جست‌وجوی استاد و پژوهشگر

John Monganمشاهده پروفایل

استاد بالینی

• Artificial Intelligence in Medical Imaging
• Machine Learning
• Radiology Informatics
• +۳ مورد دیگر

John Mongan, MD, PhD, is a Clinical Professor of Radiology and Associate Chair for Translational Informatics at the University of California, San Francisco (UCSF). He specializes in abdominal imaging and ultrasound, with a focus on artificial intelligence (AI) in medical imaging. His work includes developing AI algorithms for pneumothorax detection, leading the development of the CLAIM guideline for reproducible AI research, and chairing the RSNA Artificial Intelligence Committee. He is also a leader in IT governance at UCSF, overseeing research IT budgets and AI oversight committees. Education: MD (2008) and PhD in Bioinformatics (2006) from UC San Diego; BS in Chemistry (1999) from Stanford University. Residency and fellowship in radiology at UCSF. Research Interests: AI in medical imaging, machine learning applications in radiology, data science, and regulatory frameworks for AI deployment. He has pioneered AI challenges and datasets, such as the RSNA Pulmonary Embolism CT Dataset and the RATIC dataset, fostering global collaboration in AI research. Publications: Over 150 peer-reviewed articles, including high-impact work on AI-driven imaging solutions, checklist guidelines for AI research, and consensus statements on trustworthy AI in healthcare. Awards: Recognized for resident research (Margulis Society), academic excellence, and leadership in AI governance. He serves on editorial boards and lectures internationally on AI in radiology. Labs/Teams: Leads UCSF initiatives in translational informatics, AI dataset curation, and governance of clinical AI tools. Collaborates with global societies like RSNA and MICCAI to advance AI standards.

Sarath Chandar Anbil Parthipanمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Sarath Chandar Anbil Parthipan is an Associate Professor at Polytechnique Montréal and leads the Chandar Research Lab (CRL) . He holds the Canada Research Chair Tier 2 in Lifelong Machine Learning and the CIFAR Chair in Artificial Intelligence . As a core faculty member at Mila - the Quebec AI Institute , he also serves as an adjunct professor at the University of Montreal and IIT Madras . PhD in Computer Science (University of Montreal, 2015) MS by Research in Computer Science (IIT Madras, 2015) B.Eng in Computer Science (Anna University, 2009) His research focuses on lifelong/continual learning , deep learning , reinforcement learning , and natural language processing . He created the Conference on Lifelong Learning Agents (CoLLAs) in 2022 and serves as its organizer. Recent works explore molecular design with BindGPT , multi-agent RL coordination, and model interpretability. Scientific recognition includes: Canada Research Chair Tier 2 CIFAR Chair in AI He supervises students in topics spanning AI for science , medical image segmentation , and reset-free reinforcement learning . The CRL Annual Symposium 2023 featured collaborations with institutions like Princeton University and IBM.

William Lionheartمشاهده پروفایل

استاد

• Inverse Problems
• Imaging Techniques
• Medical Imaging
• +۳ مورد دیگر

William Lionheart is a Professor of Applied Mathematics at the University of Manchester, specializing in inverse problems with applications in imaging across industry, security, medicine, and non-destructive testing. He leads research collaborations including the Henry Mosley Centre for X-ray Imaging and the Land Mine Research Centre. His work integrates theoretical, numerical, and practical methods to advance imaging technologies. Education: BSc, PhD in Applied Mathematics. Key research areas include electrical impedance tomography, X-ray imaging, and polarizability tensor-based object characterization. He has pioneered techniques for metallic object detection and medical imaging applications. Research highlights include developing algorithms for synthetic aperture radar, elastic strain reconstruction, and proton therapy verification systems. Awards include the Wolfson Research Merit Award (2015) and a 2013 recognition. He has contributed to 193+ research outputs, led 11 projects (e.g., RASTER, SEMIS Phase III), and organized conferences like the 2023 'Rich and Nonlinear Tomography' event. His work impacts airport security, land mine detection, and medical diagnostics, generating over USD215M in industrial applications.

