جست‌وجوی استاد و پژوهشگر

Francesco Corielliمشاهده پروفایل

دانشیار

• Mathematical Finance
• Statistical Modeling
• Partial Differential Equations in Finance
• +۴ مورد دیگر

Francesco Corielli is an Associate Professor of Mathematics for Finance, Economics, and Insurance at Bocconi University, where he has held academic positions since 1989. He graduated in Economics from Bocconi University in 1983. His research focuses on model misspecification in statistics and finance, robustness analysis, partial differential equations in finance, and the application of canonical correlation to financial price analysis. He has contributed to seminal works on parametrix approximation methods, risk management, and hedging strategies in energy markets. Corielli has taught courses including Financial Econometrics, Machine Learning in Finance, and Quantitative Methods for Trading, emphasizing rigorous foundational knowledge and practical applications. His teaching philosophy prioritizes clarity and precision to avoid conceptual misunderstandings. He has published extensively in journals such as the Siam Journal on Financial Mathematics and Journal of Banking & Finance , and his work spans empirical finance, project finance, and theoretical econometrics. Notable research areas include analyzing model error propagation, developing approximation techniques for PDE solutions in finance, and exploring the interplay between textual analysis of online messages and financial market dynamics. His contributions to the understanding of beta regression in finance and ESG rating methodologies further highlight his interdisciplinary approach.

Mark Greenمشاهده پروفایل

مدرس ارشد

• Metaprogramming
• Software Systems Development
• Agent-Oriented Programming
• +۳ مورد دیگر

Dr. Mark Green is a Senior Lecturer in the School of Engineering, Computing and Mathematics at Oxford Brookes University. He holds a PhD in Computer Science from the University of Reading, focusing on visualization techniques for formal specifications of communicating systems. His expertise spans metaprogramming, software systems development, and cybersecurity, with over 10 years of teaching experience in higher education. Research interests include Agent-Oriented Programming (via the CAOPLE language), game technologies (including procedural generation and gamification), and semantic systems. He is affiliated with the Artificial Intelligence, Data Analysis and Systems (AIDAS) Institute and the Cloud Computing and Cybersecurity Group (CCC). Notable achievements include the 2017-18 Brookes Union Award for Outstanding Contribution to the Student Experience. Teaching modules include Secure Systems Architecture, Game Technologies and Development, and Software Development with C and C++. He has supervised MSc projects in experimental game development, web UI design, and AI applications. His research outputs include contributions to microservices development (CIDE IDE) and formal methods in system analysis. Awards: Brookes Union Award (2017-18) Professional Affiliations: mBCS member Consultancy: Developed a configurable Fruit Machine simulator for psychological research

Lionel Parreauxمشاهده پروفایل

استادیار

• Programming Languages
• Type Systems
• Functional Programming
• +۳ مورد دیگر

Lionel Parreaux is an Assistant Professor at The Hong Kong University of Science and Technology (HKUST) in the Department of Computer Science and Engineering since February 2021. He is actively recruiting students for his research group focusing on programming languages, type systems, and compiler optimization. He earned his PhD in 2020 from École polytechnique fédérale de Lausanne (EPFL) under the Data Analysis Theory and Applications Laboratory (DATA), where he developed the Squid type-safe metaprogramming library for Scala. His research spans Programming Languages Type Systems Functional Programming Generative Programming Compiler Optimization Language Design Recent publications (2024) cover type inference, metaprogramming, and compiler optimization. Notable works include Scope-safe metaprogramming Deforestation techniques Conditional syntax design Subtyping constraints Lazy memory management These reflect his focus on theoretical and practical language implementation challenges. Current research projects include "A Lightweight Type System for Scope and Effect Safety" (2024, Huawei Technologies) "Optimizing Functional Programs by Building on Optimal Graph Reduction Techniques" (2022-2025, RGC Early Career Scheme) He supervises 8 PhD/MPhil students and serves on program committees for POPL, APLAS, GPCE, and SPLASH symposia.

