جست‌وجوی استاد و پژوهشگر

Ezekiel Dixon-Románمشاهده پروفایل

استاد

• Critical Race Theory
• Educational Studies
• Quantification Technologies
• +۷ مورد دیگر

Ezekiel Dixon-Román is a Professor of Critical Race, Media, and Educational Studies and Director of the Edmund W. Gordon Institute for Urban and Minority Education at Teachers College, Columbia University. He holds a PhD in Psychometrics from Fordham University (2007), with prior degrees from The University of Chicago (MA, 2002) and North Carolina Central University (BA, 2000). His research critiques how quantification technologies reproduce racial and sociopolitical inequities, focusing on algorithmic governance, biopolitical systems, and Black radical traditions. He leads the Institute in Critical Quantitative, Computational, & Mixed Methodologies and co-directs the Critical Computation Bureau. Key scholarly contributions include Inheriting Possibility: Social Reproduction & Quantification in Education (2017, AERA Outstanding Book Award) and co-edited volumes such as Black Radical Love: A New Black Reconstruction (2023). His work interrogates the intersections of race, technology, and power, proposing speculative methodologies to reimagine sociotechnical systems. Dixon-Román has secured grants for urban education initiatives, public-private partnerships, and interdisciplinary collaborations. He teaches courses on critical data science, AI ethics, and Black studies in education. Education: PhD in Psychometrics (Fordham University) Affiliations: Director, Gordon Institute; Co-Founder, Institute in Critical Quantitative, Computational & Mixed Methodologies Awards: 2018 AERA Outstanding Book Award His current projects include exploring recursive colonialisms in technology and authoring Haunting Algorithms: Algorithmic Governance and Logics of Colonialism , which examines the colonial underpinnings of algorithmic systems.

Stephanie Balzerمشاهده پروفایل

استادیار

• Programming Languages
• Pure and Applied Logic
• Software Verification
• +۳ مورد دیگر

Stephanie Balzer is an Assistant Professor in the Principles of Programming Group of the Computer Science Department at Carnegie Mellon University. Her office is located in 9004 Gates-Hillman Center, and she can be reached at balzers@cs.cmu.edu with administrative support from Oliver Moss. Dr. Balzer received her PhD from ETH Zurich under the supervision of Thomas R. Gross. Her academic trajectory shows consistent focus on formal methods and programming language theory from her early work on object relationships through to her current research on verification systems. Her research program aims to enable the construction of failure-free software that is correct by design and secure to run. She deploys rigorous reasoning methods such as type systems and verification logics to formally prove adherence to desired properties. Her work emphasizes compositional methods for scalability and addresses verification needs arising from real-world problems. Dr. Balzer's interests span Programming Languages, Pure and Applied Logic, Software Verification, Type Theory, and Security . A driving force underlying her research is the belief that powerful solutions are fundamentally based on simple ideas that can be conveyed to and appreciated by non-experts. Analysis of Dr. Balzer's publication record reveals a sustained focus on session types, logical relations, and concurrent systems verification. Her recent work shows increasing sophistication in handling timed protocols, information flow control, and heterogeneous applications. She consistently publishes in top-tier venues including POPL, PLDI, ICFP, and ECOOP, often receiving distinguished paper awards for particularly impactful contributions. NSF CAREER Award on "A Semantic Framework for Verifying Heterogeneous Applications" (2024) ACM SIGPLAN Distinguished Paper Award (2023) ECOOP Distinguished Paper Award (2022) Supervised PhD student Jules Jacobs received Cum Laude distinction (2024) Dr. Balzer has secured significant research funding including an NSF CAREER Award (2025), an NSF Award on Integrated Verification of IoT and Real-time Communication Protocols (2022), an AFOSR Award (2021), CyLab Seed Funding (2020), and previous NSF and Mozilla Research Grants. She actively mentors a diverse research group including PhD candidates Yue Yao, Yinsen (Tesla) Zhang, and Zak Kent (co-advised with Guy Blelloch), as well as M.S. and undergraduate researchers. Her supervision extends to postdoctoral fellows and thesis committee roles for other students. Dr. Balzer leads research activities within CMU's ForML Lab and maintains active collaborations with researchers at ETH Zurich, Radboud University Nijmegen, and Cornell University. She plays significant leadership roles in the programming languages community including as founder of the PL Scholars Network, steering committee chair of the Programming Languages Mentoring Workshop (2023-2025), and co-organizer of the Oregon Programming Languages Summer School (2023).

