جستجوی استاد راهنمای دانشگاهی

Alan Woodwardمشاهده پروفایل

استاد

• Cyber Security
• Digital Forensics
• Cryptography
• +۵ مورد دیگر

Professor Alan Woodward is a renowned computer security expert at the University of Surrey, affiliated with the Surrey Centre for Cyber Security and Computer Science Research Centre. His career spans academia, government service, and private sector leadership, including pivotal roles in IT businesses like Charteris plc. He holds fellowships and chartered status across multiple prestigious institutions and actively advises governmental bodies such as Europol. Education: Undergraduate studies in Physics & Astronomy Postgraduate research in adaptive filtering and signal recovery at the University of Southampton's Institute of Sound and Vibration Research Research Focus: Woodward's interdisciplinary work bridges cybersecurity, digital forensics, and signal processing. His expertise includes cryptographic methods, steganography for covert communications, digital watermarking for data protection, and novel approaches to forensic computing. Current projects explore quantum computing threats and real-world cybercrime mitigation. Publication Trends: His recent articles demonstrate a strong focus on emerging cyber threats across societal and technical domains. Key themes include quantum cryptography vulnerabilities, organized cybercrime patterns, critical infrastructure risks, mobile/cloud security challenges, and public cybersecurity education with practical guidance for digital safety. Honors & Credentials: Fellow: Institute of Physics, British Computer Society, Royal Statistical Society Chartered Status: Engineer (CEng), IT Practitioner (CITP), Physicist (CPhys) Eur Ing (European Engineer) Leadership & Outreach: Beyond academic research, Woodward directs technology enterprises and leads public STEM engagement. He frequently contributes to international media (BBC, The Times, The Telegraph) as a cybersecurity commentator. His Surrey research teams collaborate with law enforcement and industry partners on threat intelligence initiatives.

• Convex Geometry
• Geometric Tomography
• Integral Geometry
• +۳ مورد دیگر

Daniel A. Klain is a Professor in the Department of Mathematics & Statistics at the University of Massachusetts Lowell , part of the College of Sciences. His career focuses on geometric and discrete mathematics, with significant contributions to Convex Geometry and its intersections with probability and combinatorics. Education: Ph.D. in Mathematics (1994), Massachusetts Institute of Technology B.S. in Mathematics (1990), Massachusetts Institute of Technology Research Interests span Convex Geometry, Geometric Tomography, Integral Geometry, and Combinatorics. His work explores geometric inequalities, valuations, and symmetrization techniques, often bridging classical geometry with modern probabilistic and discrete methods. Article Trends highlight his focus on Convex Geometry and Integral Geometry, with studies on Steiner symmetrization, shadow covering, and valuations. His publications also reflect interests in geometric probability, number theory, and educational insights. Scientific Awards and Grants: Mathematical Sciences Teaching Excellence Award (2010, 2003) Sigma Xi Young Faculty Award (2000) Jon A. Bucsela Prize in Mathematics (1990) NSF Graduate Fellowship (1990) National Merit Scholar (1986) NSF grants (2003, 1998, 1996) for convex geometry and geometric analysis Service and Collaborations: Active in teaching, research, and academic service, Klain has co-authored works in geometric probability and presented at numerous international workshops and seminars. His career integrates rigorous mathematical inquiry with educational innovation.

Inbal Arnonمشاهده پروفایل

استاد

• Language acquisition
• Psycholinguistics
• Statistical learning
• +۴ مورد دیگر

Professor Inbal Arnon leads the Language Learning and Processing Lab at the Hebrew University of Jerusalem , focusing on how language knowledge emerges through cognitive mechanisms in first and second language acquisition. Her research bridges Cognitive Science , Linguistics , and Psychology , with a special emphasis on statistical learning, Zipfian distributions, and multiword units. Current projects include funded studies on learnability advantages of Zipfian distributions in language Investigations into cross-species communication through whale song analysis Developmental trajectories of statistical learning in children Her methodological approach combines computational modeling, experimental studies, and corpus analysis. Arnon’s work has been highlighted in Science , The New York Times , and Haaretz , with a particular focus on how cognitive biases shape language structure over time. The lab maintains a diversity commitment to recruit underrepresented groups in sciences and hosts a public-facing research space at the Bloomfield Science Museum . Arnon’s team actively explores cultural transmission mechanisms and language evolution through interdisciplinary collaborations.