• Stochastic Control
• Probabilistic Modeling
• Decentralized Control Systems
• +۷ مورد دیگر

Dr. Yuyang Zhou is a Lecturer in the School of Computing, Engineering and the Built Environment at Edinburgh Napier University, where he contributes to the Centre for Artificial Intelligence and Robotics. His research focuses on advanced control systems, probabilistic modeling, and intelligent robotics, with active involvement in EU-funded projects such as iMARS (2024–2028). Institution: Edinburgh Napier University School: School of Computing Engineering and the Built Environment Research Centre: Centre for Artificial Intelligence and Robotics Role: Lecturer Email: Y.Zhou@napier.ac.uk Dr. Zhou's research centers on stochastic and nonlinear control systems, with a strong emphasis on decentralized and probabilistic frameworks. His work integrates machine learning, entropy-based monitoring, and message-passing algorithms to enhance system performance under uncertainty. Key domains include smart grids, industrial prediction systems, and robotics. The recent publications highlight a consistent trend in developing innovative control strategies for complex stochastic systems. These include event-triggered relearning, variance and entropy assignment, and fully probabilistic design methods. The research spans applications in industrial automation, energy systems, and future grid technologies, demonstrating a strong interdisciplinary approach combining AI, control theory, and IoT. Dr. Zhou supervises postgraduate research students, including Anna Chernikova (Hybrid and Switched Control Systems) and Fatima Mumtaz (AI-driven smart banking). He collaborates extensively with Prof. Randa Herzallah and is a co-investigator on the European Commission-funded iMARS project, which aims to develop intelligent multi-agent robotic systems for first responders using AI, IoT, and 5G technologies.

Cynthia Rushمشاهده پروفایل

دانشیار

• Mathematical Statistics
• High-Dimensional Inference
• Approximate Message Passing
• +۷ مورد دیگر

Cynthia Rush is an Associate Professor in the Department of Statistics at Columbia University, where she conducts research at the intersection of mathematical statistics, information theory, and high-dimensional data analysis. She is affiliated with the Graduate School of Arts and Sciences and is based in the School of Social Work building in New York City. Ph.D. in Statistics, Yale University, 2016 B.S. in Mathematics, University of North Carolina at Chapel Hill Her research focuses on the development and analysis of algorithms for high-dimensional inference, particularly using Approximate Message Passing (AMP), with applications in sparse regression, signal processing, and machine learning. She integrates tools from information theory, statistical physics, and applied probability to understand fundamental limits and performance of modern statistical methods. Her recent publications span topics such as SLOPE regularization, community detection, power posteriors, and massive multiple access in communications. These works appear in top journals including IEEE Transactions on Information Theory, Annals of Statistics, and NeurIPS. Her research shows a consistent trend toward rigorous theoretical analysis of high-dimensional statistical algorithms and their practical implications. Notable scientific recognition includes being a finalist for the JKW Student Paper Award at IEEE ISIT in 2016. She has delivered numerous invited talks at leading institutions and conferences worldwide, reflecting her active role in the theoretical data science community. JKW Student Paper Award Finalist, IEEE ISIT 2016 She advises and collaborates with researchers in statistics, machine learning, and information theory, though formal doctoral advisees are not listed. Her work is supported by theoretical grants and collaborations across engineering and mathematical sciences. She is involved in the broader academic community through seminars, workshops, and program committees, contributing to the advancement of rigorous statistical learning. Cynthia Rush leads a research group focused on high-dimensional inference and algorithmic analysis, often collaborating with researchers at institutions like Yale, Princeton, and international centers in Europe and Asia. Her lab emphasizes theoretical foundations with practical relevance in data science and communications.

Maelys J. Amatمشاهده پروفایل

مدرس

• Healthcare Disparities
• Primary Care
• Social Determinants of Health
• +۶ مورد دیگر

Maelys J. Amat, MD, MBA is a Faculty Affiliate at Harvard Medical School (HMS), an Instructor in Medicine at HMS, and a primary care physician in the Division of General Medicine at Beth Israel Deaconess Medical Center (BIDMC). She currently serves as Associate Medical Director at MassHealth, focusing on quality and utilization management for dual-eligible Medicare-Medicaid members. Education : MD and MBA degrees (institution not explicitly stated in text). Dr. Amat's research explores healthcare disparities in vulnerable populations, with a focus on improving care for patients with limited English proficiency, understanding disparities linked to social determinants of health, and addressing diagnostic errors through AHRQ-funded projects. Her work spans health equity, advocacy, and technology-driven interventions like text messaging to reduce disparities in chronic disease outcomes. Scientific Awards : Arnold Tofias/Leo Condakes Quality Scholarship. Dr. Amat has contributed to medical education through curriculum development in health equity and advocacy for residents and fellows at BIDMC. Her leadership roles in healthcare quality initiatives at MassHealth and BIDMC highlight her commitment to systemic improvements in patient care.

