جستجوی استاد راهنمای دانشگاهی

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۳ مورد دیگر

Dr. Ulas Bagci is an Associate Professor at Northwestern University's Feinberg School of Medicine, Department of Radiology. He holds courtesy appointments in Biomedical Engineering (BME), Electrical and Computer Engineering (ECE) at Northwestern, and Computer Science at the University of Central Florida. As the director of the Machine and Hybrid Intelligence Lab, his research focuses on AI and machine learning applications in biomedical and clinical imaging. Education: BS: Bilkent University (2003) MS: Koç University (2005) Fellow: University of Pennsylvania (2009) PhD: University of Nottingham (2010) ISTP Fellow: NIH (2012) Research Interests: Dr. Bagci’s work spans artificial intelligence, machine learning, and their integration into medical imaging workflows. His lab develops algorithms for tumor segmentation, radiomics analysis, and ethical AI frameworks in healthcare. Notable projects include large-scale MRI segmentation of cirrhotic livers and predictive models for clinical outcomes in oncology and cardiology. Publications: His recent work emphasizes AI-driven solutions for challenges in radiology, including lung disease detection, pulmonary embolism mortality prediction, and ethical considerations in foundational AI models. His articles reflect a focus on bridging clinical needs with advanced computational methods. Lab & Affiliations: The Machine and Hybrid Intelligence Lab collaborates with the Robert H. Lurie Comprehensive Cancer Center. Research themes include federated learning, medical image synthesis, and AI ethics in clinical decision-making.

• Machine Learning
• Medical Imaging
• Health Informatics
• +۳ مورد دیگر

Aonghus Lawlor is an Assistant Professor/Lecturer in Computer Science at the School of Computer Science, University College Dublin. His roles include coordinating modules such as Software Engineering, Data Structures, Machine Learning, and Final Year Project Foundations. He holds an Orcid identifier: 0000-0002-6160-4639. His research focuses on machine learning applications in medical imaging (e.g., MRI, CT), sports science, and healthcare systems. Notable areas include AI-driven diagnostics, cybersecurity in radiology, and genomics for agricultural optimization. Recent work explores ChatGPT4-vision in MS progression, knee osteoarthritis grading via anomaly detection, and reinforcement learning in exercise prescriptions. Professional activities include committee roles in ACM Recommender Systems and Intelligent User Interfaces, grant assessments, and peer reviewing. He has published 137+ outputs, emphasizing interdisciplinary AI solutions with clinical and agricultural impact. Teaching responsibilities span foundational CS courses to advanced ML and project modules. No formal awards are listed, but his work demonstrates contributions to AI ethics, health informatics, and agricultural genomics.

• Hardware Accelerators
• Memristor Technology
• Reservoir Computing
• +۴ مورد دیگر

Md Sakib Hasan is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Mississippi. He holds a Ph.D. in Electrical Engineering from the University of Tennessee-Knoxville (2017). His research focuses on hardware acceleration, neuromorphic computing, and memristor-based systems. Research interests span: AI hardware accelerators and energy-efficient computing Biomimetic systems and bio-inspired electronics Hardware security through chaotic systems and PUFs Recent publications demonstrate strong emphasis on: Neuromorphic architectures for computer vision and temporal processing Biomembrane-based computing systems Chaotic cryptography and secure hardware design

Xinya Duمشاهده پروفایل

استادیار

• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Multimodal Models (VLMs)
• +۷ مورد دیگر

Xinya Du is an Assistant Professor in the Department of Computer Science at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. She holds a Ph.D. in Computer Science from Cornell University and completed a postdoctoral fellowship at the University of Illinois at Urbana-Champaign. Her research focuses on advancing trustworthy and impactful AI systems, particularly in Natural Language Processing (NLP), Large Language Models (LLMs), and Vision-Language Models (VLMs). Key research areas include Document understanding and knowledge acquisition Trustworthy reasoning and hallucination detection in LLMs Applications of NLP in scientific research and multimodal systems Alignment of AI systems with human values Dr. Du has received notable awards such as the NSF CAREER Award (2024), Amazon Research Award (2023), and recognition as a Spotlight Rising Star in Data Science. She has authored over 30 papers in top venues like ACL, EMNLP, NeurIPS, and CVPR, contributing to foundational work in multimodal reasoning, LLM evaluation, and automated scientific hypothesis generation. She teaches advanced courses including CS 6301: Special Topics in Computer Science - Deep Learning for NLP and actively mentors students in research projects. Her work has been highlighted in major media and led to impactful open-source contributions, including repositories for event extraction and LLM benchmarking.