• Computational Craft
• Digital Media
• Interactive Narrative
• +۷ مورد دیگر

Dr. Anne Sullivan is an Assistant Professor in Digital Media at Georgia Tech and the founder of the StoryCraft Lab. She holds a PhD in Computer Science from UC Santa Cruz, focusing on AI frameworks for playable stories and co-creative experiences. Her research bridges computational craft, feminist game analysis, and human-centered AI, emphasizing intersectional perspectives in design. Education: PhD in Computer Science from UC Santa Cruz. She previously worked as a game developer at AAA studios and as an independent designer, bringing industry experience into her academic work. Research interests include computational craft, queer design methodologies, and accessibility in interactive media. Notable projects include Loominary (a loom-controlled digital game) and the Twine screen reader extension. She explores craft as an analog counterpart to digital interaction, advocating for inclusive and socially conscious technology. Teaching: Courses span game design (LMC-4710, LMC-4725), interactive narrative (LMC-6317), and computational expression (LMC-6310). She emphasizes hands-on, project-based learning aligned with her research. Awards & Recognition: Award-winning quilter and recipient of NSF grants for computational craft education. Her work has been exhibited internationally, including at the Smithsonian American Art Museum. Grants: Collaborative Research on computational thinking through quilting communities (NSF-funded). Current projects focus on queer/critical design frameworks and generative AI tools for marginalized communities. Labs/Teams: StoryCraft Lab (fostering interdisciplinary projects in craft, AI, and narrative). She collaborates with artists, educators, and technologists to create socially impactful interactive experiences.

• Big Data Analytics
• Text Mining
• Machine Learning
• +۶ مورد دیگر

Dr. Wei Zhang is a Senior Lecturer and Associate Head of People and Culture at the University of Adelaide's School of Computer and Mathematical Sciences, with a secondary appointment as Honorary Lecturer at Macquarie University. She holds a PhD in Computer Science from the University of Adelaide (2017) and leads research in big data analytics, text mining, machine learning, and IoT. Her work has resulted in over 100 peer-reviewed publications, including top-tier journals like ACM Computing Surveys and IEEE Communications Surveys. Dr. Zhang currently holds an ARC Early Career Industry Fellowship (IE230100119) and leads an ARC Discovery Project (DP240103070), with total funding exceeding AUD $3M from ARC, Google, and DST over five years. Her research focuses on text summarization, AIoT systems, adversarial attacks on neural networks, and medical information extraction. Professional roles include Program Coordinator, Course Coordinator, and outreach contact at her school. She actively contributes to academic governance as Associate Head of People & Culture and serves on conference committees (ACL, KDD, WWW) and journal editorial boards. Industrial collaborations span six years with roles in project leadership and technical advisory roles across multiple sectors. Dr. Zhang is a member of ACM, IEEE, and ACS, and her work has been recognized by prestigious awards such as top 100 global researchers in Network Security (SciVal). Her lab develops AI-driven solutions for IoT-enabled agriculture (e.g., mushroom cultivation monitoring) and smart construction systems, with applications in energy optimization, healthcare, and environmental monitoring.

