جست‌وجوی استاد و پژوهشگر

Leanna Hernandezمشاهده پروفایل

استادیار

• Neuroimaging in Autism Spectrum Disorders
• Genetics of Psychiatric Disorders
• Sex Differences in Brain Development
• +۵ مورد دیگر

Leanna Hernandez, Ph.D., is Assistant Professor-in-Residence in the Department of Psychiatry and Biobehavioral Sciences at the David Geffen School of Medicine, University of California, Los Angeles. She directs the Hernandez Lab and can be reached at leannahernandez@ucla.edu . Her research integrates multimodal neuroimaging with large-scale genetics to uncover mechanisms underlying autism spectrum disorders, sex differences in brain development, and the role of immune–neurodevelopment pathways such as the complement system. Core themes include: Mapping how common genetic variation shapes brain structure and function across development. Identifying neural signatures that explain the female protective effect in ASD. Elucidating interactions between sleep physiology and brain maturation in youth. Across more than 40 peer-reviewed publications (2012-2023) she has leveraged data from the Adolescent Brain Cognitive Development (ABCD) Study, the GENDAAR Consortium, and multiple international biobanks, generating insights into white-matter microstructure, functional connectivity, and transcriptomic correlates of psychiatric traits. Scientific collaborations span UCLA, UC San Diego, University of Queensland, and the Busselton Health Study, reflecting an interdisciplinary approach that combines neuroimaging, genomics, lipidomics, and behavioral phenotyping. Dr. Hernandez’s laboratory website ( hernandezlabucla.org ) provides further resources, although specific trainees, grants, and awards are not detailed in the supplied text.

Tyler Simkoمشاهده پروفایل

استادیار

• State and Local Politics
• Political Geography
• Subnational Policymaking
• +۵ مورد دیگر

Tyler Simko is an Assistant Professor of Political Science at the University of Michigan, specializing in US state and local politics, political geography, and computational social science. His research focuses on understanding and addressing inequality in American public policy through innovative methodological approaches. Education: Ph.D. in Government, Harvard University (2024) A.B. in Politics, Princeton University Simko's research examines state and local politics in the United States with particular focus on political geography and subnational policymaking. His active research agendas include legislative redistricting ("gerrymandering"), local public meetings, school segregation, affordable housing, and data privacy. Methodologically, he develops new techniques in computational social science and machine learning to evaluate subnational inequality and how it can be reduced. His work regularly involves partnerships with federal, state, and local officials to improve the design of public policy. His recent publications demonstrate a strong focus on applying computational methods to address real-world policy challenges, particularly in school desegregation, redistricting, and local government transparency. His research often leverages large-scale data collection efforts, such as LocalView (the largest database of local government meetings in the US), to analyze patterns of political behavior and policy outcomes across different jurisdictions. Awards and Recognition: APSA 2024-25 Best Paper in Education Politics and Policy Award APSA 2024-25 Best Paper in Urban and Local Politics, Honorable Mention MPSA 2024 Robert H. Durr Award for "the best paper applying quantitative methods to a substantive problem" Derek C. Bok Award for Excellence in Graduate Student Teaching of Undergraduates (2023) Simko teaches graduate and undergraduate courses in American Politics and Political Methodology at the University of Michigan. His teaching experience spans multiple institutions, including Harvard University and Princeton University. He has designed innovative courses on US Local Policymaking, data science, and computational social science. As a Data Scientist at the Office of Evaluation Sciences, he partners with federal, state, and local officials to improve program design and reduce administrative burdens. He is a co-PI of the Algorithm-Assisted Redistricting Methodology (ALARM) Project and co-creator of LocalView, the largest audio, video, and text database of local government meetings in the United States. These projects represent significant contributions to the field of computational social science and provide valuable resources for researchers studying local governance and policy-making.

