جست‌وجوی استاد و پژوهشگر

Conrad Sandersonمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• AI Ethics
• +۷ مورد دیگر

Dr. Conrad Sanderson is a Researcher and Team Leader at the Data61 division of CSIRO , focusing on artificial intelligence, machine learning, AI ethics, and high-performance numerical computing. He is also an Adjunct Professor at Griffith University . With over 150 publications and 11,000+ citations, he is renowned for developing influential open-source libraries like Armadillo and RcppArmadillo . Research Interests Artificial Intelligence & Deep Learning Responsible AI, Safe AI, and Ethical Trade-offs Numerical Linear Algebra and High-Performance Computing Recent Publications highlight advancements in: Dynamic graph anomaly detection via extreme value theory Fire propagation uncertainty estimation using neural emulators Resolving ethical tensions in AI implementation GPU-accelerated machine learning Scientific Awards Most cited paper award for thesis-based article Armadillo framework: 30+ million downloads Collaborations include researchers from Facebook, NASA, Boeing, and institutions like MIT and Stanford. His work bridges academia and industry through open-source contributions and interdisciplinary applications.

Natalie Pardeمشاهده پروفایل

دانشیار

• Natural Language Processing
• Interactive Systems
• Multimodality
• +۲ مورد دیگر

Natalie Parde is an Associate Professor and Co-Director of Undergraduate Studies in the Department of Computer Science at the University of Illinois Chicago (UIC). She co-directs the UIC Natural Language Processing Laboratory and holds affiliations with the AI.Health4All Center for Health Equity using Machine Learning and Artificial Intelligence as well as the UIC Honors College. Her research focuses on natural language processing with applications in healthcare, multimodal communication, and creative language analysis. Ph.D., Computer Science and Engineering, University of North Texas M.S., Computer Science, University of North Texas B.S., Computer Science, University of North Texas Parde's research spans three primary strands: NLP interfaces for educational technology, health-oriented summarization, and multimodal communication systems. Recent publications highlight advancements in dementia detection through spoken language analysis, empathy prediction in conversational systems, and multimodal emotion classification. Her work frequently addresses healthcare applications of NLP, including mental health assessment and medical self-disclosure detection. Scientific awards include the Dr. Hermann Zemlicka Award for Most Visionary Paper at Gmunden Retreat on NeuroIS 2024. She has advised numerous doctoral students, including Gyeongeun Lee working on empathy detection via figurative language, Shahla Farzana researching dementia detection methods, and Mohammad Arvan investigating reproducibility in NLP evaluations. The UIC NLP Lab under her direction focuses on developing NLP systems that positively impact society through educational technology interfaces and healthcare applications.

Antonela Tommaselمشاهده پروفایل

استاد مدعو

• Social Computing
• Recommender Systems
• Machine Learning
• +۵ مورد دیگر

Dr. Antonela Tommasel is a Researcher at CONICET and an Adjunct Professor at National University of the Center of the Province of Buenos Aires (UNICEN) , working at the intersection of social computing, machine learning, and misinformation mitigation. Her work combines computational techniques to address challenges in social media analysis, bias detection, and recommender system design. PhD in Computer Sciences (2017), UNICEN Bachelor in Software Engineering (2012), UNICEN Her research focuses on recommender systems with applications to social media trustworthiness , including projects like Faking It! (fake news dataset creation) and OHARS (harm-aware recommendation frameworks). Key themes include misinformation spread analysis , gender bias detection , and machine learning applications for social good. She has led 11+ years of teaching in courses like Advanced Java Programming, Recommender Systems, and Natural Language Processing for AI specializations. Her technical certifications include NVIDIA Deep Learning Institute programs on GPU-accelerated data science and Coursera specializations in machine learning and visualization. Currently based at ISISTAN Research Institute in Tandil, Argentina, she advocates for responsible AI through tools like graphoW (graph-of-words library) and Sen4Smells (technical debt prioritization). Her work emphasizes bridging social media analysis with practical implementation frameworks.

