جستجوی استاد راهنمای دانشگاهی

Nicole Novielliمشاهده پروفایل

دانشیار

• Affective Computing
• Software Engineering
• Natural Language Processing
• +۵ مورد دیگر

Nicole Novielli, Ph.D., is Associate Professor at the University of Bari “A. Moro” , Italy, where she conducts research on affective computing applied to software engineering and human-computer interaction. She leads the Collaborative Development Group and coordinates national projects investigating emotions in software teams, AI quality and IoT ecosystems. Education: Ph.D. in Computer Science, University of Bari, 2010 – thesis on “Lexical Semantics of Dialogue Acts” M.Sc. in Computer Science (Knowledge & Software Engineering), University of Bari, 2006 – summa cum laude B.Sc. in Computer Science, University of Bari, 2004 – summa cum laude Visiting researcher at USC-ICT, University of Aberdeen, FBK-irst (Trento) Research interests revolve around recognizing and exploiting affective and cognitive states in computer-mediated cooperative work. She studies sentiment and emotion mining in developers’ textual communication, multimodal emotion recognition via low-cost biometric sensors, and natural-language dialogue simulation for intelligent interfaces. Her work couples software engineering with natural language processing , social media analytics and human-computer interaction . Recent articles (2021-2025) reveal a clear trend: integrating deep learning and large language models into software engineering tasks—automated issue labelling, sentiment classification, technical-debt detection—while validating these techniques through rigorous empirical studies and biometric experiments . A parallel stream explores developer experience , measuring how emotions and cognitive load influence productivity, code quality and collaboration. Scientific awards include the 2020 Apex Award for Publication Excellence , multiple Distinguished Reviewer Awards at flagship venues (ESEC/FSE, ICSME, MSR), the Best Paper Award SANER 2019 and the Best Student Paper Award ACII 2009 . She currently teaches “Sentiment Analysis” in the Data-Science MSc and “Computer Networks” in the ITPS programme. She has advised numerous B.Sc., M.Sc. and PhD projects and is PI or Co-PI of four ongoing grants: EmoQuest (SIR), EMPATHY (PRIN), FAIR-Spoke 6 (PnRR), and QualAI (PRIN 2022). Dr. Novielli serves on the editorial boards of Empirical Software Engineering and Journal of Systems and Software , has guest-edited special issues on affect awareness in SE, and has chaired tracks at ICSE, SANER, MSR, ICSME and SSBSE. She co-leads the Collaborative Development Group and actively releases datasets and open-source tools for the community.

• Survival Analysis
• Longitudinal Data Analysis
• High-Dimensional Data Analysis
• +۸ مورد دیگر

Bin Nan serves as Chancellor's Professor in the Department of Statistics at the University of California, Irvine, where he develops statistical and machine learning methodologies to advance biomedical research and improve human health outcomes through rigorous data analysis. His educational credentials demonstrate a strong quantitative foundation: Ph.D. in Biostatistics, University of Washington (2001) M.S. in Biostatistics, University of Washington (1999) M.S. in Statistics, Virginia Commonwealth University (1997) M.S. in Aerospace Engineering, Beijing University of Aeronautics & Astronautics (1987) B.S. in Aerospace Engineering, Beijing University of Aeronautics & Astronautics (1984) Nan's research program focuses on developing cutting-edge statistical methods for survival analysis, longitudinal data, high-dimensional inference, and machine learning, with direct applications to epidemiology, bioinformatics, and brain imaging. His work addresses critical challenges in biomedical data such as temporal dependence in neuroimaging sequences, estimation of large correlation matrices, and analysis of disease onset with terminal events, all aimed at identifying biomarkers for earlier disease diagnosis. Analysis of his recent publications (2015-2023) reveals a consistent trajectory toward methodological innovation in handling complex biomedical data structures, particularly through de-biased lasso techniques for survival models, neural network applications to censored data, and specialized approaches for longitudinal data with terminal events. These advances predominantly support Alzheimer's disease research and transplant outcome studies. No specific scientific awards were documented in the source material. His research program maintains continuous funding through National Science Foundation and National Institutes of Health grants, including a recent $1.8 million award for Alzheimer's disease methodology development. Nan actively collaborates with the UCI Alzheimer's Disease Research Center and UCI Center for the Neurobiology of Learning and Memory, though student advising details were not provided. His teaching portfolio includes advanced graduate courses in probability theory, survival analysis, and high-dimensional inference. Nan operates within interdisciplinary biomedical research teams focused on translating statistical innovation into clinical applications, particularly through brain imaging analysis and biomarker identification for neurodegenerative diseases.