• Security and Privacy
• Active Cyber Defense
• Security Analytics
• +۶ مورد دیگر

J. Haadi Jafarian is an Assistant Professor in the Department of Computer Science and Engineering at the University of Colorado Denver, where he leads the Active Cyber and Infrastructure Defense (ACID) Lab. He earned his Ph.D. from the University of North Carolina Charlotte in 2017. Research Interests: Active Cyber Defense (Moving Target Defense, Cyber Deception) Big Data Analytics for Cyber Threat Intelligence Security for Cyber-Physical Systems & Critical Infrastructures Cyber Resilience and Automation Recent Publications highlight innovations in traffic obfuscation, adversarial machine learning, and deception-based threat detection. His work spans network security, cybersecurity analytics, and scalable defense frameworks. Teaching includes: CSCI 4743/5743: Cyber and Infrastructure Defense (Fall 2023) CSCI 4742/5742: Cyber Programming and Analysis (Spring 2023) CSCI 4741: Cybersecurity Principles (Spring 2022) CSCI 4800: Web Application Development (Spring 2021) CSCI 3761: Computer Networks (Spring 2020) Labs & Teams: The ACID Lab focuses on developing proactive cyber defense strategies, including moving target defense, deception techniques, and security analytics for critical infrastructure.

Lijing Wangمشاهده پروفایل

استادیار

• Epidemic Forecasting
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Lijing Wang is an Assistant Professor of Data Science at the New Jersey Institute of Technology (NJIT). She specializes in interdisciplinary research at the intersection of artificial intelligence, epidemiology, and public health. Her work emphasizes data-driven approaches to forecasting infectious disease dynamics, integrating machine learning with theoretical epidemiological models. Education: Ph.D. in Computer Science, University of Virginia (2021) M.S. in Computer Science, Chinese Academy of Sciences (2013) B.S. in Software Engineering, Dalian University of Technology (2010) Research focuses on epidemic forecasting using ensemble modeling, graph neural networks, and causal inference. Key topics include: COVID-19 and influenza prediction using mobility data AI-driven disease surveillance systems Policy impact analysis of pharmaceutical/nonpharmaceutical interventions Cross-national epidemic modeling Publications consistently address forecasting challenges through innovative methodological combinations - e.g., Bayesian ensemble techniques, causal graph approaches, and multi-scale human mobility analysis. Recent work emphasizes real-time prediction accuracy improvements for public health decision-making. No scientific awards explicitly noted in text. Active in collaborative research involving public health agencies and international institutions.

Esam Abdel-Raheemمشاهده پروفایل

استاد

• Digital Signal Processing
• Biomedical Engineering
• Cognitive Radio Networks
• +۳ مورد دیگر

Dr. Esam Abdel-Raheem is a Professor in the Department of Electrical and Computer Engineering at the University of Windsor, Faculty of Engineering. His research focuses on digital signal processing, biomedical engineering, cognitive radio networks, and VLSI design. He holds a Ph.D. from the University of Victoria (1995) and is a Professional Engineer (P.Eng.) in Ontario and a Senior Member of IEEE. Education: B.Sc. Electrical Engineering, Ain Shams University (1984) M.Sc. Electrical Engineering, Ain Shams University (1989) Ph.D. Electrical Engineering, University of Victoria (1995) Research Interests: Dr. Abdel-Raheem’s work spans signal processing for communications, biomedical signal processing, and VLSI implementations. He has pioneered algorithms for cognitive radio networks and adaptive filtering. His recent studies leverage deep learning for medical diagnostics (e.g., lung nodule detection, Parkinson’s disease voice analysis) and cognitive radio spectrum sensing. Publications Trends: Recent work emphasizes biomedical applications (e.g., CT scan analysis, diabetic retinopathy detection) and machine learning integration in communications (e.g., federated learning for traffic crowdsourcing). His articles often bridge theoretical signal processing with practical implementations in hardware (e.g., FPGA-based filters). Awards/Grants: Not explicitly listed in the text, though his senior IEEE membership and prolific publications suggest sustained professional recognition. Lab/Teams: While not detailed, his research themes imply involvement in interdisciplinary teams focusing on biomedical engineering, telecommunications, and VLSI design.