Dare Baldwinمشاهده پروفایل

استاد

• Cognitive Development
• Language Acquisition
• Event Processing
• +۳ مورد دیگر

Dare Baldwin is a Full Professor in the Department of Psychology at the University of Oregon , where she directs the Acquiring Minds Lab . Her research focuses on the intersection of language acquisition, cognitive development, event processing , and social-cognitive development . 541-346-4964 (Office) 467 Straub Hall and 210 Chapman Hall (Office Locations) Office Hours: Thursdays 12-1pm on Zoom; Fridays 9-10am in Straub Hall 467 Dr. Baldwin’s work explores how infants and young children acquire knowledge through social interactions , action processing , and language learning . Her lab investigates two major additional domains: the developmental consequences of malnutrition and human behavioral responses to natural hazards such as earthquakes. Current projects examine maternal thiamine supplementation effects on infant cognition and methodologies for online interpersonal understanding studies . Recent publications span: simulating human behavior under earthquake early warnings , infant language processing , micronutrient impacts on neurocognitive development , and event cognition mechanisms . Her lab employs interdisciplinary approaches combining eye-tracking , machine learning , and behavioral experiments . Current Lab Members: Doctoral Students: Netanel Weinstein, Scott Wallner, Elizabeth Loi, Karlena Ochoa Steigerwald, John Rochelle, Anaahat Bala Masters Students: Yasuhiro Tanaka, Leah Child, Jason Garrison, Julian Michels, Emily Neuhaus

• Arabic Natural Language Processing
• Machine Translation
• Dialect Identification
• +۷ مورد دیگر

Ahmed Abdelali is a prominent researcher at Hamad Bin Khalifa University's Qatar Computing Research Institute (QCRI), where he works in the Arabic Language Technologies department. With 97 publications spanning from 2004 to 2024, he has established himself as a leading figure in Arabic natural language processing research. His work has been presented at major conferences including ACL, EMNLP, EACL, and specialized Arabic NLP venues. Dr. Abdelali's research focuses on several key areas within Arabic computational linguistics, with particular emphasis on Arabic language technologies. His work spans Arabic dialect identification, diacritization, machine translation, offensive language detection, and part-of-speech tagging. In recent years, he has been at the forefront of adapting large language models for Arabic language processing, contributing significantly to benchmarking frameworks like LAraBench and LLMeBench that evaluate Arabic language models' performance. His publication record shows consistent high-impact contributions, with notable collaborations with researchers including Hamdy Mubarak (45 co-authored papers), Kareem Darwish (38 co-authored papers), and Nadir Durrani (26 co-authored papers). Recent work has focused on large language models for Arabic, cross-lingual spaces, and benchmarking frameworks to advance Arabic AI capabilities. His research bridges theoretical advances with practical applications, particularly in processing the linguistic complexities of Arabic and its dialects. Through his leadership in developing resources like the Farasa segmenter and contributions to major Arabic NLP conferences, Dr. Abdelali has played a pivotal role in establishing the infrastructure and community for Arabic language technology research.

• Artificial Intelligence
• Machine Learning
• Inverse Reinforcement Learning
• +۵ مورد دیگر

Aaron Snoswell is a Research Fellow at Queensland University of Technology (QUT), affiliated with the Faculty of Creative Industries, Education & Social Justice and the School of Communication. His work bridges technical AI development with social implications, focusing on ethical implementation of AI systems across multiple domains including healthcare, legal systems, and public policy. Snoswell's research interests span artificial intelligence, machine learning (particularly inverse reinforcement learning), AI ethics, automated decision-making systems, and the societal implications of AI technologies. His work demonstrates a consistent focus on making AI systems more transparent, accountable, and beneficial for society, with particular attention to healthcare applications, legal systems, and public understanding of AI technologies. Analysis of his most recent publications reveals a clear trajectory toward responsible AI deployment, with increasing focus on policy frameworks, public education about AI capabilities and limitations, and practical applications that address real-world problems in healthcare and justice systems. His work often combines technical AI development with critical social perspectives, reflecting an interdisciplinary approach that connects computer science with social sciences. Snoswell has been actively involved in policy submissions to governmental bodies including the Australian Senate Select Committee on Adopting Artificial Intelligence and responses to the G7 Guiding Principles for organizations developing advanced AI systems. His work with the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S) demonstrates his commitment to shaping responsible AI governance frameworks. He has established productive collaborations across multiple institutions and disciplines, working with researchers in communication studies, computer science, healthcare, and legal fields. His recent work on the GenAI Arcade project represents an innovative approach to public engagement with AI technologies through interactive learning environments.