David Mguniمشاهده پروفایل

مدرس

• Multi-Agent Systems
• Reinforcement Learning
• Game Theory
• +۳ مورد دیگر

Dr. David Mguni is a Lecturer in Computer Science at Queen Mary University of London, affiliated with the School of Electronic Engineering and Computer Science. His research focuses on multi-agent systems, reinforcement learning, game theory, and decision-making under uncertainty. He holds a PhD in applied mathematics from University College London and prior degrees from the University of Cambridge and the University of London. Before academia, he was a Principal Scientist at Huawei, leading the Multi-Agent Systems team in London. His work bridges theoretical foundations with practical applications, particularly in strategic decision-making and autonomous systems. He teaches the ECS656U/ECS796P Distributed Systems course and supervises students in reinforcement learning, game theory, and optimization. Research interests include non-zero-sum game frameworks, safe reinforcement learning (e.g., SAUTE RL), and reward shaping techniques. His publications span venues like AAMAS, NeurIPS, and IJCAI, addressing challenges in multi-agent coordination, adversarial environments, and algorithmic efficiency. Collaborations involve designing scalable methods for large systems and integrating language models into decision-making processes. David is part of Queen Mary’s Centre for Multimodal AI, contributing to projects on socially-attentive policies, risk-aware systems, and distributed optimization. His recent work emphasizes safety in multi-agent learning (e.g., SAUTE RL), variance reduction in estimator models, and frameworks for managing adversarial scenarios. He actively seeks PhD candidates to explore reinforcement learning and game-theoretic applications.

Gareth Tysonمشاهده پروفایل

استاد

• Computer Networking
• Social Computing
• Internet Measurements
• +۳ مورد دیگر

Professor Gareth Tyson is a Professor of Computer Science at Queen Mary University of London's School of Electronic Engineering and Computer Science. He specializes in Internet Data Science, focusing on social computing, network measurements, and cybersecurity. Tyson has secured over £5 million in research funding and has been recognized with prestigious awards, including the IETF/IRTF Applied Networking Research Prize (2023) and the SIGSOFT Distinguished Paper Award (2023). His work spans interdisciplinary collaborations, addressing challenges in decentralized systems, content moderation, and AI-generated content analysis. His research emphasizes real-world impact, with coverage in media outlets like the BBC, MIT Tech Review, and The Washington Post. Tyson has organized major conferences such as ACM IMC and CoNEXT, and his contributions include foundational studies on adult video streaming, social media ecosystems, and blockchain transactions. He also leads initiatives like the Next Generation Networking Webinar Series and the UK's annual Coseners workshop. Awards include the Brendan Murphy Memorial Young Researcher Prize (2013), Distinguished Reviewer Awards (ACM CoNEXT 2022), and Outstanding Reviewer recognitions at ICWSM. His academic service includes roles on program committees for SIGCOMM, IMC, and WWW, underscoring his leadership in the field.

Nyamsuren Enkhboldمشاهده پروفایل

مدرس

• Artificial Intelligence
• Cognitive Science
• Software Engineering
• +۵ مورد دیگر

Dr. Nyamsuren Enkhbold is a Lecturer in Computer Science (Software Engineering) at the School of Computer Science and Information Technology, University College Cork. He holds a PhD from the University of Groningen (Cognitive Modeling), an MSc from KAIST (Computer Science), and a BSc from Huree University (Computer Science). His research focuses on intelligent software development at the intersection of AI, Cognitive Science, and GIS, with notable contributions to geo-analytical question-answering systems and EU-funded projects like RAGE (serious games) and QuAnGIS (GIS workflow automation). Current interests include GenAI applications via fine-tuning and prompt engineering. He teaches CS3062 - Computing in Society CS6403 - Case Studies in Computing Entrepreneurship and previously contributed to courses at Utrecht University and KAIST. His work has been supported by a School of Computer Science Starter Fund (€10k). Research highlights include developing reusable AI components for serious games and advancing GIS systems that automatically generate workflows from user queries. His publications span cognitive modeling, spatial semantics, and NLP-driven geo-analytical tools.

Prakhar Gargمشاهده پروفایل

عضو هیئت علمی

• Nuclear Physics
• Particle Detectors
• Experimental Heavy-Ion Physics
• +۴ مورد دیگر

Prakhar Garg is a Research Scientist in the Department of Physics at Yale University, focusing on experimental nuclear physics and particle detector technology. His work involves R&D for the sPHENIX experiment at BNL and the upcoming Electron-Ion Collider (EIC). Previously, he contributed to the PHENIX experiment and the Time Projection Chamber (TPC) development at Stony Brook University. Garg holds a Ph.D. from Banaras Hindu University (2015). His research emphasizes gaseous detectors, photon detectors, and detector systems for high-energy physics experiments. Key projects include the MOLLER experiment's GEM-based tracker and EIC-related detector advancements. He has extensive experience with heavy-ion collisions, jet quenching, and medium response analysis in AuAu collisions. Publications highlight studies on azimuthal anisotropy, direct photon production, and detector optimization. His work bridges experimental design with fundamental physics questions about quark-gluon plasma and quantum chromodynamics.