Divesh Aggarwalمشاهده پروفایل

دانشیار

• Lattice Algorithms and Complexity
• Cryptography
• Pseudorandomness
• +۶ مورد دیگر

Divesh Aggarwal is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS) and a Principal Investigator at the Centre for Quantum Technologies (CQT). He leads an active research group with multiple PhD students, postdocs, and collaborators focusing on theoretical computer science and cryptography. His research spans two primary themes: (1) fine-grained complexity and exponential algorithms for hard problems, particularly lattice problems, where he works on both finding faster algorithms and proving lower bounds; and (2) randomness extractors and their applications in cryptography, privacy amplification, and tamper-resilient systems. His work intersects cryptography, computational complexity, and quantum computing. Aggarwal's recent publications (2022-2025) demonstrate continued productivity in lattice-based cryptography, with significant contributions to non-malleable codes, quantum security, and hardness assumptions. His work appears consistently in top venues including STOC, FOCS, CRYPTO, and IEEE Transactions. The research shows a strong trend toward quantum-resistant cryptography and exploring the boundaries between classical and quantum computational hardness. He actively mentors students and researchers, with current PhD students including Zeyong Li, Rishav Gupta, Saswata Mukherjee, Aditya Morolia, and Ananta Mukherjee. His alumni have secured positions at institutions including NUS, IIT Delhi, and XJTLU. Aggarwal also organizes a weekly research seminar where his group discusses theoretical computer science topics. His teaching portfolio includes advanced courses such as Computational Complexity, Pseudorandomness, Design and Analysis of Algorithms, and Introduction to Quantum Computing. He serves on program committees for major conferences including CRYPTO, EUROCRYPT, and STOC, and on editorial boards for journals like Information Processing Letters.

Joxan Jaffarمشاهده پروفایل

استاد

• Programming Languages
• Software Engineering
• Constraint Logic Programming
• +۶ مورد دیگر

Professor Joxan Jaffar is affiliated with the Department of Computer Science at the National University of Singapore (NUS) School of Computing. He earned his Ph.D. from Monash University (1985), M.Sc. (1981) and B.Sc. (1979) from the University of Melbourne. Ph.D., Monash University, 1985 M.Sc., University of Melbourne, 1981 B.Sc. (Honours), University of Melbourne, 1979 His research focuses on Programming Languages , Constraint Logic Programming , and Software Verification . Recent work involves symbolic execution methods for program analysis, memory usage, and string constraint reasoning using tools like Tracer-X. He has received significant recognition, including the MOE Academic Research Fund (AcRF) grant in 2021. Selected publications highlight advancements in symbolic execution, constraint-based program analysis, and verification of recursive data structures. His leadership roles at NUS include Head of Department (1998-2001) and Dean (2001-2007) of the School of Computing. Scientific Awards: MOE AcRF grant (2021)

Kathi Fislerمشاهده پروفایل

استاد پژوهشی

• Computing Education
• Formal Methods
• Data Science
• +۳ مورد دیگر

Kathi Fisler is a Research Professor of Computer Science at Brown University, serving as Director of CS Undergraduate Studies and Research Director at Bootstrap. She holds a PhD and MS from Indiana University and a BA from Williams College. Her research focuses on computing education, formal methods, and data-centric approaches, emphasizing how people learn formal systems. She leads efforts to integrate socially-responsible computing across Brown’s CS curriculum and collaborates on Bootstrap’s K-12 outreach programs. Key projects include data-centric computing education, notional machines, and policy analysis tools like Margrave. Education: PhD in Computer Science, Indiana University (1996) MS in Computer Science, Indiana University (1992) BA in Computer Science, Williams College (1991) Research Interests: Data-centric computing education Computing education pedagogy Formal methods for hardware and security Socially-responsible computing curriculum design Bootstrap K-12 outreach initiatives Teaching: CSCI 0050: Data-Centric Programming CSCI 0200: Data Structures & Algorithms CSCI 2952B: Computer Science Education Research Awards: Best Paper Award at Koli Calling 2017 Best Paper Award at SIGCSE 2011 Labs/Teams: Brown Computing Education Research Group Bootstrap (K-12 outreach)