Michelle Hoda Wilkersonمشاهده پروفایل

پژوهشگر

• Computational Literacy
• Scientific Computing
• Visual Data Analysis
• +۱۲ مورد دیگر

Michelle Hoda Wilkerson is a learning scientist at the University of California, Berkeley, affiliated with the Berkeley School of Education. She directs the Computing, Reasoning, and Expression (CoRE) Lab, focusing on computational literacy and the integration of scientific computing tools into precollegiate curricula. Her research emphasizes visual data analysis, agent-based simulations, and their social implications in domains like climate and health. Her scholarly contributions appear in journals such as Educational Researcher , Journal of the Learning Sciences , and Science Education . Notable awards include the National Science Foundation Early CAREER Award (2014) and the AERA Division C Jan Hawkins Award (2020). She co-organized the National Academies Workshop on K-12 Data Science Education (2022). Her research highlights the interplay between computational tools, data reasoning, and socio-cultural contexts, advocating for inclusive, humanistic approaches to data science education. Key themes include equity in technology access, teacher education, and leveraging personal experiences in learning environments. NSF Early CAREER Award (2014) AERA Jan Hawkins Award (2020)

Pierre Lermusiauxمشاهده پروفایل

استاد

• Ocean Data Assimilation
• Numerical Ocean Modeling
• Uncertainty Quantification
• +۷ مورد دیگر

Pierre Lermusiaux is the Nam Pyo Suh Professor of Mechanical Engineering and Associate Department Head for Operations Research at MIT. His research focuses on numerical ocean modeling, data assimilation, uncertainty quantification, and applications to ocean dynamics and engineering. He holds a B/M.Eng. from University of Liège, M.Sc. and Ph.D. from Harvard University. Recognized with awards like the MIT Doherty Chair and Spira Teaching Award, his work bridges computational science and marine systems. Education: B/M.Eng., University of Liège, 1992 M.Sc., Harvard University, 1993 Ph.D., Harvard University, 1997 Research Interests: Combines oceanographic modeling with advanced computational methods. Specializes in stochastic ocean prediction, autonomous systems optimization, and interdisciplinary applications of uncertainty quantification. His work enables real-time environmental forecasting and marine robotics navigation strategies. Publications: Focus on developing computational frameworks for probabilistic ocean forecasts, acoustic propagation modeling, and machine learning-based environmental prediction systems. Recent work emphasizes adaptive sampling strategies and energy-efficient path planning for underwater vehicles. Awards: Fulbright Foundation Fellowship (1993-96) Ruth and Joel Spira Award for Teaching (2010) MIT Doherty Chair in Ocean Utilization (2009-2011) Advising & Grants: Leads MIT’s MSEAS group and has secured funding from NSF, ONR, and international collaborations. Advises projects on ocean robotics, climate modeling, and underwater acoustics. Key contributions include the MIT Red Sea Modeling System and real-time forecasting platforms. Labs/Teams: Directs MIT’s multidisciplinary ocean modeling efforts, integrating mechanical engineering, computer science, and environmental science. Co-leads initiatives like the Ocean Predictions with Ensembles (OPEN) project and the METEOR autonomous observatory system.

• Augmented Reality
• Virtual Reality
• Mixed Reality
• +۶ مورد دیگر

Abey Campbell is an Assistant Professor in Computer Science at the School of Computer Science, University College Dublin. He holds roles such as Deputy Programme Director for Computer Science, Director of UCD VR Lab, and 1st Year Stage Coordinator. His research focuses on Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), and Multi-Agent Systems with applications in education, healthcare, and human-computer interaction. Campbell has coordinated modules like Augmented and Virtual Reality, Computer Graphics, Game Development, and Mobile Computing. He earned his BSc and PhD in Computer Science from University College Dublin. His work explores touchless interaction technologies, machine learning agents in STEM education, and ethical implications of emerging technologies. Notable contributions include RenderKernel for real-time rendering systems and studies on AR's role in decision support systems. Campbell has secured a grant from Enterprise Ireland for collaborative design documentation and participates in professional activities like peer reviewing for Frontiers in Virtual Reality and IEEE conferences. His collaborative projects include developing AR tools for veterinary training and evaluating immersive VR experiences in nursing education. The UCD VR Lab under his direction focuses on applied research in spatial computing and interactive systems.