• Applied Cognitive Psychology
• Defence Training Analysis
• Human Factors for Defence
• +۱۴ مورد دیگر

Dr Victoria Smy is a Lecturer in Applied Cognitive Psychology at Cranfield University, affiliated with the Centre for Electronic Warfare, Information and Cyber (EWIC) at the Defence Academy of the United Kingdom. She is also an Honorary Tutor at Cardiff University and a Chartered Member of the British Psychological Society. Her work bridges cognitive psychology with defence and security applications, particularly in training, decision-making, and human factors. Research Interests: Dr Smy's research focuses on training analysis , teamwork development , decision-making in complex environments , and cognitive vulnerabilities in digital contexts . She explores how motivation, trust, and attitudes affect learning and performance. Her recent work investigates manipulative website content and social cognitive hacking, contributing to intelligence and cybersecurity understanding. Publications & Trends: Her recent publications (2024–2016) show a strong trajectory in applied cognitive psychology, particularly in defence training, skill retention, and online influence. The articles span journals in ergonomics, psychology, and human-computer interaction, reflecting interdisciplinary impact. A clear trend is the application of cognitive theory to real-world defence and educational challenges, including disinformation analysis and team performance. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: Dr Smy has served as a Principal Investigator on projects funded by DSTL and other defence bodies, including 'Measuring sympathetic views towards extremist terrorist activities' (UIC2, 2022) and 'Horizon scanning — enhancing individual and collective training' (R-Cloud, 2023). She collaborates extensively with researchers like Marie Cahillane and Piers MacLean, indicating a strong advising and mentorship role, particularly in cognitive task analysis and training design. Labs and Teams: She is a key member of the Applied Psychology Group at Cranfield, co-founded with Dr Marie Cahillane and Dr Piers MacLean. This group conducts defence-funded research on skill fade, cognitive hacking, and training innovation.

• Medical Imaging
• Positron Emission Tomography (PET)
• Time-of-Flight PET
• +۱۲ مورد دیگر

Katrin Herweg is a Research Scientist at the Institute of Imaging and Computer Vision (Chair of Imaging and Image Processing), RWTH Aachen University, Germany. She has been actively contributing to the advancement of high-resolution, time-of-flight positron emission tomography (PET) detector technologies since 2019. Her work is deeply rooted in the Department of Physics of Molecular Imaging Systems at the Institute for Experimental Molecular Imaging, and she continues her research in detector development with a strong focus on scintillator physics and photodetection systems. Master of Science in Physics, RWTH Aachen University (2017–2020), Focus: Experimental Particle Physics Bachelor of Science in Physics, RWTH Aachen University (2014–2017) Katrin's research centers on the development of PET detectors with ultra-high timing resolution. She investigates fast and ultra-fast light emission mechanisms in scintillator materials such as CsZnCl₃, LYSO:Ce,Ca, and BaF₂ through experimental measurements and simulations. Her work aims to push the boundaries of time-of-flight PET and CT by enabling sub-100 ps timing precision, which enhances image quality and quantification in nuclear medicine. She also explores novel photodetector technologies like μSiPMs and digital-analog SiPMs (DIGILOG) to overcome limitations of traditional materials like BGO. The recent publications highlight a consistent trend in advancing PET detector performance through innovations in scintillator characterization, ASIC-based readouts (e.g., TOFPET2c), high-frequency SiPM electronics, and modular, scalable detector designs with depth-of-interaction capability. Her work bridges fundamental physics with practical medical imaging applications, particularly in scatter rejection, organ-dedicated imaging, and axial field-of-view expansion. Scientific Awards: 3rd Place, IEEE Nuclear Science Symposium Student Paper Award (November 2023) Katrin has supervised multiple bachelor's theses on topics including deep learning-based position estimation in PET detectors, optical coupling materials, and scintillator coatings. She has served as an exercise and laboratory course instructor in nuclear medicine physics for both M.Sc. Biomedical Engineering and B.Sc. Electrical Engineering students. While no direct grant information is listed, her extensive publication record in high-impact journals and conferences suggests active participation in funded research projects. She collaborates closely with Prof. Volkmar Schulz and Dr. Stefan Gundacker, key figures in molecular imaging at RWTH Aachen. Katrin is a member of the research team at the Chair of Imaging and Image Processing (LFB), which focuses on advanced imaging systems, detector development, and image reconstruction algorithms. The team is part of a larger ecosystem at RWTH Aachen dedicated to experimental molecular imaging and biomedical engineering, contributing to platforms like Hyperion III for PET/MRI research.