• Distributed Systems
• Erlang Programming Language
• Scalability Engineering
• +۴ مورد دیگر

Natalia Chechina is an Honorary Research Fellow at the School of Computing Science, University of Glasgow, specializing in distributed systems with a particular focus on the Erlang programming language and its applications in building reliable and scalable systems. Her research interests span several critical areas in distributed computing: Distributed systems architecture and design Scalability and reliability engineering Erlang ecosystem development Robotics communication systems Server software engineering Performance optimization in distributed environments Dr. Chechina's extensive publication record from 2009-2021 demonstrates consistent contributions to advancing distributed computing capabilities, particularly through her work on SD Erlang (Scalable Distributed Erlang). Her research bridges theoretical analysis with practical implementation, addressing fundamental challenges in building systems that maintain functionality despite failures. She has made significant contributions to understanding how to construct robust server infrastructure that can scale effectively while preserving reliability across diverse application domains. Her collaborative work, frequently with Phil Trinder and other colleagues at the University of Glasgow, spans robotics, instant messaging systems, and general server infrastructure. The cross-disciplinary nature of her research is evident in publications addressing robot team coordination and communication, demonstrating how distributed systems principles can solve complex challenges in multiple domains.

• Medication Safety
• Health Informatics
• Patient-Provider Communication
• +۵ مورد دیگر

Bruce L Lambert is a Professor in Medical Social Sciences (Intervention Science) at Northwestern University's Feinberg School of Medicine and concurrently holds a Professor position at the School of Communication. His work bridges clinical medicine, health informatics, and communication science with appointments across multiple institutes including the Center for Diabetes and Metabolism, Institute for Public Health and Medicine (IPHAM), and Northwestern University Clinical and Translational Sciences Institute (NUCATS). His research focuses on medication safety systems, electronic health record (EHR) design, and health communication. Key interests include preventing drug name confusion errors, optimizing indication-based prescribing, and developing clinical decision support tools. Lambert employs psycholinguistic testing to predict real-world medication errors and investigates secure messaging networks in healthcare settings. His work demonstrates how EHR interface design directly impacts wrong-patient and wrong-drug error rates. Analysis of his recent publications reveals strong emphasis on opioid safety in emergency departments, Veterans Health Administration prescribing patterns, and multimodal approaches to medication error prevention. His scholarship consistently addresses system-level interventions rather than individual provider blame, advocating for human factors engineering solutions in healthcare technology. Lambert actively contributes to medication safety policy, having published on Tall Man lettering limitations and the need for comprehensive immune monitoring in vaccine trials. His research directly informs EHR design standards and clinical workflow improvements across multiple healthcare systems. As an educator, he integrates principles of conservative prescribing and health literacy into medical training. His work on pharmacy deserts in minority communities highlights health equity concerns in medication access. Lambert's PhD from University of Illinois at Urbana-Champaign (1992) established his foundation in communication science applied to healthcare contexts.

Arvind Muruganمشاهده پروفایل

دانشیار

• Quantitative Biology
• Non-Equilibrium Dynamics
• Theoretical Computer Science
• +۷ مورد دیگر

Arvind Murugan is an Associate Professor in the Department of Physics at the University of Chicago and a member of the Committee on Computational and Applied Mathematics (CCAM). His research focuses on quantitative biology, non-equilibrium dynamics, and theoretical computer science, particularly in understanding how physical and biological systems can learn and adapt through collective dynamics. Affiliations: Gordon Center for Integrative Science, U Chicago Center for Living Systems Research Interests: Physical learning mechanisms in non-equilibrium systems Molecular self-assembly and error correction Active matter and biological regulation Associative memory in molecular networks Interdisciplinary approaches combining physics, biology, and computer science Publication Trends: His recent work explores soft modes in biological systems, temporal contrastive learning in physical systems, and error correction mechanisms in molecular processes. These studies bridge physics, computational biology, and materials science, revealing how simple physical systems can exhibit complex learning behaviors. Scientific Awards & Funding: Supported by NSF, NIH, Simons, Sloan, Moore, and Chan Zuckerberg Foundations Lab members funded by James S. McDonnell, Hertz, and NSF fellowships Collaborations & Lab: The Murugan Lab collaborates with the Rust, Tay, Wang, Elowitz, Hwa, Pincus, and Szostak labs. They actively seek researchers with expertise in molecular biology and high-throughput evolution to advance physical learning systems.