Michele Birdمشاهده پروفایل

مدرس

• Statistics Education
• Applied Statistics
• Statistical Tutoring

Michele Bird serves as an Academic Professional Lecturer in the Department of Mathematics and Statistics at the University of Wyoming, teaching foundational courses like Stat 2000: Statistics and the World and Stat 2050: Introduction to Statistics. She also coordinates the statistics program for the Center for Assistance with Statistics and Mathematics (CASM), directing tutoring services and seminars. Education : M.S. in Statistics from the University of Nevada Las Vegas. Her professional focus centers on statistics education methodology and student support systems, with emphasis on developing effective tutoring frameworks for introductory statistics learners. As CASM Statistics coordinator, she designs training for tutors and optimizes resource allocation to enhance course comprehension. Bird's work directly impacts student success in quantitative disciplines through structured academic assistance, leveraging her expertise in statistical pedagogy to bridge learning gaps in core curriculum requirements.

HanQin Caiمشاهده پروفایل

استادیار

• Mathematical Optimization
• Data Science
• Machine Learning
• +۵ مورد دیگر

Dr. HanQin Cai is the Paul N. Somerville Endowed Assistant Professor in the Department of Statistics and Data Science at the University of Central Florida (UCF), also serving as Director of the Data Science Lab. He holds a joint appointment with the Department of Computer Science. His research focuses on theoretical and algorithmic foundations of mathematical optimization, data science, and machine learning, with emphasis on non-convex algorithms, adversarial attacks, signal/image processing, and deep learning integration. He has secured NSF grants totaling over $2.6M, including a $121K single-PI grant and a $2.49M co-PI grant. His work has been recognized with the UCF OSCaR Award (2025) and IEEE Senior Member status (2024). Education: PhD in Applied Mathematical and Computational Sciences from University of Iowa (2018), with M.S. in Mathematics (2014) and M.C.S. in Computer Science (2017). Previously served as a Postdoc at UCLA Mathematics Department under Dr. Wotao Yin. Research highlights include: query-efficient zeroth-order optimization, robust signal processing with corrupted data, adversarial attacks on neural networks, and tensor-based methods for high-dimensional data analysis. His recent publications explore advanced techniques in matrix recovery, tensor decompositions, and explainable AI. Grants & Awards: NSF DMS-2304489 (2022–2025), NSF DUE-2321986 (2024–2029), UCF OSCaR Award, IEEE Senior Membership. Labs & Teams: Directs UCF's Data Science Lab, collaborates across disciplines in statistics, computer science, and engineering.

• Social Hierarchies
• Negotiation
• Groups and Teams
• +۹ مورد دیگر

Michael Schaerer is an Associate Professor of Organizational Behaviour & Human Resources at the Lee Kong Chian School of Business, Singapore Management University , where he has been since 2022. His research focuses on social hierarchies , negotiation dynamics , power/status , and organizational well-being . He leads the Sustainable Business Research Peak at SMU. PhD in Management (Organizational Behavior) , INSEAD (2012-2017) M.Sc. in International Management , London School of Economics (2009-2010) B.A. in Business Administration , University of St. Gallen (2006-2009) His work on power dynamics and negotiation has generated significant insights into how low-power individuals navigate social hierarchies, manage paranoia, and achieve better outcomes. Recent studies explore compensation suppression in social impact contexts and gender discrimination in hiring . His meta-analyses provide longitudinal perspectives on workplace bias. He has received 16 major awards , including the 2023 IACM Outstanding Conference Paper Award , 2020-23 Lee Kong Chian Fellowship , and 2017 INSEAD MBA Alumni PhD Award . His teaching excellence has been recognized through the Dean's Teaching Honor List (2018-2023) and 2020 MIM Teaching Award . As a research advisor, he guides doctoral students in organizational behavior and human resources. His work intersects with psychology, behavioral economics , and positive organizational scholarship , supported by grants like the Swiss National Science Foundation Doc Mobility Scholarship (2015-2016) .