• Discrete Mathematics
• Combinatorics
• Number Theory
• +۵ مورد دیگر

Professor Peter Larcombe is a prominent academic in the College of Science and Engineering at the University of Derby, specializing in Discrete and Applied Mathematics. His research focuses on Horadam sequences, combinatorial identities, and mathematical communication. He has published extensively on topics including recurrence relations, matrix methods, and the philosophy of mathematics. Key areas of exploration include the properties of Horadam sequences, the interplay between writing and mathematical practice, and the sociocultural aspects of mathematical genius. His work often bridges theoretical mathematics with pedagogical and philosophical inquiries, emphasizing clarity and interdisciplinary approaches. Notable contributions include foundational studies on recurrence identities, generating functions, and the analysis of matrix invariants. His articles frequently appear in journals like the Palestine Journal of Mathematics and Fibonacci Quarterly , reflecting his deep engagement with number theory, combinatorics, and linear algebra. Research Themes: Sequence Theory, Mathematical Communication, Combinatorial Analysis Collaborators: Eric Fennessey, Ovidiu Bagdasar Key Tools: Generating functions, matrix exponentiation, recurrence relation techniques

Ioannis D Schizasمشاهده پروفایل

دانشیار

• Signal Processing
• Machine Learning
• Data Mining
• +۹ مورد دیگر

Ioannis D. Schizas is an Associate Professor in the Department of Electrical and Computer Engineering at The University of Texas at Arlington (UTA), with a primary appointment in the Nedderman College of Engineering. He joined UTA in 2011, progressing from Assistant to Associate Professor before being promoted to Full Professor (effective September 2024). His research focuses on machine learning, signal processing, distributed systems, and data mining, with applications in sensor networks, remote sensing, and graph-based learning. Education: He holds a Diploma in Computer Engineering and Informatics (University of Patras, Greece, 2004), an M.Sc. (2007), and a Ph.D. (2011) in Electrical and Computer Engineering from the University of Minnesota. Research Interests: Schizas' work spans machine learning algorithms, statistical signal processing, and distributed optimization. Key areas include clustering techniques, kernel methods, dimensionality reduction, and applications in wireless sensor networks, hyperspectral imaging, and multi-target tracking. Publications: His recent work emphasizes scalable machine learning (e.g., kernel-based clustering, neural network pruning for IoT), distributed sensor data processing, and graph filtering for data reduction. Notable trends include fusion of modalities (e.g., hyperspectral unmixing) and real-time systems (e.g., video tracking). Awards: He received the Outstanding Advisor Award (2024) and Advisor Excellence Award (2023) at UTA. His research has been supported by grants from the Army Research Office, AFOSR, and NSF, totaling over $1M in funding. Advising & Grants: Schizas has advised numerous PhD/Master’s students on topics like kernel learning, distributed tracking, and data-driven techniques. His grants include projects on dynamic data-driven systems (e.g., multi-threat tracking, DDROSSIL framework). Labs/Teams: His research group collaborates on projects involving distributed algorithms, sensor networks, and machine learning applications. Active collaborations exist with organizations like Adobe Systems and the Air Force Office of Scientific Research.

Anand Vidyashankarمشاهده پروفایل

استاد

• Biostatistics
• Statistics
• Biotechnology
• +۱۰ مورد دیگر

Anand Vidyashankar is a Professor in the Department of Statistics at George Mason University (Fairfax, VA, USA). He has held academic positions at the University of Illinois at Chicago, University of Georgia, and Cornell University. Previously, he worked in pharmaceutical industries including Abbott Labs, Eli Lilly, and held visiting roles at Searle and the University of Wisconsin Madison's Center for Mathematical Sciences. His research focuses on solving scientific problems through mathematical, statistical, and computational methods. Key areas include biostatistics, bioinformatics, robust inference, branching processes, and risk theory, supported by NSF grants and industry collaborations. He co-organized the ICORS-DSSV 2024 conference, integrating robust statistics and data visualization. His work bridges theory and application, addressing challenges in biopharmaceuticals, finance, and internet-based statistical models. Grants include NSF-funded research on statistical inference for random recursive equations (2011–2014).