• Applied Mathematics
• Mechanics of Materials
• Building and Construction
• +۱۱ مورد دیگر

Diego Guillermo Manzanal Milano is an Associate Professor in the Department of Continuum Mechanics and Structural Theory at the Technical University of Madrid. His current institutional affiliations include: Computational Mechanics Research Group (member since October 2020; Adjunto de Dirección General since September 2020) University Research Institute for Intelligent and Sustainable Civil Infrastructures (CIVILis) (member since November 2024) His research spans highly interdisciplinary domains at the intersection of engineering and computational sciences: Core mechanics: Computational Mechanics, Mechanics of Materials, Structural Theory Civil infrastructure systems: Building and Construction, Construction & Building Technology, Geotechnical Engineering Materials science: Multidisciplinary and Miscellaneous Materials Science applications Cross-cutting domains: Applied Mathematics, Computer Science Applications, Energy & Fuels, and Geological Engineering Emerging areas: Sustainable Civil Infrastructures, Interdisciplinary Computer Science in Engineering No scientific awards were documented in the provided information. Details regarding student supervision, research grants, or advising activities were not specified in the source text.

• Large-scale Agile Software Development
• Software Process Improvement
• Empirical Software Engineering
• +۲ مورد دیگر

Torgeir Dingsøyr is an Adjunct Chief Research Scientist and Research Professor in the Department of IT Management at Simula Metropolitan, a leading Norwegian research institute specializing in software engineering and digital technologies. His role encompasses both strategic research leadership and active empirical investigation into large-scale agile software development and software process improvement. Research Interests Large-scale agile software development methods and governance. Coordination and communication challenges in very large development programmes. Software process improvement (SPI) with emphasis on practical, evidence-based approaches. Teamwork effectiveness and autonomous teams in continuous deployment environments. Digital transformation project organization, particularly within Scandinavian contexts. Across more than two decades, Dingsøyr has produced influential handbooks and empirical studies that bridge the gap between SPI theory and industrial practice. His work increasingly addresses second-generation agile methods, emphasizing safety nets for high-risk development and autonomy at scale. Scientific Awards No specific awards listed in the provided text. Advising & Grants Dingsøyr collaborates extensively with industry and academic partners to secure funding for longitudinal case studies and improvement initiatives. While individual student names are not provided, his publications demonstrate active supervision and mentoring within multi-partner projects. Laboratory & Teams He operates within Simula Metropolitan’s research environment, contributing to interdisciplinary teams that unite software engineering researchers, data scientists, and industrial practitioners to advance empirical software engineering and agile transformation.

Hongkai Wenمشاهده پروفایل

استاد

• Machine Learning Systems
• Artificial Intelligence
• Data Science
• +۵ مورد دیگر

Hongkai Wen is a Professor (Chair in Machine Learning Systems) in the Department of Computer Science at the University of Warwick, UK. He holds dual appointments as a Fellow of the Alan Turing Institute (serving as Independent Scientific Advisor for BridgeAI and member of Turing Research Ethics team) and previously worked as Senior Research Scientist at Samsung AI Centre Cambridge and postdoctoral researcher at Oxford University. Education: Computer Science, Keble College, University of Oxford Research Focus: Develops intelligent multi-modal perception systems for real-world deployment with extreme computational efficiency. Core expertise spans ML systems optimization, neural architecture search, and cross-disciplinary applications in robotics, urban mobility, and wearable/IoT security. Pioneered event-based vision techniques and training-free NAS frameworks. Publication Trends: Recent work (2023-2025) demonstrates accelerating innovation in diffusion model efficiency, on-device AI deployment, and sensor fusion techniques. Dominant themes include computational resource optimization for edge devices, multi-modal temporal modeling, and privacy-preserving spatial analytics, with significant contributions to NeurIPS, ICML, and CVPR venues. Scientific Recognition: Best Paper Award, AutoML Conf 2023 (T-CET) Best Paper Runner-up, SenSys 2024 (AdaFlow) Best Paper Awards: IPSN 2014 & EWSN 2013 1st/2nd Place, Zero Cost NAS Competition (AutoML'22) Mentorship & Funding: Actively supervises PhD candidates through thesis committees at Warwick, Ulster, and Queensland universities. Secured National AI Strategy Fund for Macro Neural Architecture Search research. Recruits annually for PhD positions with scholarships from UKRI, Turing Institute, and industry partnerships. Research Leadership: Heads the AI/ML Systems (AMS) Division at Warwick, directing a 15+ member team developing deployable ML frameworks for mobile/robotic platforms. Maintains active collaborations with Samsung AI Centre and Turing Institute's BridgeAI programme on ethical AI deployment.

