جستجوی استاد راهنمای دانشگاهی

• Computer Vision
• Biometrics
• Forensics
• +۳ مورد دیگر

Dr. Kevin Hernandez Diaz is a Postdoctoral Researcher at Halmstad University's School of Information Technology, specializing in computer vision and biometrics. His work bridges theoretical advances in deep learning with practical applications in security, industrial safety, and healthcare. His primary research interests include: Ocular and periocular biometrics for unconstrained environments Deep learning model optimization for edge/mobile deployment Computer vision solutions for industrial safety (PPE/fire detection) Explainable AI for biometric verification systems Cross-spectral recognition and synthetic data generation Analysis of his 15 most recent publications (2020-2024) reveals consistent innovation in making biometric systems robust for real-world deployment. His work shows strong emphasis on practical constraints like computational efficiency, pandemic adaptations, and industrial environmental challenges, with increasing focus on explainability and privacy preservation. His scientific contributions include: Novel architectures for lightweight face recognition (SqueezerFaceNet) Explainable verification frameworks for biometric systems Industrial safety applications using YOLOv4 Thermal-based healthcare monitoring solutions Cross-spectral periocular recognition techniques Dr. Hernandez Diaz maintains active research collaboration within Halmstad University's computer vision community and participates in industry-focused projects addressing real-world computer vision challenges. His doctoral work established new benchmarks for ocular recognition in unconstrained settings, and his current research continues to push boundaries in efficient and robust biometric systems.

Alper Çelikelمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Data Science
• +۲ مورد دیگر

Dr. Alper Çelikel is an Associate Professor at the Department of Computer Engineering, Faculty of Engineering and Natural Sciences, İstanbul Okan University. He specializes in machine learning, artificial intelligence, and data science with specific focus areas including natural language processing, computer vision, and optimization of neural network architectures. Education: PhD in Computer Science from Boğaziçi University (2014) Research Focus: Deep learning, cross-lingual systems, and multi-modal learning Leadership: Director of Research and Development Policy at İstanbul Okan University His recent research explores hybrid CNN-Transformer architectures, federated learning in healthcare, and explainable AI frameworks. He has received prestigious awards including the TÜBİTAK Career Award (2018) and Turkish Academy of Sciences Young Scientist Award (2015). Dr. Çelikel has supervised multiple graduate researchers and actively contributes to curriculum development and academic quality assurance initiatives. TÜBİTAK Career Award (2018) Turkish Academy of Sciences Young Scientist Award (2015) As an academic leader, he chairs the Research and Application Centers Directorate and contributes to university-wide policy development including information security, education, and research protocols.

• Pervasive Healthcare
• Context-Awareness
• Activity Recognition
• +۲ مورد دیگر

Daniele Riboni is an Associate Professor at the Department of Mathematics and Computer Science , University of Cagliari , where he has held this position since 2015. Previously, he was a postdoctoral fellow and assistant professor at the University of Milano , where he earned his Ph.D. in Computer Science in 2007. His research focuses on pervasive healthcare , context-awareness , activity recognition , and privacy in pervasive computing . His recent publications emphasize machine learning and sensor networks for cognitive assessment in smart homes, explainable AI in healthcare, and biomedical data mining . Key areas include graph neural networks , large language models , and ontology generation . Notably, he has contributed to datasets like AnnoMI for counseling dialogues and systems like FootApp for sports analytics. He has organized workshops such as CoMoRea 2024 and CoMoRea 2015 , focusing on context modeling and activity recognition. No specific scientific awards, students, or grants are detailed in the provided texts.

Neil Smalheiserمشاهده پروفایل

استاد

• Neuroscience
• RNA Biology
• Synaptic Plasticity
• +۵ مورد دیگر

Neil Smalheiser is a Professor in Psychiatry at the University of Illinois Chicago , with dual expertise in neuroscience and medical informatics . He directs two laboratories: one focused on small RNAs in brain function and disease, and another dedicated to informatics tools for hypothesis generation and data analysis. His research spans RNA biology , synaptic plasticity , pathogenesis of neuropsychiatric disorders , and text mining . Smalheiser has developed innovative tools like Anne O'Tate and Arrowsmith for biomedical literature analysis and leads NIH-funded projects on data synthesis and systematic reviews. Recent work explores exosomal RNA transfer , microRNA regulation , and automated indexing of scientific articles . He was named an ACMI Fellow (2023) and holds multiple NIH grants for medical informatics research. Smalheiser's lab investigates how RNA molecules influence synaptic plasticity and mental health, while advancing computational methods for evidence synthesis. Scientific Awards : ACMI Fellow (2023) NIH R01 Grants (2016–2020, 2023) NIH NIA P01 AG039347 Grant (2017–2018) Fellow of the American Medical Informatics Association (2021)