Ana Puig Puigمشاهده پروفایل

استاد

• Gamification in Education
• Serious Games
• 3D Point Clouds
• +۹ مورد دیگر

Dr. Anna Puig Puig is a Professor at the University of Barcelona, affiliated with the Faculty of Mathematics and Computer Science within the Department of Mathematics and Computer Science. Her research focuses on gamification in education, 3D point cloud processing, data visualization, and biomedical applications of computer science. Key research areas include: Gamification and serious games for education 3D point cloud segmentation and analysis Machine learning applications in geospatial and biomedical domains Interactive visualization systems Virtual reality for archaeological and educational purposes Notable projects include: INDOMAIN - Pedagogical Module in Intelligent Tutoring Systems HORIZON 2020 European Cancer Image Platform GRAPES - Machine Learning for Shape Processing CLiC Research Group in Language and Computing Digital Reconstruction of Neolithic Social Life

Hanna Ehlertمشاهده پروفایل

پژوهشگر

• Artificial Intelligence in Speech Therapy
• Dynamic Assessment
• Language Development Disorders
• +۴ مورد دیگر

Hanna Ehlert is a researcher at Leibniz University Hannover, affiliated with both the Institute for Special Education (Faculty of Philosophy) and the Institute for Information Processing (TNT/Phonomatics spin-off). Her work bridges artificial intelligence with speech therapy, focusing on automated diagnostics and dynamic assessment for child language development. PhD in Special Education (2020, Leibniz University Hannover) M.Sc. & B.Sc. in Speech and Language Therapy/Logopedics (HAWK Hildesheim) State-certified speech therapist (Hannover Medical School) Her research integrates: Artificial Intelligence in speech therapy Dynamic Assessment for multilingual children Language development disorders Voice disorder prevention Technology for inclusive education Key research projects include: TALC (Tool for Analyzing Language and Communication) Phonomatics spin-off AI-LIT (AI-supported Literacy Development)

Auxiliadora Sarmiento Vegaمشاهده پروفایل

استاد

• Audio Source Separation
• Biomedical Signal Processing
• Machine Learning
• +۵ مورد دیگر

Auxiliadora Sarmiento Vega is a full professor at the University of Seville 's School of Engineering within the Department of Signal Theory and Communications . With over two decades of research experience, her work bridges audio signal processing and biomedical applications, focusing on blind source separation, entropy-based methods, and machine learning for healthcare diagnostics. Research Pillars : Audio source separation, biomedical signal/image analysis, and virtual reality integration Key Projects : ACACIA (Signal Analysis), NEUBIAS (Bioimage Analysts Network), and multiple NIH-funded biomedical imaging initiatives Academic Contributions span 15+ years, with groundbreaking work in: Alpha-Beta divergence clustering algorithms EEG processing for motor imagery BCI systems Automated breast cancer grading from histological images Glaucoma and diabetic retinopathy diagnostics via retinal image analysis Virtual reality platforms for emotion analysis research She actively collaborates with institutions like the IEEE Women in Engineering (Spanish section secretary) and NEUBIAS network , while mentoring through outreach programs like g4g Day that empower young women in STEM.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۶ مورد دیگر

Tengda Han is a Research Scientist at Google DeepMind , specializing in neural networks for video understanding. He earned his PhD from the University of Oxford under Andrew Zisserman and a BEng in Mechanical & Material Engineering from the Australian National University . Prior to his PhD, he studied business administration and law at Renmin University of China for one year. PhD in Computer Science, University of Oxford (2022) BEng in Mechanical & Material Engineering, Australian National University (2016) One year of business administration and law at Renmin University of China His research focuses on video representation learning , self-supervised methods , multimodal learning , and efficient prompting techniques . He has pioneered training-free frameworks for audio description, zero-shot object counting, and hyper-realistic movie generation. Recent publications demonstrate trends in temporal alignment , discriminative prompting , 5D video modeling , and open-world counting . His work often bridges computer vision with natural language processing and speech recognition . Scientific Awards : Best Paper Award at ACCV2024 Best Poster Award at BMVC2023 BMVA Sullivan Doctoral Thesis Prize Runner-up He has co-organized workshops at ICCV25 , NeurIPS23 , and BMVA Symposium on Vision & Language . Collaborators include Andrew Zisserman, Dima Damen, and Flamingo project members at DeepMind.