Patrick C. Wohlfarthمشاهده پروفایل

استاد

• American Politics
• Quantitative Methodology
• Judicial Politics
• +۵ مورد دیگر

Patrick C. Wohlfarth is a Professor and Director of Undergraduate Studies in the Department of Government and Politics at the University of Maryland, College Park. He holds a Ph.D. in Political Science from the University of North Carolina at Chapel Hill (2010) and completed a Post-Doctoral Fellowship at Washington University in St. Louis (2010-2011). His research focuses on American politics, judicial behavior, legal institutions, and quantitative methodology, particularly exploring judicial politics, executive branch litigation, and public opinion's impact on legal outcomes. Wohlfarth is co-author of three major books, including the award-winning Cognitive Aging and the Federal Circuit Courts (2024), which won the 2025 C. Herman Pritchett Award. His work has been published in top journals such as American Journal of Political Science , Journal of Politics , and Law & Society Review . He has received prestigious awards, including the 2015 Excellence in Teaching Award from the College of Behavioral and Social Sciences. His research explores how cognitive aging affects judicial decision-making, the influence of Supreme Court justices' personalities on legal outcomes, and public attitudes toward judicial term limits. Recent work examines the geographic origins of redistricting cases and the relationship between public confidence in the Supreme Court and legislative actions restricting its jurisdiction. Wohlfarth teaches courses on American government and the U.S. Supreme Court, emphasizing constitutional policy and institutional dynamics. His interdisciplinary approach bridges political science and legal studies, offering insights into judicial behavior, public opinion, and institutional legitimacy.

• Agent-Based Modeling
• Multi-Agent Systems
• Computer Science Education
• +۴ مورد دیگر

Seán Russell is an Assistant Professor in Computer Science at University College Dublin (UCD), affiliated with the School of Computer Science. He holds a BSc and PhD from UCD, as well as a Professional Diploma in University Teaching and Learning. His research spans agent-based simulation systems, multi-agent architectures, and computer science education. Notable contributions include work on hypermedia MAS, microservices for scalable simulations, and pedagogical strategies for non-native English speakers in CS1 courses. Education: BSc in Computer Science, University College Dublin PhD in Computer Science (details unspecified) Professional Diploma in University Teaching and Learning, University College Dublin Research Interests: Russell focuses on agent-oriented programming, distributed systems (microservices/REST), and innovative teaching methodologies. His work bridges theoretical agent architectures with practical applications like traffic simulation and waste management. Recent education-focused research addresses code quality in CS1, error message comprehension, and linguistic barriers for non-native English students. Grants & Awards: UCD College of Science Teaching Excellence Award (2022) OPTI-ROUTE Grant (2017–2018) Teaching & Learning Award (2021/2022) Teaching & Leadership: Coordinates modules in programming fundamentals (e.g., Intro to Programming 1, Object-Oriented Design) and serves as Vice Chair of the Ireland ACM SIGCSE Chapter. Supervised a PhD student (2019–2024).

Joerg Kliewerمشاهده پروفایل

استاد

• Information Theory
• Distributed Computing
• Error Correction
• +۲ مورد دیگر

Joerg Kliewer is a Professor in the Department of Electrical and Computer Engineering at NJIT. His research focuses on information theory, secure distributed computing, error correction, and network communication resilience. Education: Ph.D. in Electrical Engineering, University of Kiel (1999) M.S. in Computer Science, Stanford University (1984) Diploma in Electrical Engineering, Hamburg University of Technology (1993) Research: Develops coding schemes for distributed storage, privacy-preserving machine learning, and straggler-tolerant cloud computing. Recent work includes federated learning optimization and reinforcement learning-based decoding.

