance methodologies. Notable work includes a textbook on cloud security assurance and analysis of HEp-2 medical images using machine learning techniques. Research outputs demonstrate expertise in both theoretical frameworks and applied solutions for modern computing challenges, with a focus on security and scalability across distributed systems.

Robert A. Nehmerمشاهده پروفایل

استاد

• Accounting Information Systems
• Internal Controls
• Continuous Auditing
• +۵ مورد دیگر

Robert A. Nehmer is a Professor of Accounting at Oakland University's School of Business Administration, where he has served since at least 2006 (evidenced by a 10-Year Service Award in February 2016). His research bridges accounting theory with cutting-edge technology, focusing on internal controls, continuous auditing frameworks, and emerging systems like blockchain and drone technology. Dr. Nehmer teaches assurance and accounting information systems courses at both graduate and undergraduate levels from his office in Elliott Hall, Room 200H. Dr. Nehmer's academic foundation was built at the University of Illinois at Urbana-Champaign: Ph.D. in Accounting Master's in Accountancy Bachelor's in Accountancy His research agenda centers on formal systems and technological disruption in auditing, with current projects exploring XBRL representations, distributed ledger technologies, and software agent implementations for internal controls. Notable work includes pioneering research on drone applications in auditing that led to an ongoing KPMG collaboration, alongside investigations into blockchain-based assurance frameworks and financial ontologies. His methodology often combines mathematical modeling with practical implementations in transaction processing environments. Analysis of his 15 most recent publications reveals a clear evolution from foundational XBRL and agent-based modeling (2009-2016) toward immersive technologies like IoT, blockchain, and AI (2020-2024). The research trajectory demonstrates increasing industry relevance, with recent work directly addressing audit evidence frameworks for drone-collected data and ChatGPT applications in accounting education. Cross-cutting themes include risk assessment formalization, control system optimization, and semantic representation of financial concepts. Dr. Nehmer's contributions have been recognized through: University Service Award, Oakland University/SBA (April 2016) 10 Year Service Award, Oakland University (February 2016) As an active researcher with strong industry partnerships including KPMG, ISACA, and XBRL-US, Dr. Nehmer likely secures research funding through collaborative projects and professional organization engagements. His extensive publication record in top journals like the Journal of Emerging Technologies in Accounting suggests successful grant acquisition for technology-focused accounting research. While specific student advising details aren't provided, his graduate teaching responsibilities indicate mentorship of master's and doctoral candidates in accounting information systems.

Shiri Dori-Hacohenمشاهده پروفایل

استادیار

• Information Ecosystem Threats
• AI Safety
• Sociotechnical AI Alignment
• +۵ مورد دیگر

Shiri Dori-Hacohen is an Assistant Professor of Computer Science & Engineering at the University of Connecticut, directing the Reducing Information Ecosystem Threats (RIET) Lab. Her work focuses on AI safety, sociotechnical AI alignment, and mitigating information ecosystem threats through transdisciplinary collaboration. She has secured $7.7M in NSF funding and received awards including the 2023 D-30 Disability Impact List for groundbreaking fairness research. Education: B.Sc. and M.Sc. (cum laude) in Computer Science, University of Haifa, Israel M.S. and Ph.D. in Computer Science, University of Massachusetts Amherst Research Interests: Combating misinformation, controversy detection, AI ethics, and health equity. Her work bridges computer science with medicine, public health, and social sciences. Current projects address disinformation, botnet detection, and fairness in medical AI systems. Awards and Recognition: 2023 D-30 Disability Impact List 2022 AI Risk Analysis Award (NeurIPS) 2016 UMass Amherst Innovation Challenge First Place 2011 Google Lime Scholarship Leadership & Advocacy: Co-founder of Graduate Women in STEM @ UMass, Women in Information Retrieval, and Disabled In Computing. Active media commentator featured in Reuters, The Guardian, Forbes, and Galei Tzahal radio. Labs & Initiatives: PI of RIET Lab which develops computational tools to detect threats in information ecosystems. Research incorporates petabyte-scale social network data and graph-theoretic approaches. Current focus on medical fairness and misinformation mitigation in marginalized communities.

Miguel Vargas Martinمشاهده پروفایل

استاد

• Computer Security
• Cybersecurity
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Miguel Vargas Martin is a Professor of Computer Science at Ontario Tech University's Faculty of Business and Information Technology. He holds a PhD from Carleton University, a Master's from CINVESTAV del IPN, and a Bachelor's from Universidad Autónoma de Aguascalientes. His research focuses on cybersecurity, authentication systems, machine learning, and human factors in security. Dr. Martin teaches graduate courses such as Cryptography and Secure Communications, and undergraduate courses including Machine Learning and Cryptography, Malware, and Network Security. Education: PhD in Computer Science, Carleton University (2003) Master of Applied Science in Electrical Engineering, CINVESTAV del IPN (1998) Bachelor of Science in Computer Science, Universidad Autónoma de Aguascalientes (1996) Research Interests: Dr. Martin's work addresses cutting-edge topics in computer security and artificial intelligence. His recent studies include improving password security through honeyword generation using machine learning, developing differential privacy visualizations for public understanding, and creating emotion recognition models for companion robots. His cybersecurity frameworks target edge computing and IoT environments, emphasizing practical defenses against modern threats. Key Contributions: Over 25 peer-reviewed articles since 2012 span topics from brain-computer interfaces for password memorability analysis to fusion-based optimization algorithms. His work bridges theoretical advancements with real-world applications in healthcare, transportation systems, and industrial IoT security.