Azizur Rahmanمشاهده پروفایل

استاد

• Data Science
• AI and Machine Learning
• Statistics
• +۷ مورد دیگر

Professor Azizur Rahman is a leading academic in applied statistics and data science at Charles Sturt University (Australia), where he leads the Data Mining Research Group and directs the Data Analytics Lab. He holds a PhD in Economics and Applied Statistics from the University of Canberra, with postdoctoral experience at the University of Adelaide. His expertise spans statistical methodologies, microsimulation, AI/ML, and data-driven policy analysis. He has attracted over $4.03M in research funding and published over 200 scholarly works. Education: BSc (Honours) in Statistical Science, University of Chittagong (2000) MSc (Thesis) in Biostatistics, University of Chittagong (2003) PhD in Economics and Applied Statistics, University of Canberra (2010) Research Focus: Big data analytics and AI applications in health, environment, and policy Bayesian inference and multilevel modeling Spatial microsimulation for socioeconomic analysis Water quality modeling and environmental systems Public health challenges in developing nations Key Contributions: Developed novel computational methods for microsimulation modeling Founder of the Data Analytics Lab at CSU Editorial roles in journals like PLOS ONE and International Journal of Microsimulation Recipient of 2023 ANZRSAI Outstanding Service Award and Charles Sturt Excellence Awards Grants & Awards: $4.03M+ external research funding secured 30+ awards including travel grants, fellowships, and service recognitions Advising & Mentorship: Supervised 6 PhD/DIT students and co-supervised many more. Active in mentoring early-career researchers through editorial boards and conference organizing roles. Labs & Collaborations: Leads DaMRG (Data Mining Research Group) and collaborates with global institutions on interdisciplinary projects involving AI/ML, environmental science, and public health.

Lane Harrisonمشاهده پروفایل

دانشیار

• Information Visualization
• Visual Analytics
• Human-Computer Interaction
• +۳ مورد دیگر

Lane Harrison is an Associate Professor in the Department of Computer Science at Worcester Polytechnic Institute (WPI), where he directs the Visualization and Information Equity lab (VIEW). His research leverages cognitive and perceptual principles to improve information visualization and visual analytics systems, with critical applications in cybersecurity and health-risk communication for high-stakes decision-making. His educational background includes a BS (2009) and PhD (2013) in Computer Science from the University of North Carolina, Charlotte. Prior to WPI, he was a Postdoctoral Researcher at Tufts University's Visual Analytics Lab. Harrison's research focuses on empirical evaluation of visualization techniques , investigating how cognitive principles can optimize user performance with visual representations. He develops design guidelines for effective visualizations in domains like cybersecurity and healthcare, while creating adaptive systems that integrate models of user abilities. His work bridges theoretical foundations with practical applications to address real-world challenges in data interpretation. Analysis of his 2016-2021 publications reveals consistent emphasis on user-centered evaluation methodologies , including crowdsourcing and controlled experiments. Key trends include quantifying exploration behaviors in web visualizations, addressing cognitive biases in data reproduction, and developing healthcare-focused analytics for drug interactions and risk communication. His research demonstrates strong interdisciplinary connections between visualization, cognitive science, and domain-specific applications. His scientific recognition includes: Best Paper Award at ACM CHI 2016 for adaptive interface research Harrison secures significant research funding including an NSF Grant (2022) for visualization studies and participates in an 11-school AI collaboration for intelligence professionals (2025). He teaches data visualization and web programming courses, mentoring students through the VIEW lab on projects applying visualization techniques to social issues and scientific domains. He directs the VIEW lab at WPI, which develops computational methods to understand how people engage with data visualizations while emphasizing equitable information access. Current projects integrate user modeling with visualization systems to optimize design for diverse cognitive abilities and application contexts.

• Clinical Trials
• Maternal and Fetal Medicine
• Hypertension Management
• +۴ مورد دیگر