ChengXiang Zhaiمشاهده پروفایل

استاد

• Intelligent information systems
• Information retrieval
• Data mining
• +۴ مورد دیگر

ChengXiang Zhai is the Donald Biggar Willett Professor in Engineering at the University of Illinois at Urbana-Champaign , holding appointments in the Department of Computer Science , Carl R. Woese Institute for Genomic Biology , and the Department of Statistics . He leads research in intelligent information systems, with a focus on information retrieval, data mining, NLP, and machine learning. His TIMAN research group and DAIS explore applications in healthcare, education, and scientific discovery. He develops MOOCs on text retrieval and mining, and has published extensively on topics including LLM alignment, user simulation, and multimodal systems. Key Research Areas : Intelligent search engines, explainable AI, human-AI collaboration, biomedical informatics Recent Trends : LLM economics, knowledge overshadowing, just-in-time recommendation systems He has received the ACM Fellow title, SIGIR Salton Award , and multiple teaching honors including Rose Award and Graduate Mentoring Award . He serves as series editor for Springer Information Retrieval Book Series .

Kayhan Batmanghelichمشاهده پروفایل

استادیار

• Medical Vision
• Machine Learning
• Bioinformatics
• +۱۱ مورد دیگر

Kayhan Batmanghelich is an Assistant Professor in the Department of Electrical and Computer Engineering at Boston University , where he also holds affiliations as a Hariri Institute Junior Faculty Fellow and AIR Affiliate . Previously, he served as an Assistant Professor at the University of Pittsburgh's Department of Biomedical Informatics with a secondary appointment in their School of Computing and Information. Education : Ph.D. in Computer Science from the University of Pennsylvania (2012) Research Interests : Focus on overcoming AI challenges in healthcare, including Explainability, Data Efficiency, Multimodal Data Fusion, and Causality. His research develops AI systems for medical imaging, genetics, and electronic health records, particularly targeting diseases like Chronic Obstructive Pulmonary Disease (COPD) , Alzheimer’s Disease , and Non-Alcoholic Fatty Liver Disease (NAFLD) . Key innovations include biomechanically-informed neural networks for lung tissue stiffness estimation and graph-based AI for multi-scale pulmonary disease analysis. Recent publications highlight multimodal frameworks for COPD subtyping, vision-language models in mammography, and diffusion models for 3D CT synthesis. His work has been recognized with the NSF CAREER Award and Google Academic Research Award (GARA) , alongside Hariri Institute grants. Awards : NSF CAREER Award (2025) Google Academic Research Award (2024) Hariri Focused Research Program Awards (2024) His BatmanLab trains students in medical AI and collaborates with institutions like the University of Pittsburgh School of Medicine and Brigham and Women’s Hospital. Funding sources include NIH, NSF, and industry partnerships.

Anqi Liuمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Distributionally Robust Learning
• +۵ مورد دیگر

Anqi Liu (Angie) is an Assistant Professor in the Department of Computer Science at the Whiting School of Engineering, Johns Hopkins University. She is affiliated with the Data Science and AI Institute, Mathematical Institute for Data Science (MINDS), and Institute for Assured Autonomy (IAA). Her research focuses on developing principled machine learning algorithms for reliable, trustworthy, and human-compatible AI systems in high-stakes applications. PhD in Computer Science from University of Illinois Chicago Postdoctoral Research at Caltech's Department of Computing and Mathematical Sciences Her work emphasizes robustness to changing data environments, uncertainty quantification, and human-AI interaction. Key methodologies include distributionally robust learning, active learning, safe exploration, fair machine learning, and conformal prediction. Applications span healthcare (NIA/NIH-funded), robotics, and computational social science. Amazon Research Award Johns Hopkins + Amazon Initiative for AI Faculty Research Johns Hopkins Discovery Award Institute for Assured Autonomy Challenge Grant She advises PhD candidates in AI safety and fairness, with students co-advised by faculty in Human-Robot Interaction and Computational Linguistics. Collaborations include Center for Language and Speech Processing (CLSP) and Laboratory for Computational Sensing and Robotics (LCSR).