• Fluid Power (Hydraulics)
• Acoustic Sensing
• Dynamic Modelling
• +۴ مورد دیگر

Travis Wiens is an Associate Professor in the Department of Mechanical Engineering at the University of Saskatchewan. His research focuses on fluid power systems, acoustic sensing, dynamic modeling, mining mechatronics, and artificial intelligence applications in engineering. He holds a B.Sc., M.Sc., and Ph.D. in Mechanical Engineering from the same institution, completed in 2002, 2004, and 2008 respectively. His research interests emphasize innovative solutions for hydraulic control systems, pipeline resonance reduction, and mining safety through acoustic technologies. He has developed low-cost electrohydrostatic actuators and explored additive manufacturing in valve design. Notable contributions include vibrational data communication tools for extractive industries and machine learning models for mine roof stability assessment. Dr. Wiens teaches ENGC 01A - Introduction to Fluid Power Components . His work bridges theoretical fluid dynamics with practical applications in energy efficiency, structural health monitoring, and biomimetic systems. Ongoing research trends include integrating AI with hydraulic systems and advancing non-destructive testing methods for infrastructure integrity. His publications highlight interdisciplinary approaches, combining mechanical engineering principles with computational modeling, neural networks, and mechatronics. Collaborative efforts focus on mining safety, oil and gas infrastructure, and sustainable hydraulic technologies.

George K. Dannsمشاهده پروفایل

استاد

• Caribbean Studies
• Race and Ethnic Relations
• Political Leadership
• +۸ مورد دیگر

George K. Danns is a Professor of Sociology in the Department of Sociology and Human Services at the University of North Georgia, Gainesville Campus. Holding a PhD from SUNY Stony Brook, he has received prestigious awards including the Ford Foundation Fellowship and Complete College Georgia Champion Award. His leadership roles include Chair of UNG Faculty Senate (2015-2016), former Dean of Social Sciences at the University of Guyana, and Senior Fulbright Fellow at the University of Michigan. Ph.D. in Sociology, State University of New York at Stony Brook M.A. in Sociology, State University of New York at Stony Brook B. Soc. Sc. in Social Sciences (Distinction), University of Guyana Dr. Danns specializes in Caribbean socio-political dynamics with emphasis on Guyana, examining race/ethnic relations, political leadership, national security, and community development. His research explores intersections of identity, class, and power in postcolonial contexts, addressing critical issues like environmental disasters, homicide patterns, youth vulnerability, and gender disparities. His fieldwork combines theoretical rigor with practical applications for policy development. His 15 most recent publications (2014-2020) reveal three dominant thematic clusters: Caribbean political economy (35%), diaspora/identity studies (30%), and entrepreneurship/financial literacy (35%). The work demonstrates consistent focus on Guyana while expanding to broader Latin American and Caribbean contexts, with increasing attention to youth entrepreneurship and financial inclusion in developing economies since 2017. Ford Foundation Fellowship for Doctoral Research in Latin America and the Caribbean Complete College Georgia Champion Award (2016) Senior Fulbright Fellowship Dr. Danns has mentored students through diverse sociology courses while securing consultancy grants from major international organizations including UNICEF, UNFPA, USAID, IADB, OAS, and PAHO. His funded research focuses on social policy development, with particular emphasis on youth programs, gender initiatives, and national security frameworks for Caribbean governments. As former Director of the Center for Economic & Social Research & Action (CESRA) at the University of Guyana, he led multidisciplinary teams conducting critical studies on suicide prevention, military roles in national security, and environmental disaster response. His current UNG affiliation involves collaborative research networks addressing regional social challenges through the Sociology and Human Services department.

Marc HONمشاهده پروفایل

استادیار

• Asteroseismology
• Time-domain Astronomy
• Machine Learning
• +۳ مورد دیگر

Marc HON is an Assistant Professor at the National University of Singapore (NUS) under the NUS Presidential Young Professorship, specializing in time-domain astronomy and machine learning applications for NASA missions including Kepler, TESS, and the Roman Space Telescope. His work focuses on characterizing stellar populations and discovering novel astrophysical phenomena through data-driven methodologies. His research spans asteroseismology for probing stellar interiors and Galactic archaeology to map the Milky Way's evolution using variable stars, alongside exoplanetary science investigations into planetary system evolution, habitable worlds, and James Webb Space Telescope atmospheric characterization. A core methodology involves developing machine learning frameworks like deep learning classifiers and generative models for large-scale astronomical datasets. HON's publication trends (2018-2024) reveal consistent innovation at the astrophysics-ML intersection, with emphases on red giant asteroseismology, exoplanet dynamics, and scalable analysis pipelines for space telescope data. Key contributions include flow-based stellar evolution emulators, deep learning oscillation detectors, and large-scale TESS Galactic archaeology studies. Scientific recognition includes: NASA Hubble Fellowship (2020) He actively contributes to major international collaborations as a member of both the TESS and Kepler Asteroseismic Science Consortia, with direct involvement in MIT's TESS mission operations and data pipelines.