Zhibin Chenمشاهده پروفایل

استادیار

• Transportation Network Modeling and Optimization
• Intelligent Transportation Systems
• Discrete Optimization
• +۴ مورد دیگر

Zhibin Chen is an Assistant Professor of Engineering at NYU Shanghai and concurrently a Global Network Assistant Professor within the broader New York University system. Since January 2019 he has led research and teaching activities at the Division of Engineering and Computer Science in Shanghai, while maintaining university-wide collaborations through his Global Network appointment. Education Ph.D. in Transportation Engineering, University of Florida (2017) Research Interests Dr. Chen’s scholarship centres on Transportation Network Modeling and Optimization , Intelligent Transportation Systems , and Discrete Optimization . He integrates operations research, data science, and engineering to address emerging challenges in electric mobility, autonomous vehicles, and large-scale urban networks. Recent thrusts include: Data-driven analytics of electric-vehicle charging behaviour under usage heterogeneity. Optimization of charging and swapping infrastructure for electric buses and trucks. Network-level deployment and control strategies for connected and automated vehicles. Day-to-day traffic dynamics and equilibrium models with elastic demand. Pricing, policy, and incentive design for sustainable transportation systems. Scientific Awards Stella Dafermos Best Paper Award – awarded at the 95th Transportation Research Board Annual Meeting. Ryuichi Kitamura Paper Award – also conferred at the 95th TRB Annual Meeting. Editorial & Professional Service Dr. Chen currently serves on the Editorial Advisory Board of Transportation Research Part C: Emerging Technologies , shaping the editorial direction of the leading journal in his field. Grants & Collaborations While specific grant identifiers are not disclosed in the provided text, Dr. Chen’s extensive publication record in top-tier journals ( Transportation Science , Transportation Research Parts B, C, D , IEEE ITS , Applied Energy ) and his editorial role indicate sustained research funding and active collaboration with international partners across North America and China. Laboratories & Teams Operating within the Division of Engineering and Computer Science at NYU Shanghai , Dr. Chen leads a research group focused on next-generation mobility analytics, leveraging the university’s interdisciplinary ecosystem and NYU’s Global Network resources to advance smart and sustainable transportation.

Daniel Hershcovichمشاهده پروفایل

استادیار

• Natural Language Processing
• Cross-Cultural NLP
• Computational Linguistics
• +۷ مورد دیگر

Daniel Hershcovich is a Tenure-Track Assistant Professor at the Natural Language Processing section of the Department of Computer Science, University of Copenhagen. His research focuses on cross-cultural adaptation of language models, integrating human values into AI systems, and evaluating AI's real-world impact in domains like law, literature, and food culture. Research Themes Cultural value alignment in LLMs Multimodal models for accessibility Cross-cultural recipe and food knowledge Historical Scandinavian text analysis Ethical AI and bias mitigation Scientific Recognition SAC Highlight Award (ACL 2025) Outstanding Paper Award (ACL 2017) Advising & Grants : Mentions collaborations on multiple EMNLP/ACL/CoNLL papers. Leads Independent Research Fund Denmark project ALIKE (2025-2027) and contributes to Innovation Fund Denmark's XHAILe (2025-2028). Co-organized SemEval 2019 and CoNLL 2019/2020 shared tasks. Labs & Teams : Leads the CoAStaL research group. Collaborates with teams at IBM Research Haifa, University of Manchester, and Wuhan University of Science and Technology.