Wei Chenمشاهده پروفایل

استاد

• Data Visualization
• Visual Analytics
• Biomedical Image Computing
• +۵ مورد دیگر

Wei Chen is a Professor at the State Key Laboratory of CAD&CG, College of Computer Science, Zhejiang University, Hangzhou, China. His academic journey began and ended at Zhejiang University, where he earned both his Bachelor's (1996) and Ph.D. (2002) in Computer Science, followed by a visiting Ph.D. position at the Fraunhofer Institute in Germany (2000-2002) and a visiting scholar role at Purdue University (2006-2008). Research Focus: Visualization, Visual Analytics, Biomedical Image Computing, Big Data Analytics. Academic Leadership: Served on editorial boards of journals like IEEE Transactions on Visualization and Computer Graphics, Journal of Visual Informatics, and as Chair of IEEE Pacific Visualization Symposium. Impact: Over 110 IEEE/ACM Transactions and CCF-A papers, four Chinese textbooks on visualization, and two monographs on big data technology. His recent publications (2023-2024) span domains like visual analytics for health insurance fraud detection, quantum circuit visualization, federated learning visualization, urban mobility modeling, and AI-enhanced cultural heritage preservation. A thematic trend shows integration of deep learning, large language models, and human-in-the-loop systems with visual interfaces. Scientific Awards include the Zhejiang Province Natural Science First Prize (2021, 2017), CCF Technology Invention First Prize (2020), Wu Wenjun Artificial Intelligence Science and Technology Progress First Prize (2023), and multiple Best Paper/Poster recognitions at IEEE VIS and Pacific Visualization conferences. He actively mentors graduate students and leads the Visual Analytics Group , contributing to national and international standards in visualization research. His editorial and organizational roles in top conferences further solidify his influence in shaping the field.

• Information Retrieval
• Knowledge Graphs
• Natural Language Processing
• +۵ مورد دیگر

Florina Piroi is a Senior Scientist (Research Fellow) at the Center for Research Data Management (E058-06) within the Faculty of Informatics at TU Wien. Her research integrates information retrieval, knowledge graphs, and semantic technologies to advance exploratory search systems and research data infrastructure. Her core research interests include: Information Retrieval evaluation and validation methodologies Knowledge graph applications for domain-specific search Patent text mining and semantic technologies Medical concept normalization and entity linking Argumentative zoning in scientific documents Table extraction and classification systems Analysis of her recent publications reveals strong trends in applying machine learning to specialized IR tasks, particularly in patent analysis and medical text processing. Her work emphasizes robust evaluation frameworks and cross-lingual capabilities, with consistent contributions to the CLEF campaign and PatentSemTech workshops. Dr. Piroi actively collaborates with international researchers through the Network Lab at TU Wien and contributes to the university's Center for Research Data Management, focusing on semantic technologies for research data infrastructure and scholarly communication systems.

Tim Althoffمشاهده پروفایل

استادیار

• Data Science
• Natural Language Processing
• Mental Health Informatics
• +۳ مورد دیگر

Tim Althoff is an Assistant Professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where he directs the Behavioral Data Science Group. His research combines data science, social network analysis, and natural language processing to develop computational methods for understanding human behavior, mental health, and public health through digital traces.

• eHealth
• Cyber-security
• Internet of Things
• +۳ مورد دیگر

Prof Ahmed Al-Dubai is a Professor at the School of Computing Engineering and the Built Environment , Napier University. His research spans eHealth , Cyber-security , and Internet of Things domains. Research interests include: Edge computing, Network security, Smart cities, Energy harvesting Recent projects focus on: AI-driven emergency vehicle tracking Temporal transcriptomics for sepsis research Chaos-based encryption for IoT He supervises students in areas like: Network optimization Medical data analytics Security protocols Current funded work includes: £3.2M EPSRC grant for multi-modal hearing aids Kuwait College funded energy harvesting solutions Royal Society security research in vehicular networks

Stefan Harmelingمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Reinforcement Learning
• +۳ مورد دیگر

Prof. Dr. Stefan Harmeling is a Distinguished Professor at TU Dortmund University 's Faculty of Computer Science and leads the Harmeling Lab . Previously, he served as Professor for Machine Learning at Universität Düsseldorf (2014-2022) and held postdoctoral positions at the University of Edinburgh (2005-2007) and Max Planck Institutes in Tübingen (2007-2014). His research spans machine learning , deep learning , reinforcement learning , and causality , with applications in medical imaging , seismology , and political discourse analysis . Education : Dipl. Math. in Mathematical Logic, University of Münster (1998) M.Sc. in Computer Science, Stanford University (2000) Dr. rer. nat. in Machine Learning, University of Potsdam (2005) His scientific contributions include 15 recent publications (2021-2025) covering topics from cardiac MRI analysis to LLM applications in political deliberation . These works demonstrate expertise in generative models , self-supervised learning , and adversarial robustness . Notable awards : 2022: Helsinki Tomography Challenge winner 2012: Günter Petzow Prize 2011: DAGM Prize 2009: COSMOSTAT Best Contribution 2009: GREAT08 Challenge Top Score As an advisor, he has mentored 8 PhD students including Tobias Uelwer (2023 PhD), Sebastian Konietzny , and Maike Behrendt . His teaching portfolio includes courses on probabilistic reasoning, machine learning, and deep learning at TU Dortmund. He also serves as area chair for TinyPapers@ICLR 2024 and organizer for multiple NeurIPS/ICML workshops.