Gabor Oroszمشاهده پروفایل

استاد

• Nonlinear dynamics and control
• Time delay systems
• Connected and automated vehicles
• +۶ مورد دیگر

Gabor Orosz is a Professor at the University of Michigan in both the Department of Mechanical Engineering and Department of Civil and Environmental Engineering . His work bridges nonlinear dynamics and control , time delay systems , and connected automated vehicles , with a focus on traffic flow optimization and vehicle safety . Education: PhD in Engineering Mathematics, University of Bristol, UK (2006) MSc in Engineering Physics, Budapest University of Technology and Economics, Hungary (2002) Research Focus : Orosz's research explores the intersection of vehicle automation , connectivity , and nonlinear dynamics . He investigates time delay effects in teleoperation , intent-sharing protocols for cooperative maneuvering , and control barrier functions for safety-critical systems . His work spans theoretical analysis, numerical validation, and real-world experimentation. Article Trends : Recent publications highlight advancements in latency mitigation for remote driving , nonholonomic vehicle control , intent-sharing frameworks , and energy-efficient strategies for connected vehicle systems . Themes include delayed feedback , stochastic communication , and safety-guaranteed control . Awards & Appointments : NSF CAREER Award (2014) Fulbright Scholar at Budapest University of Technology (2023-2024) Editorial roles in Vehicle System Dynamics (2020) and Time Delay Systems (2017) Student Mentorship : Orosz has advised numerous PhD students, including Anil Alan (2024, TU Delft), Chaozhe He (2018, University at Buffalo), and Tamás Molnár (2020, Wichita State University). His alumni work at institutions like Toyota Research Institute , Ford Motor Co. , and Zoox . Labs & Teams : He leads research at the University of Michigan's Mechanical Engineering Department and collaborates with international institutions such as Caltech and Budapest University of Technology . His team focuses on experimental validation of connected vehicle systems and delay-tolerant control .

Henrik von Colerمشاهده پروفایل

استادیار

• Music Technology
• Spatial Audio Systems
• Live Electronics
• +۳ مورد دیگر

Henrik von Coler is an Assistant Professor at Georgia Institute of Technology's School of Music within the College of Design. His work bridges engineering, electronic music, and empirical research, focusing on spatial audio systems, live electronics, and human-computer interaction in musical contexts. He joined Georgia Tech in 2023 after serving as director of the TU Studio for Electronic Music at Technische Universität Berlin from 2015 to 2023, where he founded the Electronic Orchestra Charlottenburg (EOC) to explore live electronic ensembles in multichannel environments. His research emphasizes the integration of sound, space, and HCI to enhance compositional and performative expressiveness. Notable projects include immersive audio installations, virtual instrument design, and AI-assisted composition. Coler has performed globally on immersive audio systems and curated international concerts. His technical contributions span spatial sound synthesis algorithms, networked music systems, and real-time signal processing tools. Key areas of exploration include volumetric music performances in metaverse environments, hybrid spatial interaction via ARCube, and statistical models for spectral synthesis. He has developed open-source systems like Orchestra (for metaverse performances) and SPRAWL (for ensemble interaction). Coler’s work often combines empirical research with artistic practice, aiming to redefine the boundaries of live electronic music through technological innovation. His academic output spans over 30 peer-reviewed articles since 2011, with recent focus on metaverse applications, AI-human collaboration, and immersive audio design. While no formal awards are listed, his leadership roles and project outcomes highlight significant contributions to music technology and spatial audio engineering.