Dominik Stammbachمشاهده پروفایل

پژوهشگر ارشد

• Natural Language Processing
• Computational Law
• Misinformation Detection
• +۳ مورد دیگر

Dominik Stammbach is a Postdoctoral Research Associate at Princeton University's Center for Information Technology Policy (CITP) and Polaris Lab, applying Natural Language Processing to enhance access to justice, detect climate misinformation, and combat corporate greenwashing through data-centric methodologies. His educational background includes: Dr. Sc. in Computer Science, ETH Zurich (2024) Master's in Language Science and Technology, Saarland University, Germany Stammbach's research pioneers NLP applications for societal impact, focusing on automated fact checking (evidence extraction from legal documents), AI tools for public defenders, and detection of climate denial narratives. He integrates high-quality data practices with transformer-based models to address real-world challenges in legal accessibility and environmental communication, emphasizing user-centered design through nationwide interviews with public defenders. His publication trajectory reveals accelerating specialization in climate-NLP intersections and legal AI, with 2023-2024 works dominating his output. Key themes include knowledge-base optimization for fact verification, political bias mitigation in LLMs, and environmental claim detection—showcasing methodological rigor through ACL/EMNLP publications and interdisciplinary journal contributions. Stammbach actively shapes research communities as organizer of ClimateNLP workshops (ACL 2024/2025) and keynote speaker at IEEE ICDM 2025, driving collaboration between NLP researchers and climate scientists while developing practical AI tools for public sector agencies.

Irfan Ahmadمشاهده پروفایل

دانشیار

• Pattern Recognition
• Document Image Analysis
• Handwriting Recognition
• +۷ مورد دیگر

Dr. Irfan Ahmad serves as an Associate Professor in the Department of Information and Computer Science at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, where he teaches undergraduate and graduate courses in Computer Science and Software Engineering while conducting research and advising graduate students. His academic service includes committee roles on graduate studies, program development, and competitions. His research expertise centers on Pattern Recognition with specialized focus on Document Image Analysis , Handwriting Recognition , and Machine-Printed Text Recognition . He actively explores Machine Learning applications including Deep Learning and Natural Language Processing , with significant contributions across Artificial Intelligence, Computer Vision, Data Mining, Neural Networks, and Computational Linguistics as evidenced by his PeerJ subject area specializations. Recent publications reveal a strategic emphasis on adaptive deep learning architectures for document analysis, particularly generative methods for handwritten text recognition and knowledge distillation techniques. His editorial work on feature extraction and multilingual fake news detection further demonstrates applied research bridging theoretical machine learning with real-world language processing challenges. As an active Academic Editor for PeerJ Computer Science with 1,205 contribution points, Dr. Ahmad provides substantial service to the scholarly community through manuscript evaluation and editorial oversight across emerging technologies in data science and artificial intelligence.

Elaheh Ahmadiمشاهده پروفایل

استاد مدعو

• Wide Bandgap Semiconductors
• Epitaxial Growth
• Semiconductor Characterization
• +۵ مورد دیگر

Elaheh Ahmadi serves as an Adjunct Professor in the Department of Electrical and Computer Engineering at the University of California, Los Angeles (UCLA), teaching courses 221A and 221B while maintaining status as a Senior Member of IEEE. Her research centers on III-Nitride and Oxide semiconductor systems, specializing in epitaxial growth methodologies and advanced characterization techniques. This work directly enables next-generation device architectures for high-power switching and high-frequency communication systems, with significant applications in energy-efficient electronics and integrated optoelectronic/MEMS platforms. Dr. Ahmadi's exceptional contributions have earned recognition through prestigious awards: International Symposium on Compound Semiconductors Young Scientist Award (2022) University of Michigan EECS Outstanding Achievement Award (2022) DARPA Young Faculty Award (2021) NSF CAREER Award (2021) AFOSR Young Investigator Award (2020) ONR Young Investigator Award (2020) Her research program is supported by substantial competitive funding from federal agencies including NSF, DARPA, AFOSR, and ONR. While the source text does not enumerate current advisees, her device engineering focus inherently involves graduate student supervision in semiconductor fabrication and testing.