Jeff Szychowski is a Professor and Chair of Biostatistics at the University of Alabama at Birmingham (UAB), School of Public Health. He holds multiple academic roles, including Department Chair and Vice Chair of Research and Faculty Development. He earned his PhD in Statistics from the University of Alabama. His research focuses on clinical trials, maternal and fetal medicine, hypertension management, and biostatistical methodologies. He has led numerous grants, including NIH-funded studies on maternal health and cardiovascular outcomes. Szychowski has advised over a dozen graduate students and contributed to over 200 scholarly works, with recent studies emphasizing blood pressure control in hypertensive pregnancies and structural barriers in global maternal care. He actively participates in professional committees and serves as a peer reviewer for journals like the American Journal of Obstetrics and Gynecology. Education: PhD in Statistics, University of Alabama (2006). Research Interests: Clinical trials in maternal-fetal medicine, hypertension in pregnancy, categorical data analysis, and biostatistical methodologies. His work bridges statistical rigor with clinical impact, particularly in high-risk obstetric populations. Grants: Over 30 grants, including leadership of the CHAP trial (Chronic Hypertension and Pregnancy), NIH-funded studies on maternal cardiovascular health, and interventions to reduce disparities in maternal outcomes. Professional Activities: Member of the Society for Clinical Trials and Society for Maternal-Fetal Medicine. Chair of Alabama Chapter committees and DSMB roles. Active in curriculum development and educational policy at UAB. Key Contributions: Pioneered protocols for antihypertensive therapy in pregnancy, evaluated postpartum outcomes, and addressed racial disparities in peripartum cardiomyopathy. His work in Cameroon highlighted structural barriers to maternal care in conflict zones. Labs/Teams: Leads the Biostatistics Department at UAB, fostering interdisciplinary research in maternal health, cardiovascular biology, and clinical trial design.

Praveen Tripathiمشاهده پروفایل

استادیار

• Machine Learning
• Data Mining
• Spatio-Temporal Data Analysis
• +۳ مورد دیگر

Praveen Tripathi is a Research Assistant Professor in the Department of Computer Science at Stony Brook University. His research focuses on Machine Learning, Data Mining, Spatio-Temporal Data Analysis, and Time Series Data Analysis. He has contributed to trajectory analysis frameworks, recommendation systems with temporal influence, and optimization algorithms. While his biography section is not detailed here, his work emphasizes practical applications of spatio-temporal data and multi-objective optimization. Awards are listed in the menu but specific details are not provided in the text. His publications span cybersecurity, trajectory analysis, and financial market dynamics, reflecting a strong interdisciplinary approach. No advising or grant information is explicitly mentioned in the provided content.

Marsha Kline Pruettمشاهده پروفایل

استاد

• Co-parenting
• Father involvement
• Family systems dynamics
• +۳ مورد دیگر

Marsha Kline Pruett, the Maconda Brown O'Connor Professor at the Smith College School for Social Work, is a leading scholar in co-parenting, father involvement, and family systems dynamics. She directs the Ph.D. program and teaches doctoral/masters courses while also providing clinical services and consulting on organizational dispute resolution. Education: B.A., University of Pennsylvania M.S., University of Pennsylvania M.S.L., Yale School of Law Ph.D., University of California at Berkeley ABPP (American Board of Professional Psychology) Her research focuses on father engagement , co-parenting interventions , and family policy . Key projects include the Supporting Father Involvement initiative and development of cross-culturally valid coparenting tools now translated into six languages. Recent publications reveal trends in attachment theory , child welfare , and cross-national program implementation . She has received the Stanley Cohen Award for Distinguished Research (2017) and contributed to UK's Parents as Partners program recognized nationally. As a clinical psychologist and attorney, she bridges legal and mental health disciplines. Current work includes integrating the Supporting Father Involvement program into the Brazelton Touchpoints Center and validating coparenting tools across cultural groups.

Jim Haglundمشاهده پروفایل

استاد

• Algebraic Combinatorics
• Enumerative Combinatorics
• Symmetric Functions
• +۲ مورد دیگر

Jim Haglund is Professor of Mathematics at the University of Pennsylvania, specializing in algebraic and enumerative combinatorics. His research explores symmetric functions, Macdonald polynomials, combinatorial statistics, rook theory, and polynomial root behavior. He directs the CAGE seminar and IPAC seminar series, fostering collaboration in combinatorics. Dr. Haglund's work connects combinatorics with representation theory and special functions, particularly through Macdonald polynomial operators and the Delta Conjecture. His research employs both theoretical frameworks and computational experimentation. Analysis of recent publications reveals consistent focus on combinatorial structures underlying symmetric functions, with innovations in delta operators, chromatic quasisymmetric functions, and rook theory generalizations. His work frequently bridges combinatorics with algebraic geometry and representation theory. Awards & Recognition: Fellow of the American Mathematical Society Editorial boards: Journal of Combinatorics and Involve Advising & Collaboration: Mentored 16 PhD students and numerous postdoctoral researchers. Leads combinatorial research group exploring connections between Macdonald theory, diagonal harmonics, and algebraic geometry.