Moinuddin Qureshiمشاهده پروفایل

استاد

• Computer Architecture
• Memory Systems
• Hardware Security
• +۱ مورد دیگر

Moinuddin Qureshi is a Professor of Computer Science at Georgia Institute of Technology, affiliated with the School of Computer Science and involved in the Online Master of Science in Computer Science (OMSCS) program. He holds a Ph.D. and M.S. from the University of Texas at Austin. His research focuses on computer architecture, memory systems, hardware security, and quantum computing, with notable contributions to mitigating rowhammer vulnerabilities and advancing quantum error correction. Previously, he was a Research Staff Member at IBM T.J. Watson Research Center (2007–2011), where he contributed to caching algorithms for Power-7 processors. He has held leadership roles, including Program Chair of MICRO 2015 and Selection Committee Co-Chair of Top Picks 2017. His work has been recognized with prestigious awards, including the 2019 Persistent Impact Prize and multiple best paper awards. Key research areas include secure memory design (e.g., rowhammer mitigation techniques like MINT and Moat), quantum computing (e.g., Flag-Proxy Networks and Élivágar), and hardware vulnerability analysis (e.g., Roguerfm attacks and COAXIAL memory systems). His publications span 2009–2025, addressing topics like error correction, secure tracking, and quantum annealing optimization. Awards include membership in ISCA, MICRO, and HPCA Hall of Fame, alongside contributions to conferences like HiPC and IEEE MICRO. His work bridges theoretical advancements with practical implementations in both classical and quantum domains.

Rob van Beersمشاهده پروفایل

استادیار

• Motor Control
• Motor Learning
• Spatial Perception
• +۳ مورد دیگر

Rob van Beers is an Assistant Professor at the Faculty of Behavioural and Movement Sciences at Vrije Universiteit Amsterdam, with affiliations to Neurocontrol, IBBA, and AMS - Sports. His research focuses on human motor control, spatial perception, and computational modeling using Bayesian approaches to understand sensory-motor integration under uncertainty. He holds ancillary roles as a Researcher at Radboud University (Nijmegen) since 2015 and serves on the Editorial Board of the Journal of Neurophysiology since 2015. His work contributes to UN Sustainable Development Goals related to health and well-being. Key research interests include motor learning dynamics, sensorimotor adaptation, and the neural basis of spatial orientation. Recent studies explore Alzheimer’s impacts on motor adaptation and Bayesian inference in vestibular path integration. Teaching responsibilities include courses on linear systems dynamics, physical measurement techniques, and motor systems regulation. His work spans 42 peer-reviewed articles, with datasets published on platforms like Dryad and Zenodo.