Sophia Ananiadouمشاهده پروفایل

استاد

• Natural Language Processing
• Text Mining
• Artificial Intelligence
• +۹ مورد دیگر

Sophia Ananiadou is a Professor in the School of Computer Science at the University of Manchester , where she serves as Director of The National Centre for Text Mining (NaCTeM) , the world’s first publicly funded text mining center. She leads interdisciplinary research at the intersection of Natural Language Processing (NLP) , Artificial Intelligence (AI) , and Machine Learning , with applications spanning biomedicine , public health , environmental science , law , and social sciences . Her work emphasizes computational terminology , information extraction , and neurosymbolic methods , resulting in tools like TerMine and Acromine that are widely adopted in academia and industry. Education PhD in Computational Linguistics, UMIST DEA in Linguistics, Paris VII, Jussieu DEA in Literature, Paris IV, Sorbonne BA in Language and Linguistics, University of Athens Research Interests focus on scalable text mining solutions, including automatic term recognition , event extraction , emotion detection , and resource building . Her recent publications highlight applications in large language models (EmoLLMs) , misinformation analysis , occupational exposure annotation , and argument mining , reflecting a trajectory toward integrating Affective Computing and Generative AI into biomedical and social science domains. Scientific Awards IBM UIMA Innovation Award (3x) Daiwa Award Next Big Thing Prize (2018) Collaborations include leadership roles in the Alan Turing Institute , AIST Artificial Intelligence Research Center , and the OpenMinTed H2020 project . Her tools support organizations like NICE , Cochrane , and Pfizer , and she co-founded the ACL SIGBioMed community to advance biomedical NLP.

• Natural Language Processing
• Artificial Intelligence
• Responsible AI
• +۸ مورد دیگر

Anna Korhonen is a Professor of Natural Language Processing at the University of Cambridge. She co-directs the Language Technology Laboratory (LTL), leads the Centre for Human-Inspired Artificial Intelligence (CHIA), and co-founded the Institute for Technology and Humanity. A Senior Research Fellow at Churchill College, she is also a Fellow of the Association for Computational Linguistics (ACL) and ELLIS, and a former Turing Fellow at the Alan Turing Institute. Her research focuses on advancing NLP and AI technologies with a human-centric, equitable approach, emphasizing multilingualism, interpretability, and applications for social and global good (e.g., health, climate, biomedical sciences). She collaborates across disciplines, integrating insights from cognitive, social, and creative intelligence. Scientific awards include: Royal Society University Research Fellowship JSPS Postdoctoral Fellowship Google Faculty Award ACL and ELLIS Fellowships Senior Research Fellowship at Churchill College EPSRC, MRC, and Innovate UK grants She supervises PhD students via the University of Cambridge and the European ELLIS PhD program, with research projects spanning text mining, conversational AI, and low-resource language technologies.

Danijela Tešendićمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Environmental Monitoring
• +۲ مورد دیگر

Danijela Tešendić serves as an Associate Professor in the Department of Mathematics and Informatics at the Faculty of Sciences, University of Novi Sad. Her office is located in the Information Technologies and Systems office (DMI&DF), second floor, room 50, with contact details including telephone (485)-2873 and email tesendic@dmi.uns.ac.rs. She maintains a professional presence through her website at http://www.is.pmf.uns.ac.rs/daca/. Her research demonstrates dual expertise in environmental monitoring systems and library information technology. Recent work (2022-2025) focuses on machine learning applications for airborne pollen classification using CNN architectures and domain adaptation techniques, contributing to standardization frameworks in environmental science. Earlier contributions (2013-2019) established foundational work in library management systems, particularly through the BISIS software platform, business intelligence integration, and mobile accessibility solutions for visually impaired patrons. Analysis of her publication trajectory reveals a strategic shift toward interdisciplinary environmental informatics while maintaining connections to information systems. Her pollen monitoring research bridges computer vision with ecological applications, emphasizing real-time processing and cross-device compatibility. Concurrently, her library science work pioneered cloud-based service models and inclusive design principles, showcasing adaptable technical frameworks across distinct domains. Scientific Awards No awards or honors were documented in the provided materials. Advising and Grants Student mentorship details are absent from the source text. No research grants or funding sources are explicitly referenced.