Muayyad Jabriمشاهده پروفایل

استاد

• Change Management
• Dialogue Processes
• Organizational Behavior
• +۳ مورد دیگر

Muayyad Jabri is an Adjunct Professor at UNE Business School, University of New England, specializing in change management through dialogue and narrative approaches. His research integrates Bakhtin's philosophical concepts with organizational theory, examining change processes in cross-cultural contexts. With visiting professorships in Europe and China, he has developed globally informed perspectives on management practices. Academic Contributions: Author of multiple books including Rethinking Organizational Change: The Role of Dialogue, Dialectic & Polyphony (Routledge) and over 40 refereed articles. His work has been translated into Japanese, German, and Spanish. Professional Expertise: Accredited practitioner in MBTI and KAI instruments. Editorial board member for Journal of Change Management, Journal of Management Development, and Leadership and Organization Development Journal. Consulting Experience: Advised major organizations including Pfizer, ICI Pharmaceuticals, and Amersham International on team design and organizational change.

Pamela E. Harrisمشاهده پروفایل

استاد

• Algebraic Combinatorics
• Representation Theory
• Graph Theory
• +۴ مورد دیگر

Pamela E. Harris is a Professor of Mathematics in the Department of Mathematical Sciences at the University of Wisconsin-Milwaukee. She is also a cohost of the podcast Mathematically Uncensored and President and co-founder of Lathisms: Latinxs and Hispanics in the Mathematical Sciences. Education: PhD in Mathematics (2012), University of Wisconsin-Milwaukee; M.S. in Mathematics (2008), University of Wisconsin-Milwaukee; B.S. in Mathematics (2005), Marquette University; Associate Degrees in Sciences and Liberal Arts (2003), Milwaukee Area Technical College. Her research focuses on algebraic combinatorics, particularly representation theory of Lie algebras, with applications to parking functions, graph theory, and discrete mathematics. She is a leading advocate for diversity, equity, and inclusion in mathematics, mentoring underrepresented students and co-organizing symposia for SACNAS and the American Mathematical Society. Dr. Harris has authored over 65 peer-reviewed articles and coauthored books such as Asked And Answered: Dialogues On Advocating For Students of Color in Mathematics and Practices and Policies: Advocating for Students of Color in Mathematics . Her work includes developing community agreements and DEI frameworks for academic settings. Scientific Awards: MAA Deborah and Franklin Tepper Haimo Award (2023), MAA Northeast Section Award (2020), MAA Henry L. Alder Award (2019), Council on Undergraduate Research Mentor Award (2019), Karen Uhlenbeck EDGE Fellow (2020). She actively engages in promoting community-building initiatives and has contributed to national dialogues on mentorship, equity, and the intersection of mathematics with social justice.

• Game Theory
• Economic Theory
• Decision Making
• +۳ مورد دیگر

Eran Shmaya is a Professor in the Department of Economics at Stony Brook University, located in the Social and Behavioral Sciences Building. His research focuses on game theory, economic theory, decision-making processes, and microeconomic systems. He is actively involved with the Stony Brook Center for Game Theory, contributing to foundational studies in strategic interactions and informational dynamics. Shmaya's work bridges theoretical economics with applied models, addressing topics such as Bayesian learning, optimal queueing regimes, and the behavioral implications of strategic miscalibration. His recent publications explore collective action problems, regret-minimization frameworks, and the structural analysis of optimal disclosure mechanisms. He teaches graduate-level courses in Microeconomics and Game Theory, reflecting his expertise in these areas. His research has been published in top-tier journals, with a focus on rigorous theoretical contributions and empirical relevance. Notable themes include the analysis of multi-agent systems, stochastic processes in economic contexts, and mechanisms for efficient resource allocation under uncertainty.

Jacqueline Messingمشاهده پروفایل

مدرس

• Language Revitalization
• Multilingualism
• Indigenous Communities
• +۴ مورد دیگر

Jacqueline Messing is a Lecturer in the Department of Anthropology at the University of Maryland (UMD) since 2010, specializing in sociolinguistics, ethnography, and education. She holds a PhD and MA in Anthropology from the University of Arizona and a BA in BDIC/Linguistics & Anthropology from the University of Massachusetts-Amherst. Research Interests: Her work focuses on language revitalization, multilingualism, and identity in Mexico and the U.S., particularly among indigenous communities. She examines how language policies, education systems, and sociocultural factors influence language shift and cultural preservation. Teaching: Courses include Educational Anthropology, Language and Identity, and Native American Languages. She actively engages students through innovative methods like Twitter hashtags for classroom discussions (#UMDLangIDRacism202X). Publications: Her research spans sociolinguistic studies in Tlaxcala, Mexico, and broader analyses of racism in language use. Key works include Language Acquisition, Shift, and Revitalization in Latin America (2016) and a tribute to linguist Jane H. Hill (2019). Advising/Grants: No formal advisee list or grants are mentioned in the provided materials. Her contributions are primarily through teaching and research.