• Text mining
• Intelligent information retrieval
• Natural language processing
• +۵ مورد دیگر

Efstathios Stamatatos is a Professor in the Department of Information and Communication Systems Engineering at the University of the Aegean, Greece. He has been a faculty member at the university since 2004, following previous research positions at the Wire Communications Lab of the University of Patras, the Polytechnic University of Madrid, the Austrian Research Institute for Artificial Intelligence, and the TEI of Ionian Islands. His primary research interests include Text mining, Intelligent information retrieval, Natural language processing, Machine learning, and Computer music, with a particular focus on authorship attribution, plagiarism detection, and web genre identification. His work bridges computational linguistics, digital forensics, and digital humanities, applying machine learning techniques to analyze textual patterns and stylistic features. Dr. Stamatatos has authored numerous publications on authorship attribution, plagiarism detection, and text classification, with a strong emphasis on developing robust methodologies that work across different domains and languages. His research has evolved from traditional n-gram approaches to more sophisticated techniques involving machine learning ensembles, topic modeling, and recently, addressing challenges posed by generative AI systems. He has served as Associate Editor for the International Journal of Digital Crime and Forensics, and as Editorial Board Member for Language Resources and Evaluation and Information Processing and Management. He has also been Guest Editor for a Special Issue on Plagiarism and Authorship Analysis in Language Resources and Evaluation. Dr. Stamatatos has been instrumental in organizing the PAN (Uncovering Plagiarism, Authorship, and Social Software Misuse) workshop series, serving as co-organizer and contributing numerous overview papers on authorship verification, plagiarism detection, and digital text forensics. He has also served on program committees for major conferences including ACL, SIGIR, ECIR, and AAAI.

Majid Zamaniمشاهده پروفایل

مدرس

• Biomedical Engineering
• Artificial Intelligence
• Neuroscience
• +۳ مورد دیگر

Dr Majid Zamani is a Lecturer in the School of Electronics & Computer Science at the University of Southampton. His research focuses on implantable and wearable biomedical devices, applied AI in biomedical engineering, and hardware-efficient processing frameworks. Member of: Digital Health and Biomedical Engineering Institute for Life Sciences Member of: Centre for Internet of Things and Pervasive Systems Member of: Centre for Health Technologies Member of: UKRI AI Centre for Doctoral Training in AI for Sustainability (SustAI) Current research addresses key challenges in scalability, signal processing, sensing, energy efficiency, and miniaturization for next-generation implantable brain-machine interfaces (iBMI). He explores hardware-efficient computational platforms for biomedical applications, including AI-driven algorithms for neural signal/image processing, augmented navigation in constrained anatomical spaces, and low-power real-time processors in 180/90/45 nm CMOS technologies. Recent publications focus on deep learning for spike sorting, binarized neural networks, noise-aware speech enhancement, and AI integration in surgical navigation. His work bridges biomedical engineering with AI and hardware optimization. Teaching: Digital system design (ELEC6236) 42+ publications in journals like IEEE Transactions on Medical Imaging, Journal of Neural Engineering, and IEEE Access

Nicole Li-Jessenمشاهده پروفایل

دانشیار

• upper airway health and diseases
• computational medicine
• tissue engineering
• +۵ مورد دیگر

Nicole Li-Jessen, PhD is an Associate Professor in the Department of Surgery at McGill University's Faculty of Medicine and Health Sciences and holds the Canada Research Chair (Tier 2) in Personalized Medicine of Upper Airway Health and Diseases. She serves as Graduate Program Director for the School of Communication Sciences and Disorders and is an Associate Investigator at The Research Institute of the McGill University Health Centre (RI-MUHC). Dr. Li-Jessen maintains additional affiliations with the Departments of Otolaryngology and Biomedical Engineering, and is a Research Member of Quantitative Life Sciences and McGill Regenerative Medicine Network. Dr. Li-Jessen's research laboratory integrates in vitro, in vivo, and in silico (computational) approaches to study vocal fold biology and wound healing, with the goal of generating computational platforms that guide surgeons and speech pathologists in voice repair methods. Her key research areas include: Non-invasive assessment of airway reflux Designing 3D printable biomaterial for laryngeal tissue and muscle reconstruction Creating wearable e-health devices for upper airway monitoring Agent-based modeling of vocal trauma and repair response Development of tumor-on-a-chip platforms for studying laryngeal cancer chemoresistance Her work is funded by a Canada Research Chair, the CIHR, NSERC, SSHRC, FRQS, and NIH in the United States. Dr. Li-Jessen has published extensively in high-impact journals across biomedical engineering, otolaryngology, and regenerative medicine fields, with recent publications focusing on vocal fold biomaterials, computational modeling of vocal pathology, and audio-based digital biomarkers for respiratory diseases. Dr. Li-Jessen has received several prestigious awards including the Canada Research Chair (2021), Principal's Prize for Excellence in Teaching (2018), and the Rosemary Wedderburn Brown Prize (2018). She serves as Section Editor of PLOS Digital Health and is actively involved in science policy as a Delegate for Science Meets Parliament. As Graduate Program Director, Dr. Li-Jessen oversees graduate thesis programs in the School of Communication Sciences and Disorders and has mentored numerous PhD, Master's, and undergraduate students. She leads the Voice and Upper Airway Research Lab (VUA Lab), which advocates for EDI principles in STEM and currently has open positions for PhD and post-doctoral researchers in computer modeling and digital health projects.