Allison Sullivanمشاهده پروفایل

استادیار

• Software Engineering
• Formal Methods
• Programming Languages
• +۳ مورد دیگر

Allison Sullivan is an Assistant Professor of Computer Science at the University of Texas at Arlington (UTA), where she also serves as the Undergraduate Software Engineering Program Director. She is a member of the Software Engineering Research Center (SERC) at UTA and serves as faculty advisor for UTA's Society of Women Engineers (SWE) club. Dr. Sullivan received her PhD in Software Verification, Validation and Testing (SVVAT) from the University of Texas at Austin in 2017 under Sarfraz Khurshid. Her educational background includes: PhD in Software Verification, Validation and Testing, University of Texas at Austin (2017) M.S. in Software Engineering, University of Texas at Austin (2014) B.S. in Software Engineering, University of Texas at Dallas (2012) Dr. Sullivan's research focuses on two primary areas: Automated Software Engineering : Test/Oracle Generation, Automated Bug Localization and Repair, Mutation Testing, and Regression Testing Formal Methods and Programming Languages : Abstractions, Finite Model Finders, Program Synthesis, and SAT/SMT Solvers She leads the SCOPE lab which focuses on 'showing the correctness of all program executions' and has published extensively on Alloy modeling language applications. Her recent publications demonstrate a strong focus on applying formal methods to software engineering problems, with a growing emphasis on the intersection of large language models and software development practices. Her work spans theoretical foundations, tool development, and empirical studies of how developers use modeling languages. Her scientific achievements have been recognized with: NSF CAREER Award (2024) UTA CSE department Rising Star Research Award (2024) UTA College of Engineering Outstanding Early Career Faculty Award (2025) NSF grant for building an educational tool for software modeling ($400k) Dr. Sullivan has successfully advised two PhD students to completion: Dr. Ana Jovanovic (defended November 2024) and Dr. Anahita Samadi (defended February 2025). She actively mentors undergraduate researchers and has secured significant research funding including the NSF CAREER grant. Her service includes committee roles for major conferences including ASE, ISSRE, and FormaliSE. She leads the SCOPE lab at UTA, which brings together graduate and undergraduate researchers to develop techniques for improving software verification and validation, with particular emphasis on making formal methods more accessible to practitioners.

• Black Feminist Theory
• Black Studies
• African American Literature
• +۵ مورد دیگر

Haylee C. Harrell (they/them) serves as an Assistant Professor in the Department of English at the University of Houston's College of Liberal Arts and Social Sciences, with affiliate appointments in African American Studies, Women’s, Gender, and Sexuality Studies, and the Media and Moving Image Program. Their work centers on Black feminist theory and its interdisciplinary connections to critical race studies, philosophy, and literary analysis. Education Background: Ph.D. in Women’s, Gender, and Sexuality Studies from Emory University Bachelor of Arts in English from the University of Utah Research Focus: As a Black feminist theorist, Dr. Harrell critically engages with Critical Black Studies, feminist philosophy, and 20th-21st century African American literature to interrogate questions of gender, sexuality, and blackness. Their scholarship emphasizes creative pedagogical approaches where students explore race/gender/sexuality through diverse expressive mediums, reflecting their own experience as a first-generation scholar. Key research areas include Black Feminist Theory, Affect Studies, Sexuality Studies, and Foucault Studies within Black intellectual traditions. Publication Trends: Dr. Harrell's recent publications (2021-2025) demonstrate sustained engagement with Black feminist thought and critical race theory. Their work reinterprets intellectual legacies like Patricia J. Williams' scholarship while bridging Foucault's theories with Black studies, and examines literary representations of race through tropes like the 'monstrous mulatta.' This output reveals a commitment to intellectual reparations and interdisciplinary dialogue across philosophy, law, and literature. Advising and Grants: The source material does not specify doctoral advisees or formal mentoring relationships, though their teaching of graduate seminars (ENGL 7386/7396) suggests involvement in advanced student supervision. No grant funding details are provided in the available text. Professional Activities: Dr. Harrell actively contributes to the Critical Studies of the Americas collective, fostering transnational perspectives on the Americas. Their affiliation with multiple interdisciplinary programs underscores a commitment to collaborative scholarship beyond traditional departmental boundaries.