Jeyakesavan Veerasamyمشاهده پروفایل

استاد

• Wireless Networks
• Algorithms
• Computer Science Education
• +۴ مورد دیگر

Dr. Jeyakesavan Veerasamy is a Professor of Instruction in Computer Science and Director of the Center for CS Education & Outreach at the Erik Jonsson School of Engineering and Computer Science, University of Texas at Dallas. His roles include teaching computer science courses, directing outreach programs for K-12 students, and organizing summer research experiences and coding camps. He oversees initiatives such as cyber defense workshops, robotics, game design, and app development programs aimed at fostering computer science literacy in the Dallas area. Education: PhD in Computer Science, University of Texas at Dallas (1999) MS in Computer Science, University of Texas at Dallas (1993) B.E. in Electronics and Communication Engineering, Anna University (1990) Research focuses on wireless networking optimization, approximation algorithms, and computer science education. His work includes patents on wireless network efficiency and contributions to theoretical computer science, such as approximation algorithms for postman problems. He received the Best PhD Dissertation Award in Computer Science (1998-99) for his work on approximation algorithms. Outreach efforts include teacher training programs, professional development workshops, and partnerships with schools to deliver coding classes taught by UTD graduate students. His programs emphasize practical applications of computing through robotics, cybersecurity, and app development.

Dexin Shiمشاهده پروفایل

دانشیار

• Psychometrics
• Statistical Methodology
• Causal Inference
• +۳ مورد دیگر

Dr. Dexin Shi is an Associate Professor in the Department of Psychology at the University of South Carolina, affiliated with the McCausland College of Arts and Sciences. He holds expertise in quantitative psychology, focusing on statistical methodology development and application. Dr. Shi earned his Ph.D. in Quantitative Psychology from the University of Oklahoma (2016) and completed a postdoctoral fellowship at the University of South Carolina. His research emphasizes psychometrics, causal inference, missing data analysis, and model selection, with applications in educational, clinical, and health psychology. He has published over 50 peer-reviewed articles in top journals like Psychological Methods and Structural Equation Modeling . Notable awards include the 2021 Rising Star Award from the Association for Psychological Science and the McCausland Faculty Fellowship (2021–2024). Dr. Shi teaches courses such as PSYC 220 (Psychological Statistics) and advanced quantitative methods like PSYC 815 (Causal Inference). He has received grants for innovative pedagogy and open educational resources. His research trends highlight advancements in statistical techniques, including Bayesian methods, machine learning applications in equating, and causal pathway identification. He actively explores methodological challenges in psychological assessment and data analysis.

Carlos Borgesمشاهده پروفایل

دانشیار

• Inverse Scattering Problems
• Numerical Analysis
• Domain Decomposition
• +۴ مورد دیگر

Carlos Borges is an Associate Professor in the Department of Mathematics at the University of Central Florida (UCF), part of the College of Sciences. He holds a Ph.D. in Mathematics from Worcester Polytechnic Institute (2013) and has held postdoctoral positions at the Oden Institute (University of Texas-Austin) and the Courant Institute (NYU). His research focuses on inverse scattering problems, numerical analysis, and neural networks, with applications in computational engineering and mathematical physics. Education: PhD in Mathematics (Worcester Polytechnic Institute, 2013), MS in Mathematics (Instituto de Matematica Pura e Aplicada, 2007), BEng in Computer Engineering (Instituto Militar de Engenharia, 2002). Research interests include inverse scattering (acoustic, electromagnetic), domain decomposition methods, fast solvers, and machine learning integration in numerical analysis. His work emphasizes high-resolution parameter reconstruction and multi-frequency data utilization for obstacle identification. He advises four students: PhD candidates Isabela Vasconcellos Viana and Nick Arustamyan, and undergraduates Tina Tran and Eli Rivera-Sanchez. His recent publications (2023–2025) highlight advances in neural network-driven inverse scattering and robust algorithms for irregular geometries. He organizes the Scientific Computing Seminar at UCF, focusing on numerical analysis and computational methods. His software contributions include solvers for inverse scattering problems, available on GitHub. He is active in professional societies like SIAM and IEEE, and regularly presents at conferences such as SIAM CSE 2025.