Harald Van Heerdeمشاهده پروفایل

استاد پژوهش

• Marketing Management
• Branding and Brand Equity
• Econometrics
• +۸ مورد دیگر

Harald Van Heerde is a Research Professor of Marketing at the University of New South Wales, Sydney, within the UNSW Business School's Department of Marketing. He holds roles as Editor of the Journal of Marketing and Executive Vice-Chairman/Program Director of the Marketing Science Hub at AiMark. His academic career includes positions at Maastricht University, the University of Waikato, Tilburg University, and Massey University. Education: Ph.D. in Economics (Cum Laude), University of Groningen, the Netherlands (1999) M.Sc. in Econometrics (Cum Laude), University of Groningen, the Netherlands (1995) Research Interests: Harald focuses on applying econometric models and large datasets to address critical marketing challenges. His work explores marketing mix effectiveness , brand equity , digital marketing strategies , consumer behavior in crises , and cross-industry applications such as retailing, healthcare, and entertainment. Methodologically, he emphasizes dynamic models, endogeneity correction, optimization techniques, and text mining. Articles Trends: Recent publications highlight analysis of inflation's impact on consumer spending , mobile app engagement , brand recovery post-crisis , and econometric frameworks in marketing decision-making. His work bridges theoretical advancements with practical business implications, particularly in stochastic cost industries and global market dynamics. Awards & Fellowships: 2024: AMA Fellow & Shelby/Hunt Best Paper Award 2021: Churchill Award (Lifetime Contributions) 2004–2023: 10+ paper awards including MSI/Root, Paul Green, and multiple long-term impact recognitions Advising & Grants: Currently supervising doctoral candidates Ayesha Hossain (Human Branding) and Ada Choi (consumer financial decision-making). Supervised 12 completed theses across branding, retailing, and digital marketing. Secured over AU$2 million in grants including ARC Discovery, MSI, and the Marsden Fund. His grants examine topics like brand crisis management, price war dynamics, and mobile marketing ROI. Labs & Teams: Leads the Marketing Science Hub at AiMark, a nonprofit connecting academics with household panel data. Consults for global firms including Unilever, Edeka, and AZTEC. His work emphasizes collaborative data-driven research with industry partners.

• Structural Health Monitoring
• Computer Vision
• Artificial Intelligence
• +۳ مورد دیگر

Roya Nasimi, Ph.D., is an Assistant Professor in the Department of Engineering at California State University, East Bay, where she joined in Fall 2023. Her expertise spans structural engineering, computer vision, and artificial intelligence, with a focus on developing innovative solutions for infrastructure monitoring and safety. Dr. Nasimi's educational background includes: Ph.D. with distinction in Structural Engineering from the University of New Mexico Master’s degree in Structural Engineering from the University of Tabriz Bachelor’s degree in Civil Engineering from the University of Tabriz Her research focuses on structural health monitoring using advanced technologies. She integrates computer vision , artificial intelligence , and machine learning to develop systems for monitoring aging infrastructure, particularly bridges. Her work includes designing low-cost and high-end sensor systems, conducting full-scale bridge experiments, and collaborating on interdisciplinary projects to enhance infrastructure safety and resilience. Her recent publications (2021-2025) demonstrate a strong emphasis on non-contact monitoring techniques using drones, lasers, and computer vision. Key trends include the application of deep learning for displacement measurement, digital twinning for infrastructure, and rockfall prevention through machine learning. Her work bridges civil engineering with cutting-edge technology to address critical infrastructure challenges. Dr. Nasimi's research is supported by multiple grants: U.S. Army Corps of Engineers Transportation Research Board (TRB) Transportation Consortium of South-Central States (Tran-SET) New Mexico Consortium She serves on two TRB standing committees and mentors students in structural health monitoring and infrastructure technology. Dr. Nasimi leads interdisciplinary research teams focused on infrastructure monitoring, utilizing drones, lasers, and computer vision systems. Her work involves field experiments on bridges and rail systems, often in collaboration with government agencies and research consortia.

Sina Sarehمشاهده پروفایل

استاد

• Soft robotics
• Multi-modal mobility
• Manipulation and attachment
• +۱ مورد دیگر