Emmanuel Abbéمشاهده پروفایل

استاد

• Machine Learning
• Information Theory
• Probability Theory
• +۷ مورد دیگر

Emmanuel Abbé is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) , holding the Chair of Mathematical Data Science jointly under the School of Basic Sciences (SB) and School of Computer and Communication Sciences (IC) . His research focuses on the mathematical foundations of data science, combining probability, statistics, and discrete mathematics to advance machine learning and information theory. Research Interests : Community detection and stochastic block models Information theory and coding Deep learning theory and generalization bounds Graph-based data analysis and spectral methods Neural network regularization and optimization Mathematical aspects of AI and ML Scientific Awards : Foundation Latsis International Prize Bell Labs Prize NSF CAREER Award Google Faculty Research Award Walter Curtis Johnson Prize von Neumann Fellowship IEEE Information Theory Society Paper Award Simons-NSF Mathematics of Deep Learning Collaborative Research Award Advising and Grants : Prof. Abbé supervises multiple PhD students including Lotfi Jandaghi Aryo, Pushkin Denys, and Senouf Ortal Yona. His research is supported by grants from the Swiss National Science Foundation and other international bodies.

• Software Engineering
• Software Testing
• Machine Learning Systems
• +۴ مورد دیگر

Dr. Iftekhar Ahmed is an Associate Professor in the Department of Informatics at the University of California, Irvine’s Donald Bren School of Information & Computer Sciences. His research focuses on software engineering methodologies, emphasizing software testing, analysis, and accessibility. He holds a Ph.D. in Computer Science from Oregon State University (2018) and a B.S. in Computer Science and Engineering from Shahjalal University of Science and Technology, Bangladesh (2007). Education: Ph.D., Computer Science, Oregon State University, 2018 B.S., Computer Science and Engineering, Shahjalal University of Science and Technology, Bangladesh, 2007 His research integrates artificial intelligence, data mining, and empirical software engineering to improve software quality and safety. Key areas include: Automated testing frameworks for large systems Bug prediction models for code vulnerabilities Accessibility testing tools (e.g., Ma11y mutation framework) Safety-critical systems like autonomous vehicles Recent work explores AI-driven code generation, prompt engineering, and mitigating biases in software tools. His team received a $1.2M grant in 2022 to enhance accessibility testing tools. Ahmed also investigates human factors in software development, including developer mental health and tool adoption challenges. His publications address critical issues like code smells in quantum computing, commit message quality, and Jupyter notebook bug patterns. He actively participates in industry-academia collaborations, such as the 2023 Southern California Software Engineering Symposium.

Steve Zippersteinمشاهده پروفایل

استادیار مدعو

• Criminal Justice Policy
• Legal History of the Middle East Conflict
• Technology and Cybersecurity Law and Policy
• +۳ مورد دیگر

Steve Zipperstein is an Adjunct Assistant Professor at the Luskin School of Public Affairs, University of California, Los Angeles (UCLA). He concurrently serves as Director of the UCLA Younes and Soraya Nazarian Center for Israel Studies, a Distinguished Senior Scholar at the UCLA Center for Middle East Development, and a Senior Fellow with The Hague Initiative for International Cooperation. He also holds visiting lecturer roles at Tel Aviv University Law School and the Hertie School in Berlin, and teaches in UCLA’s Global Studies Program and School of Engineering. His legal career spans over 40 years, including roles as a federal prosecutor, Chief Legal Officer at BlackBerry and Verizon Wireless, and Counselor to Attorney General Janet Reno during the 1995 Waco hearings. Zipperstein’s research focuses on Criminal Justice Policy , Legal History of the Middle East Conflict , and Technology and Cybersecurity Law . He has authored three seminal books on the Israeli-Palestinian legal conflict, including The Legal Case for Palestine: A Critical Assessment (2024) and Zionism, Palestinian Nationalism and the Law: 1939-1948 (2022). His work integrates historical legal analysis with contemporary geopolitical challenges. Recent publications (2023-2025) emphasize proportionality in warfare, international legal frameworks, and cybersecurity governance. Earlier works (1992-1997) explored sentencing guidelines and legal defense strategies. His scholarship has been featured in outlets like Justice: The Legal Magazine , Routledge series, and academic journals. Zipperstein has received recognition as an elected member of the American Law Institute and a Life Fellow of the American Bar Foundation. His legal advocacy extends to congressional testimony on telecommunications policy and media commentary on Middle Eastern conflicts, including interviews with BBC, ABC News, and The Hague Initiative.