Jin Geمشاهده پروفایل

استادیار

• Liver Disease
• Liver Transplantation
• Cirrhosis
• +۶ مورد دیگر

Jin Ge, MD, MBA is an Assistant Professor in the Department of Medicine at the University of California, San Francisco (UCSF) School of Medicine. He serves as a gastroenterologist and transplant hepatologist in the Liver Transplant Program, with affiliations at the UCSF Bakar Computational Health Sciences Institute and the UCSF-UC Berkeley Joint Program in Computational Precision Health. After earning a bachelor's degree in engineering at Princeton University (2008), he obtained combined MD and MBA degrees from the University of Pennsylvania (2015) before completing residency in internal medicine and fellowships in gastroenterology and transplant hepatology at UCSF (2018-2022). His work focuses on applying clinical informatics, artificial intelligence, and data science to enhance outcomes for patients with advanced liver disease through innovative technologies and decision support systems. Liver disease management Transplant hepatology Clinical decision support systems Large language models Health equity in organ allocation Electronic health record analytics His research output spans 15+ peer-reviewed publications covering topics from AI-guided liver transplantation allocation to NLP-driven cirrhosis prognosis , with multiple first-author studies in Hepatology and Liver Transplantation . Recent work includes developing a liver disease-specific chat interface using retrieval-augmented generation and implementing clinical decision support systems through human-centered design. APASL 2023 Best Oral Presentation AASLD 2021 Anna S. Lok Award UCSF 2019 Clinical Fellow Award University of Pennsylvania 2015 Palmer Scholar 20+ professional recognitions across academia As a practicing clinical researcher, he directs the Division of Gastroenterology's Clinical AI initiatives and maintains active involvement with the National COVID Cohort Collaborative (N3C) Consortium. His clinical practice addresses complex hepatology cases requiring multidisciplinary management strategies.

• Privacy-preserving machine learning
• Adversarial robustness
• Differential privacy
• +۵ مورد دیگر

Saeed Mahloujifar is a researcher in the Department of Computer Science at Princeton University's School of Engineering and Applied Science. He has established himself as a prominent researcher in machine learning security, privacy, and robustness, with extensive collaborations with leading researchers including Prateek Mittal, Mohammad Mahmoody, and Somesh Jha. His research primarily focuses on security and privacy challenges in machine learning systems. Mahloujifar has made significant contributions to understanding and mitigating membership inference attacks, developing defenses against poisoning and backdoor attacks, advancing differential privacy techniques, and exploring the fundamental limits of robust machine learning. His work bridges theoretical foundations with practical applications, often developing novel algorithms and frameworks that have been widely adopted in the security and privacy communities. The analysis of his recent publications reveals a strong research trajectory centered on privacy-preserving machine learning, with particular emphasis on large language models, differential privacy guarantees, and security vulnerabilities. His work spans theoretical foundations of privacy through practical security mechanisms like watermarking and robustness benchmarking. A notable trend is his increasing focus on large language models and their security implications, alongside continued contributions to foundational privacy theory. Mahloujifar has co-authored over 90 publications since 2017, with a significant acceleration in output since 2020. His work appears consistently in top-tier venues including NeurIPS, ICML, IEEE S&P, and USENIX Security, demonstrating both breadth and depth in his research contributions.