Sina Sareh is a robotics researcher at the Royal College of Art (RCA), where he leads the RCA Robotics Laboratory within the School of Design. He has established himself as an expert in soft robotics and multimodal sensing, developing innovative solutions for human safety and access problems in industrial operations. Dr. Sareh's educational background includes: PhD in Robotics from the University of Bristol, where he worked on monolithic design of flexible actuators for operation in confined liquid environments MSc in Control Systems from the University of Sheffield BSc in Electrical Engineering from Amirkabir University of Technology, Tehran Dr. Sareh's research focuses on soft robotics, multi-modal mobility, manipulation and attachment, and multimodal sensing. His work bridges the gap between robotics engineering and practical applications, particularly in medical and industrial settings. He has developed novel approaches to robotic attachment inspired by octopus biology, created haptic interfaces that mimic the feeling of touching human internal organs, and designed soft robotic technologies to help articulate pain symptoms. His research consistently demonstrates innovation in creating adaptable robotic systems that can operate effectively in complex, unstructured environments where traditional rigid robots face limitations. His publication record demonstrates a strong trajectory in robotics research, with emphasis on soft robotics, medical applications, and novel sensing techniques. The research shows progression from fundamental soft actuator design to practical applications in surgery, industrial operations, and human-robot interaction, with a consistent focus on solving real-world problems through biologically inspired approaches. Dr. Sareh has successfully secured multiple research grants, including EPSRC funding for 'Getting a Grip' and 'Multi-vendor Interoperability in Robotics,' as well as InnoHK funding for 'Intelligent Medicine Warehousing.' He has also served as an impact assessor for the Research Excellence Framework (REF) 2021 in Engineering and is a member of the editorial board at IET Cyber-physical Systems and Robotics Journal. Currently, Dr. Sareh advises research students including Filippo Sanzeni, and maintains active collaborations with industry and academic partners through the RCA Robotics Laboratory, which serves as a hub for interdisciplinary robotics research at the intersection of design, engineering, and human-centered applications. His work on projects like 'Topographies of Pain' and 'Reminisys' demonstrates a commitment to applying robotics technology to improve healthcare outcomes and quality of life.

• Materials Science
• Computational Modelling
• Optical Materials
• +۳ مورد دیگر

Arslan Mazitov is a Researcher and Doctoral Assistant at the École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Engineering (STI) and the Institute of Materials (IMX) . He is part of the Computational Science and Modelling Laboratory (COSMO) , focusing on computational materials science with an emphasis on van der Waals materials, optical properties, and machine learning applications. His research explores novel materials for photonics, energy storage, and nanotechnology. Mazitov's work bridges theory and experiment, employing advanced modeling techniques to predict material behavior and design innovative solutions. Key research areas include van der Waals heterostructures , optical anisotropy engineering , and AI-driven materials discovery . He has contributed to studies on semiconductors, 2D materials, and interfacial phenomena. His computational methods address challenges in predicting material stability, optical properties, and surface behavior under various conditions. Active in collaborative projects, Mazitov's work has practical implications for photonic devices, energy storage systems, and nanoscale engineering. His research emphasizes interdisciplinary approaches, combining computational modeling with experimental validation to advance material innovation.

Patrick Hayesمشاهده پروفایل

استاد

• Atmospheric Chemistry
• Air Pollution
• Climate Forcing Agents
• +۴ مورد دیگر

Patrick Hayes is a Full Professor in the Department of Chemistry at Université de Montréal. His research focuses on atmospheric chemistry of air pollution and climate-forcing agents, with expertise in aerosol chemistry, mineral dust dynamics, and analytical spectroscopy. He collaborates with Environment and Climate Change Canada, Quebec’s Ministry of the Environment, and private sector partners like Glencore. Education & Roles: PhD in Chemistry (not explicitly stated, inferred from academic rank) Director of the Hayes Group conducting Arctic fieldwork and computational modeling Teaches courses in environmental chemistry across multiple programs Research Interests: Chemical characterization of atmospheric particles and their climate impacts Mineral surface chemistry and dust emission processes Development of advanced analytical tools for environmental monitoring Study of Arctic aerosol dynamics and transboundary pollution Recent Trends in Publications: Focus on Arctic aerosol behavior and dust dynamics Analysis of urban pollution sources (Beirut/Montreal comparisons) Integration of remote sensing with ground-based measurements Health risk assessments of particulate matter components Awards & Recognition: 2021 Perkin-Elmer Award (CSASS) RSC Analyst Emerging Investigator Award Advising & Grants: Supervised 8+ graduate students since 2016 Lead researcher on 20+ projects, including $2.5M+ in funding from CRSNG, FRQNT, and industry Key roles in networks like EcotoQ and MOACC Labs & Teams: Hayes Group at UdeM with advanced instrumentation capabilities Partnerships with federal/provincial agencies and international collaborators