Pei-Hsun Hsiehمشاهده پروفایل

پژوهشگر

• Political Economics
• Political Psychology
• Climate Change Policy
• +۴ مورد دیگر

Pei-Hsun Hsieh is a Postdoctoral Researcher at the University of Pennsylvania, focusing on political and social behavior in democratic societies. They hold a Ph.D. in Political Science from Stony Brook University (2023) and specialize in examining public perceptions of government influence, electoral behavior, and policy support for inequality and climate change mitigation. Doctoral Degree: Political Science, Stony Brook University, 2023 Dr. Hsieh combines theory-driven and data-driven methodologies, including natural language processing, statistical modeling, economic games, and agent-based simulations. Their work explores the intersection of political economy, social norms, and environmental policy through large-scale social media analysis and behavioral experiments. Key research trends include analyzing how crises like pandemics affect climate change discourse, redistributive preferences under merit-based systems, and the role of emotions in policy debates. Publications span journals like PNAS, Journal of Environmental Psychology, and Humanities and Social Sciences Communications. Teaching includes Computational Text Analysis for Social Sciences , covering machine learning and NLP techniques. Current projects investigate plant-based diets as climate solutions, sanction effectiveness in international politics, and the dynamics of norm strength in cooperative settings. Affiliated with the Center for Social Norms and Behavioral Dynamics and the Philosophy, Politics, and Economics program at UPenn, they apply computational methods to understand political behavior, policy preferences, and institutional trust.

Yi Panمشاهده پروفایل

استاد

• Parallel and Cloud Computing
• Wireless Networks
• Bioinformatics
• +۳ مورد دیگر

Dr. Yi Pan is a Distinguished University Professor and Chair of the Department of Computer Science at Georgia State University. He holds a B.Eng. and M.Eng. from Tsinghua University (China) and a Ph.D. from the University of Pittsburgh (USA). His research focuses on parallel computing, wireless networks, bioinformatics, and machine learning, with over 330 publications and 39 authored/edited books. Dr. Pan has organized international conferences and delivered over 40 keynote speeches globally. Education: B.Eng., Computer Engineering, Tsinghua University, 1982 M.Eng., Computer Engineering, Tsinghua University, 1984 Ph.D., Computer Science, University of Pittsburgh, 1991 Research Interests: Dr. Pan’s work spans parallel and cloud computing, wireless networks, and bioinformatics. His contributions include scalable algorithms for functional module discovery in protein networks, self-defense mechanisms for cyber threats, and efficient routing protocols for sensor networks. Recent efforts integrate AI into healthcare, such as lesion localization in OCT imaging and autism spectrum disorder diagnosis via EEG analysis. Awards & Recognition: IEEE Distinguished Speaker (2000–2002) Yamacraw Distinguished Speaker (2002) Listed in Who’s Who in America and Who’s Who in Computational Science Awards from NSF, AFOSR, IBM, and Mellon Foundation Advising & Leadership: As department chair, Dr. Pan oversees interdisciplinary collaborations between Computer Science and Computer Information Systems. He has advised numerous students and holds editorial roles in 15 journals, including several IEEE Transactions. His grants focus on advancing AI-driven healthcare, cybersecurity, and computational biology. Labs & Teams: Leads research initiatives in bioinformatics, medical AI, and parallel computing, collaborating with industry partners like IBM and Shell Oil. Active in organizing conferences such as the IEEE International Conference on Bioinformatics and Biomedicine.