• Machine Learning
• Data Mining
• Bioinformatics
• +۱۱ مورد دیگر

Andrea Passerini is a Full Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy, where he also serves as Coordinator of the PhD programme in Information Engineering and Computer Science (Ministerial Decree 45/2013). His academic footprint spans multiple departments including Mathematics, Sociology, Cellular Biology, and Industrial Engineering, reflecting deep interdisciplinary engagement across computational sciences and life sciences. His research centers on Machine Learning and Data Mining with specialized expertise in Neuro-Symbolic AI , Probabilistic Reasoning , and Statistical Relational Learning . He pioneers methods for graph-based learning, medical AI applications, and explainable systems, with significant contributions to bioinformatics (particularly RNA-protein interactions) and healthcare diagnostics. His work bridges theoretical rigor with practical implementations in critical domains. Analysis of his 2025 publications reveals dominant trends in neuro-symbolic integration for graph data, human-AI collaboration in medical decision-making, and robust recommender systems. His research increasingly focuses on interpretable AI for high-stakes applications like surgical planning and physician support, while advancing foundational techniques in graph neural networks and concept-based modeling. As PhD programme Coordinator, Professor Passerini mentors doctoral candidates across AI and computer science disciplines. His collaborative network extends to medical researchers at CIBIO (Cellular, Computational and Integrative Biology department) and industrial partners, though specific lab structures aren't documented in available materials. Current projects emphasize medical AI validation, temporal network modeling, and LLM integration with structured reasoning frameworks.

• Human Activity Recognition
• Wearable Sensors
• Machine Learning
• +۴ مورد دیگر

Thomas Ploetz is an Adjunct Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. His work focuses on sensor-based human activity recognition, wearable computing, and computational behavior analysis with applications in healthcare, smart homes, and education. He leads interdisciplinary research integrating machine learning, IoT systems, and human-centered design. His research interests include improving activity recognition robustness through synthetic data generation, developing explainable AI for time-series analysis, and advancing healthcare technologies like diabetic foot ulcer monitoring systems. He explores ethical implications of wearable sensing in diverse populations, including underrepresented groups. Key contributions include IMUTube (virtual sensor data generation), ProxiCycle (cyclist safety monitoring), and DISCOVER (smart home activity recognition framework). His work addresses challenges in data scarcity, domain adaptation, and long-term system maintenance in pervasive computing environments. He has been awarded grants such as the GVU/IPaT Research and Engagement Grant (2020), and his research appears in top venues like UbiComp and ISWC. He actively contributes to the wearable computing community through conference organization and editorial work.

Maxim Romanovمشاهده پروفایل

پژوهشگر ارشد

• Social history of premodern Islamic world
• Arabic written tradition
• Computational methods
• +۳ مورد دیگر

Maxim Romanov heads 'The Evolution of Islamic Societies' project at University of Hamburg's Asia-Africa-Institut, funded by DFG's Emmy Noether Program. Former positions include senior research fellow at KITAB Project and University of Vienna. Research reconstructs social history of Islamic world (c.600-1600 CE) through computational analysis of Arabic chronicles and biographical collections. Research Focus: Digital humanities approaches to premodern Islamic history including OCR development for Arabic manuscripts, corpus linguistics, and geospatial modeling of historical data. Technical Contributions: Developed OpenITI corpus infrastructure, al-Ṯurayyā gazetteer system, and computational methods for large-scale historical text analysis. Recent work enhances NLP for classical Arabic with OCR accuracy exceeding 90%.