• Critical Care Medicine
• Immunology
• Trauma Surgery
• +۵ مورد دیگر

Vanessa Nomellini, MD, PhD is an Associate Professor in the Division of Burn, Trauma, Acute and Critical Care Surgery at UT Southwestern Medical Center. She joined UT Southwestern in 2023 as the director of research for her division and leader in the Critical Care Outcomes Research Translation (CORT) group. Education: Dr. Nomellini earned her MD and PhD in Cellular and Molecular Biochemistry from Loyola University. She completed her general surgery residency at the University of Wisconsin and Surgical Critical Care fellowship at the University of Pennsylvania. Research Interests: Her work focuses on immune dysfunction in critically ill patients, particularly sepsis and trauma-induced immunosuppression. She leads studies on immune recovery mechanisms and develops the ICU Recovery Program for long-term patient management. Her NIH-funded research (R35 NIGMS) investigates immune suppression through both animal models and human observational studies. Publications Trends: Her recent work emphasizes sepsis pathophysiology, coagulopathy management, and clinical improvements in critical care. Key areas include immunomodulatory therapies, biomarker utility, and optimizing ICU protocols. Scientific Awards: Recipient of NIGMS R35 grant (2019-current) Advising & Grants: Leads a multi-institutional research team and holds leadership roles in CORT. Her grants focus on translational immunology and critical care outcomes. Labs & Teams: Directs research at UT Southwestern's Critical Care Division, collaborating with Drs. Levi and Carlson in CORT initiatives.

Ryan Giordanoمشاهده پروفایل

استادیار

• Bayesian Statistics
• Machine Learning
• Variational Methods
• +۴ مورد دیگر

Ryan Giordano is an Assistant Professor in the Department of Statistics at the University of California, Berkeley. He holds a PhD in Statistics from UC Berkeley (2019), advised by Michael Jordan, Tamara Broderick, and Jon McAuliffe, an MSc in Econometrics and Mathematical Economics from the London School of Economics (2009), and undergraduate degrees in Mathematics and Theoretical/Applied Mechanics from the University of Illinois at Urbana-Champaign. Prior to academia, he worked as an engineer at Google and HP and served as a Peace Corps volunteer in Kazakhstan. His research focuses on variational methods , Bayesian robustness , sensitivity analysis , and statistical computing , with applications in machine learning, environmental science, and astronomy. He is particularly known for developing scalable Bayesian inference techniques and quantifying the robustness of statistical models to data perturbations. Giordano’s recent work includes studies on Laplace approximation accuracy, MCMC sensitivity to data removal, and robustness metrics for differential expression analysis. He has contributed to open-source statistical software and collaborates with Tamara Broderick’s group at MIT on postdoctoral work (pre-2019 position). His academic trajectory combines theoretical innovation with practical applications, emphasizing reproducibility and computational efficiency in statistical methodology.

Stuart Kurtzمشاهده پروفایل

استاد

• Theoretical Computer Science
• Computational Complexity Theory
• Type Theory
• +۴ مورد دیگر

Stuart Kurtz is a Professor in Computer Science and the College at the University of Chicago, and serves as Master of the Physical Sciences Collegiate Division. He holds the endowed position of George and Elizabeth Yovovich Professor. His research focuses on theoretical computer science, including computational complexity theory, randomness in computation, type theory, and formal logic. He has contributed to foundational areas such as the Berman-Hartmanis Isomorphism Conjecture and the computational properties of random sets. Kurtz is affiliated with the Theoretical Computer Science and Programming Languages Groups at the University of Chicago. He has been recognized with the 2009 Quantrell Award for teaching excellence. His service roles include Director of Undergraduate Studies and Department Chair in Computer Science. He actively mentors Ph.D. students and has advised multiple graduates in complexity theory and related fields. His academic background includes a Mathematics Ph.D. from the University of Illinois, supervised by Carl Jockusch. He approaches type theory as an intersection of formal logic and functional programming. Research interests span measure-theoretic randomness, computational logic, and complexity class separations. His recent work explores connections between theoretical computer science and interdisciplinary fields like physics and statistics. In teaching, Kurtz has instructed courses such as Formal Language Theory, Discrete Mathematics, and Honors Intro Programming. His service contributions include roles in the Computation Institute and Toyota Technological Institute at Chicago. His lab affiliations and collaborative work reflect a strong commitment to advancing theoretical foundations in computer science.

Penina Axelradمشاهده پروفایل

استاد

• Astrodynamics
• Satellite Navigation
• Global Navigation Satellite Systems (GNSS)
• +۵ مورد دیگر

Dr. Penina Axelrad is a University of Colorado Distinguished Professor and Joseph T. Negler Professor of Aerospace Engineering Sciences at the University of Colorado Boulder. She has held academic roles since 1992, serving as Department Chair from 2012–2017. A member of the National Academy of Engineering since 2019, her research focuses on GNSS technology, satellite navigation, and remote sensing applications. She has authored over 223 publications and secured $17.5M in research grants. Education: Ph.D., Aeronautics and Astronautics, Stanford University, 1991 S.M., Aeronautical and Astronautical Engineering, MIT, 1986 S.B., Aeronautical Engineering (Avionics Option), MIT, 1985 Research Interests: Global Navigation Satellite Systems (GNSS), multipath mitigation, GNSS reflectometry, orbital dynamics, and quantum sensing for Earth science. Her work bridges astrodynamics, satellite navigation, and environmental monitoring. Awards: Member, National Academy of Engineering (2019) Women In Aerospace Educator Award (2016) Institute of Navigation Samuel Burka Award (2012) AIAA Summerfield Book Award (2011) Advising & Grants: Advised numerous students (no names listed) and led major grants including NASA Quantum Pathways Institute and Sentinel-6 orbit determination projects. Active in Institute of Navigation leadership roles. Labs/Teams: Colorado Center for Astrodynamics Research (CCAR), Quantum Pathways Institute, and collaborative efforts on CubeSat atomic clock experiments.

• Prevention Science
• College Student Retention
• Parent-Child Relationships in Adolescence and Emerging Adulthood
• +۳ مورد دیگر

Professor Laura Hill serves as Chair and Professor in the Department of Human Development at Washington State University's College of Agricultural, Human, and Natural Resource Sciences (CAHNRS). Her academic career spans over 20 years, including roles as Associate Director for Health Promotion (2011-2014) and Associate/Assistant Professorships. She holds a Ph.D. in Psychology from Vanderbilt University (1998), an M.S. from Vanderbilt (1994), and a B.A. in Greek Studies from Smith College (1979). Dr. Hill's research focuses on prevention science, particularly translating evidence-based interventions into real-world settings. Key areas include brief interventions for college student retention (especially in STEM), parent-child dynamics in emerging adulthood, and workforce development. She leads major grants totaling millions, including a NIH-funded study on parenting interventions for college students and a WSU Strategic Reallocation grant addressing student success through values-based programming. Her funded projects emphasize scalable solutions, such as adapting parenting programs for Spanish-speaking families and evaluating community wellness initiatives. She teaches graduate courses like HD540 (Effective Intervention Programs) and HD513 (Research Methods). Her scholarly work bridges developmental psychology with practical applications, frequently involving students in co-authorship.

• Educational Assessment
• Pedagogy
• STEM Education
• +۳ مورد دیگر

Professor Paul Black is a distinguished academic at King's College London, affiliated with the School of Education, Communication & Society and the Centre for Research in Education in Science, Technology, Engineering & Mathematics (CRESTEM). His career has centered on advancing educational assessment and pedagogy, particularly in STEM disciplines. He is renowned for pioneering formative assessment strategies that integrate learning and evaluation to enhance student outcomes. Research Interests: Black's work explores how teacher-led assessments can drive classroom innovation, emphasizing the synergy between formative and summative methods. His contributions address global educational challenges, including standardization debates and the equitable implementation of assessment frameworks. Key Article Trends: His publications from 2013–2020 highlight themes like ethical assessment practices, the historical impact of formative assessment, and bridging theory-practice gaps in STEM education. Recent works underscore the adaptability of assessment strategies in diverse cultural and linguistic contexts. Professional Impact: The 2023 book 'Educational Assessment: The Influence of Paul Black on Research, Pedagogy and Practice' documents his legacy, noting his influence on scholars worldwide. His ideas have informed policy responses to crises like pandemic-related exam cancellations. Advising & Grants: While specific grants or advisees are not detailed here, his work reflects collaborative research with educators and policy experts. The CRESTEM centre serves as a hub for advancing his vision of holistic educational reform.