Elizabeth Polgreenمشاهده پروفایل

استادیار

• Programming Languages
• Program Synthesis
• Formal Verification
• +۷ مورد دیگر

Elizabeth Polgreen is a Lecturer (~Assistant Professor) in the School of Informatics at the University of Edinburgh, where she conducts research in programming languages and formal methods, particularly program synthesis and verification. She is affiliated with the Laboratory for Foundations of Computer Science and contributes to the Programming Languages and Software Engineering research area. Her research focuses on formal program synthesis, leveraging techniques such as symbolic reasoning, genetic algorithms, and large language models to improve the scalability and automation of software verification. She explores applications in code modernization, tensor program lifting, and explainable AI. Her work bridges programming languages, AI, and formal methods to build trustworthy systems. Her recent publications (2020–2025) span top venues including PLDI, CGO, AAAI, CAV, OOPSLA, and NeurIPS, showing a strong trend in neuro-symbolic synthesis, grammar inference, and verification of AI and low-resource code. She has secured competitive funding, including a Royal Academy of Engineering fellowship and an Amazon Research Award. Scientific awards include: Royal Academy of Engineering Research Fellowship Amazon Research Award Best Paper Award at GPCE Distinguished Paper Award from CGO She advises multiple PhD students, including Yixuan Li, Alexander Brauckmann, and José Wesley de Souza Magalhães, often in collaboration with Professor Mike O'Boyle. Her research is supported by grants from the Royal Academy of Engineering and Amazon. She has delivered keynotes, tutorials, and a TEDx talk, contributing actively to outreach and education in formal methods. She leads a research group within the Laboratory for Foundations of Computer Science, focusing on trustworthy systems through synthesis and verification. Her team includes PhD students and collaborators working on cutting-edge topics in program analysis, AI for code, and compiler design.

David Highamمشاهده پروفایل

مدرس

• Management
• Entrepreneurship
• Retail Business Operations
• +۵ مورد دیگر

David Higham serves as Lecturer in Management and Entrepreneurship at Elon University's Martha and Spencer Love School of Business since 2014, concurrently holding the position of Interim Director for the Doherty Center for Creativity, Innovation and Entrepreneurship. His office is located in Koury Business Center, room 202. His academic foundation includes a BS in Accounting and MBA from Elon University, complemented by Six Sigma Black Belt Training from ACC/NC State. BS in Accounting, Elon University MBA, Elon University Six Sigma Black Belt Training, ACC/NC State Higham's research integrates practical business operations with academic instruction, focusing on management strategy, entrepreneurial finance, and retail innovation. His expertise in Blue Ocean Strategy informs teaching of New Product Development & Branding, while extensive experience as a business owner shapes his approach to Principles of Management and Small Business Management courses. Current professional activity emphasizes personalized online sales systems. He secured the Open Education North Carolina grant (Spring 2020) and Love School of Business AI Grant (Fall 2023) for implementing ChatGPT in education with prompt engineering focus. As Sigma Iota Epsilon Advisor and Elon Year of Service Committee Member, he actively mentors students while serving on the Christmas Cheer of Alamance Board as Vice President. Higham's teaching portfolio spans Principles of Marketing, Gateway to Business, and Entrepreneurial Finance at Elon, plus Retailing, Customer Service, and Industrial Leadership courses previously taught at Alamance Community College. His professional ventures include operating Hazel Grove Customs, Holly Hill Photography, and former Regis salon franchises.