Yongyi Maoمشاهده پروفایل

استاد

• Communications
• Machine Learning

Yongyi Mao is a Professor at the School of Electrical Engineering and Computer Science, University of Ottawa. He holds a Ph.D. in Electrical Engineering from the University of Toronto and has a multidisciplinary background in medical biophysics and engineering. His research focuses on communications and machine learning, with notable contributions to federated learning, information theory, and adversarial robustness. Professor Mao has held academic roles since 2003, advancing from Assistant to Full Professor by 2012. Education: B.Eng., Southeast University, 1992 M.D., Nanjing Medical University, 1995 M.S., University of Toronto (Medical Biophysics), 1998 Ph.D., University of Toronto (Electrical Engineering), 2003 Research interests span machine learning frameworks, federated learning, adversarial attacks, and domain adaptation. His work often bridges theoretical foundations (e.g., generalization bounds) with practical applications in text classification and watermarking. Publications reflect a strong emphasis on machine learning theory and NLP applications, with recent trends toward improving model robustness and generalization. No scientific awards are explicitly listed, though his prolific output suggests significant recognition in the field. Advising and grants: While specific student names or grant details are not provided, his position as a Full Professor indicates active research supervision and likely grant involvement. His lab focuses on advancing AI and communication technologies through interdisciplinary approaches.

Gaye Stephensمشاهده پروفایل

استادیار

• Health Informatics
• Electronic Health Records
• Patient Engagement
• +۴ مورد دیگر

Gaye Stephens serves as Assistant Professor in the School of Computer Science and Statistics at Trinity College Dublin, where she is a core member of the Centre for Health Informatics alongside Dr. Lucy Hederman and Prof. Mary Sharp. She actively contributes to institutional governance as a board member of the Irish Platform for Patient Organisations, Science and Industry (IPPOSI) and serves on the school's research ethics committee. Her research centers on patient-centered health informatics with focus areas including Electronic Health Record design , citizen engagement methodologies (such as Citizen Juries and Think-ins), and scalable information models for healthcare integration. She pioneers approaches that position patients as central stakeholders in health data governance, addressing critical challenges in digital health literacy, informed consent frameworks, and interoperability between legacy and emerging health technologies. Analysis of her recent publications reveals consistent focus on knowledge engineering for healthcare , with particular emphasis on temporal data modeling in knowledge graphs (2024-2025), nurse knowledge elicitation through serious games (2023-2024), and novel methodologies like the WICKED framework for capturing clinical wisdom (2022-2023). Her work consistently bridges technical informatics with human-centered design principles. Stephens actively contributes to national health informatics infrastructure through memberships in: Royal Academy of Medicine of Ireland Council of Clinical Information Officers National Standards Authority of Ireland Health Informatics Group Health Informatics Society of Ireland (including Nursing and Midwifery group) e-Health Ireland ECOSYSTEM working group She supervises across undergraduate, MSc (Health Informatics and Global Health), and PhD programs while leading client-based final year projects. Her teaching portfolio includes Introduction to Health Informatics, Information Modeling, Connected Health, and Electronic Health Record Architectures, with research advising spanning health data governance and patient engagement projects. Stephens co-leads the Knowledge and Data Engineering Group's Health Informatics research stream, focusing on semantic interoperability, adaptive hypermedia systems, and novel engagement models for health data governance. Her current projects emphasize citizen-centered EHR architectures and interdisciplinary approaches to healthcare data integration.

Mehmet Öztürkمشاهده پروفایل

استاد

• Energy Harvesting
• Thermoelectrics
• Nanoelectronics
• +۵ مورد دیگر

Dr. Mehmet Öztürk is a Professor in the Department of Electrical and Computer Engineering at North Carolina State University. His research focuses on nanoelectronics, energy harvesting, and advanced materials for flexible electronics, particularly thermoelectric devices for body heat energy conversion. He holds a Ph.D. in Electrical Engineering from NC State, a Master’s from Michigan Technological University, and a Bachelor’s from Bogazici University. Dr. Öztürk’s research interests span Physical Electronics, Photonics, and Magnetics, with emphasis on novel materials and processes for thermoelectric generators and wearable technologies. His work includes developing flexible, high-efficiency thermoelectric systems using liquid metal interconnects and graphene-doped elastomers. Recent projects involve aerosol spray deposition techniques for stretchable electronics and optimizing materials for body heat harvesting systems. Key scientific contributions include analytical models for thermoelectric energy extraction, high thermal conductivity composites, and microporous CNT nanocomposites. His work bridges fundamental material science with applied engineering solutions for energy-efficient wearable devices. Awards: 2020 William F. Lane Outstanding Teaching Award 2009 IEEE Fellow for contributions to Si/SiGe epitaxy 2006 IEEE Undergraduate Teaching Award Lab Affiliations: Center for Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST)