جست‌وجوی استاد و پژوهشگر

Hassan Aqeel Khanمشاهده پروفایل

مدرس ارشد

• Medical Imaging AI
• Neurotechnology
• Computational Pathology
• +۲ مورد دیگر

Dr. Hassan Aqeel Khan is a Senior Lecturer in Applied AI & Robotics at Aston University's School of Computer Science and Digital Technologies. His research focuses on AI/ML applications in healthcare, particularly medical imaging, neuroscience, and resource-constrained settings. He holds a Ph.D. from Michigan State University and is a Fellow of the Higher Education Academy (FHEA). Research Focus: Key innovations include: Eye-tracking systems for histopathology annotation Open-source EEG analysis tools (e.g., NeuroAssist) AI diagnostics for low-resource healthcare environments Publication Trends: Recent works (2021-2024) emphasize accessible AI tools for neurological monitoring and cancer diagnosis, with 60% focusing on open-source medical datasets and algorithms. Teaching: Teaches Programming Languages, Enterprise Computing, and Machine Learning. Previously developed curricula at University of Jeddah and NUST Pakistan. Laboratory: Leads healthcare AI research in the Engineering for Health group and Aston Centre for AI Research.

Ahmad Beltaguiمشاهده پروفایل

دانشیار

• Design and Design Driven Innovation
• Service Operations Management
• 3D Printing and Additive Manufacturing
• +۳ مورد دیگر

Dr. Ahmad Beltagui is a Reader in Operations and Service Management at Aston Business School, part of the College of Business and Social Sciences at Aston University. He holds a PhD in Manufacturing Engineering and Operations Management from the University of Nottingham and an MEng in Product Design Engineering from the University of Strathclyde. His research focuses on design-driven innovation, servitization, 3D printing, and innovation ecosystems. He has received funding from the EPSRC and British Academy, and his work has been featured in media outlets like BBC World Service and The Conversation. He is a Senior Fellow of the Higher Education Academy and teaches modules like Service Operations Management and User Experience Design. His research explores the intersection of technology adoption, sustainability, and organizational transformation. Education: PhD, University of Nottingham (2011) MEng, University of Strathclyde (2007) PGCert Professional Practice, University of Wolverhampton Research Interests: Design and Design-Driven Innovation Service Operations Management 3D Printing & Additive Manufacturing Business Model Innovation Innovation Ecosystems Funding Highlights: EPSRC (£99,899) for Digital Twin Prototype Development (2019–2020) British Academy/Leverhulme (£9,955) for 3D Printing Research (2018–2020) Media Contributions include articles on 3D printing’s societal impact, low-carbon heating, and crisis response technologies.

• Biological and Artificial Vision
• Human Sensory Augmentation
• Secure Data Analytics
• +۳ مورد دیگر

Dr. Noel Murphy is an Associate Professor and Head of the School of Electronic Engineering at Dublin City University (DCU). He has held various leadership roles, including Associate Dean for Education in the Faculty of Engineering and Computing (2005-2007), Head of School (2007-2012, 2015-2018, and returning in 2021). He has been teaching at DCU since 1986 and has contributed extensively to academic governance, including roles on Academic Council and Governing Authority committees. Dr. Murphy holds a BA (Mod) in Theoretical Physics from Trinity College Dublin (TCD), a PhD from DCU (2003) on Information Theory models for Biological and Artificial Vision, and a part-time MA in Pure Mathematics from Maynooth University (2015). His research focuses on: Biological and Artificial Vision: Including Information Theoretic models and the work of Stephen Grossberg. Secure Data Analytics: Particularly leveraging SGX-enabled applications for data ownership control. Algebraic Number Theory: Exploring elliptic curves and Apéry's Constant. IoT and Edge Computing: Focusing on secure processing for IoT applications. Human Sensory Augmentation and Multimedia Information Retrieval. In addition to his teaching and leadership roles, Dr. Murphy has supervised numerous PhD and Master's students to completion. He has secured funding as Principal Investigator or co-Investigator on national and EU-funded research projects. He is affiliated with DCU's Entwine Research Centre. Outside academia, Dr. Murphy is Honorary Secretary of the Irish Light Aviation Society, holds a Private Pilot’s License, and is involved in aircraft restoration projects, including a 1940 Piper J5 and a Vans RV-8.

• Natural Language Processing
• Computer Vision
• Deep Learning
• +۳ مورد دیگر

Dr. Vimal Kumar Kumar serves as a Research Fellow at the University of Limerick's Department of Computer Science and Information Systems, affiliated with Lero – the Irish Software Research Centre. His academic career includes prior faculty positions as Assistant Professor at Jaypee University of Information Technology (2009-2022) and Lecturer at SRM Institute of Science and Technology (2007-2009), followed by a Postdoctoral Researcher role at University College Dublin (2022-2023). His educational background includes: PhD in A Novel sense based Hindi to Tamil machine translation system from Jaypee Institute of Information Technology (2019) Masters from Anna University Chennai (2005-2007) Bachelor from PSG College of Technology (2000-2004) Dr. Kumar's research centers on Natural Language Processing with specialized focus on machine translation for Indian languages (Hindi, Tamil), text summarization, and sentiment analysis. He extends this work into computer vision applications for medical imaging and activity recognition, plus deep learning implementations for IoT-based agricultural monitoring. His methodology frequently addresses challenges in low-resource language processing and develops optimized neural network architectures for mobile deployment. Analysis of his publication trends reveals consistent interdisciplinary innovation, particularly in healthcare applications (retinal disease detection), agricultural technology (crop yield prediction), and social media analytics. His work demonstrates strong emphasis on practical AI solutions for resource-constrained environments and underrepresented linguistic communities, often leveraging generative models and contextual embeddings. Dr. Kumar actively contributes to Lero's research initiatives, aligning his technical work with UN Sustainable Development Goals through software solutions addressing global challenges in health, food security, and digital inclusion.

TOORAJ NIKOUBINمشاهده پروفایل

استاد

• NanoElectronics Device/Circuit/System
• Approximate Computing
• Reconfigurable Computing
• +۳ مورد دیگر

Dr. Tooraj Nikoubin is a Professor of Instruction in the Department of Electrical and Computer Engineering at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. He holds a Ph.D. in Computer Engineering from Shahid Beheshti University (2009), and M.Sc./B.Sc. degrees in Electrical Engineering-Electronics from K.N.T. University of Technology (Iran). His research focuses on nano-electronics, approximate computing, reconfigurable systems, and wearable electronics, emphasizing device-circuit co-design in emerging technologies. With over 35 journal/conference publications and one book chapter over 13+ years in academia, Dr. Nikoubin teaches both graduate and undergraduate courses across computer and electrical engineering domains. Research interests include nano-scale device optimization, energy-efficient circuits, and hardware acceleration for edge computing applications. His work spans from biometric authentication systems using PPG signals to drone-based precision agriculture and molecular property prediction. Recent efforts prioritize low-power, area-efficient designs in cryptography (e.g., AES S-box optimization) and health monitoring wearables. Dr. Nikoubin has contributed to innovative hardware solutions such as fiber antennas for wireless body area networks and low-cost radar systems for structural health monitoring. His lab explores intersections between emerging technologies like CNTFETs and FinFETs with system-level power management. Current openings exist for students/researchers to contribute to this dynamic research environment.

• Software Engineering
• Computer Science Education
• Modeling and Simulation
• +۳ مورد دیگر

Dr. Bruce Mabis is a Clinical Assistant Professor of Computer Science at the University of Evansville, affiliated with the College of Engineering and Science. With 46 years in Evansville, he has taught at UE since 1975 and three other regional universities. His expertise spans software engineering, computer science education, and systems modeling. Education: PhD in Computer Science (Vanderbilt University, 1992), M.S. in Electrical Engineering (University of Evansville, 1990), B.S. in Physics (Capital University, 1971). Research interests include curriculum design, simulation modeling, and software engineering methodologies. His work emphasizes educational innovation and practical applications of computer science principles. Key publications focus on systems analysis, programming pedagogy, and simulation frameworks. No scientific awards are listed, but his career spans over four decades of academic contributions. He has advised no named students in the provided texts. Grants and lab affiliations are not explicitly mentioned.

Haopeng Zhangمشاهده پروفایل

استادیار

• Natural Language Processing
• Generative AI
• AI4Science (Healthcare, Linguistics, Sensing)
• +۳ مورد دیگر

Haopeng Zhang is an Assistant Professor in the Department of Information and Computer Sciences at the University of Hawaii at Mānoa, leading the ALOHA Lab. He holds a Ph.D. from the University of California, Davis (advised by Dr. Jiawei Zhang), dual M.S. degrees from Georgia Tech (Electrical Engineering and Computational Science), and a B.S. from UIUC (Electrical Engineering). His research focuses on NLP, Generative AI, AI4Science, and Graph Mining, emphasizing biomedical applications, multimodal reasoning, and workflow generation. Recent achievements include organizing workshops at EMNLP and ACL, receiving grants from NSF and OpenAI, and developing tools like StrucSum and MermaidFlow. Education: Ph.D., Computer Science, UC Davis (2024) M.S., Electrical Engineering & Computational Science, Georgia Tech B.S., Electrical Engineering, UIUC Research interests span structural summarization, LLM applications in healthcare and linguistics, and graph-based NLP systems. His work bridges theoretical advancements with practical tools, including the ALOHA Lab's contributions to reliable summarization systems and multimodal benchmarks. Notable contributions include the DomainSum benchmark and Wi-Chat wireless sensing framework. Key awards include UH travel grants, OpenAI credits, and NSF computing allocations. He actively serves on conference committees (ACL, KDD) and reviews for top journals (ACM TKDD, IEEE transactions). Teaching responsibilities include Advanced AI and Machine Learning courses at UH Mānoa. Lab activities focus on AI-driven solutions for scientific domains, with ongoing projects in biomedical event extraction and low-resource language support.

• Language Assessment
• Language Didactics (Foreign Languages)
• Educational Technology
• +۳ مورد دیگر

Raili Hilden is a full professor in language didactics (foreign languages) at the University of Helsinki's Department of Education, Faculty of Educational Sciences. Her core activities include research, teaching, and societal impact with a focus on language assessment, particularly in high-stakes testing contexts. She leads research projects like AASIS (Automatic assessment of spoken interaction in second language) and DigiTala, exploring automated assessment tools for speaking proficiency. She chairs the Finnish National Matriculation Examination Board's Swedish section and contributes to national curriculum development. Research Interests : Language assessment methodologies, teacher assessment literacy, educational equity in language education, and the integration of technology in language testing. Current projects emphasize automated scoring systems and multimodal assessment formats. Key Contributions : Directed national evaluations of language learning outcomes (2012-2014), developed grading criteria for Finnish national curricula, and pioneered computer-based language testing innovations. Her work bridges educational policy, technology, and pedagogical practice. Awards : Recipient of top honors including Vuoden kieltenopettaja 2003, Kulturfonden Språkpriset 2004, and The FIPLV International Award 2005. Active in international conferences and serves on boards like the Finnish Matriculation Examination Board. Grants/Projects : Multiple Academy of Finland grants (AASIS: 2023-2027; DigiTala: 2025-2026), DD-LANG (2022-2026) focusing on diagnostic language assessment innovations. Labs/Teams : Leads multidisciplinary teams combining linguistics, computer science, and educational research to advance automated assessment technologies. Collaborates with Scandinavian institutions on teacher assessment literacy initiatives.

Jeremy Barnesمشاهده پروفایل

استادیار

• Cross-lingual Methods
• Transfer Learning
• Sentiment Analysis
• +۵ مورد دیگر

Jeremy Barnes is an Assistant Professor in the IXA Group at the University of the Basque Country (UPV/EHU), part of the HiTZ Centre. He holds a PhD in Computational Linguistics and has extensive postdoctoral experience at the University of Oslo. His research focuses on cross-lingual methods, sentiment/emotion analysis, weak supervision, and under-resourced language resources. He has contributed to projects like NorDial and NorLM, developing tools like skweak. Barnes teaches courses in computational syntax, text mining, and NLP. Education: PhD (Pompeu Fabra University), M.A. and B.A. in Linguistics Key Projects: LUMINOUS (multimodal LLMs), SANT (Norwegian sentiment analysis) His work spans structured sentiment analysis, cross-lingual transfer learning, and dialectal feature identification. He has received awards for his book Sonic Ethnography (2021) and photography (2020). Barnes advises numerous Master's theses and collaborates internationally on NLP challenges.

Denilson Barbosaمشاهده پروفایل

استاد

• Natural Language Processing
• Information Retrieval
• Machine Learning
• +۳ مورد دیگر

Denilson Barbosa is a Professor of Computing Science at the University of Alberta's Faculty of Science. He holds a PhD and specializes in Natural Language Processing, Information Retrieval, and Machine Learning. His research focuses on knowledge extraction, entity recognition, and knowledge graph construction. Barbosa teaches courses like CMPUT361 (Information Retrieval) and CMPUT656 (Knowledge Graphs). He served as President of the Canadian Artificial Intelligence Association (CAIAC) from 2023 to 2024. His work includes developing tools like the NLP Workbench and contributing to open relation extraction, Wikipedia analysis, and low-resource language models. Education and Background: Barbosa's academic background aligns with his research interests in computational linguistics and AI applications. His teaching emphasizes practical skills in algorithms, data structures, and machine learning for text processing. Research Highlights: Barbosa's research spans semantic graphs, probabilistic language models, and defect prediction systems. He explores challenges in multilingual NLP, particularly for Indigenous and low-resource languages like Cree. His work often integrates machine learning with traditional IR methods to improve system efficiency and accuracy. Recent Contributions: Notable recent projects include improving Bengali/Hindi LLMs, evaluating QA systems via textual entailment, and developing Bayesian methods for crowdsourced truth discovery. His articles reflect his interdisciplinary approach, combining theory with real-world applications in education, software engineering, and social media analysis.

Faith-Michael Uzokaمشاهده پروفایل

استاد

• Medical Informatics
• Technology Adoption
• Computing Disciplinary Studies
• +۵ مورد دیگر

Prof. Faith-Michael Uzoka is a full Professor in the Department of Mathematics & Computing at Mount Royal University, Canada. He holds adjunct professorships at the Faculty of Commerce, Catholic University of Eastern Africa (Kenya) and the ICT University (USA). His expertise spans Medical Informatics, Technology Adoption, and Computing Disciplinary Studies. He has over three decades of academic experience, including a postdoctoral fellowship at the University of Calgary (2004-2005). Education includes a PhD/MS in Computer Science from Nigeria’s Federal University of Technology, an MBA from the University of Benin, and postdoc training in Calgary. His research focuses on AI-driven healthcare solutions, particularly in tropical disease diagnosis and maternal health outcomes, with emphasis on explainable AI and mobile health applications in resource-limited settings. Editorial roles include International Journal of Biomedical Engineering and multiple conferences. His recent work emphasizes machine learning for malaria/typhoid diagnosis, maternal healthcare prediction systems, and digital health interventions in low-income countries. He has reviewed for high-impact journals like Journal of Healthcare Engineering and ACM Transactions on Computing Education. His projects include developing mobile diagnostic systems for febrile diseases, eHealth frameworks in developing nations, and AHP-based decision models for healthcare financing. He collaborates internationally on sterile processing practices in African hospitals and cloud computing adoption in universities.

Kevin Leachمشاهده پروفایل

استادیار

• Cybersecurity
• Software Engineering
• Dependable Systems
• +۳ مورد دیگر

Kevin Leach is an Assistant Professor of Computer Science at Vanderbilt University's School of Engineering. His research focuses on designing dependable cybersecurity systems and software engineering practices that withstand sophisticated adversarial attacks. He holds a PhD from the University of Virginia (2016), where he received the Louis T Rader Outstanding Research Award. Prior to Vanderbilt, he was a research scientist and lecturer at the University of Michigan. Education: Ph.D. in Computer Engineering, University of Virginia MS in Computer Science, George Mason University BS with Distinction in Computer Engineering and Computer Science, University of Virginia His research investigates two core areas: leveraging hardware capabilities like Trusted Execution Environments for low-overhead security instrumentation, and understanding how developers and operators make decisions in adversarial environments. He has published over 30 refereed articles, 3 of which have received awards. Recent work includes studies on cognitive biases in cybersecurity competitions, AI-driven code assessment, and malware detection techniques. Awards: Louis T Rader Outstanding Research Award (2016) 3 award-winning papers (specific awards unspecified) His research bridges technical security mechanisms with human decision-making processes, emphasizing both system dependability and developer/operator awareness. Current projects include work on federated learning defenses, runtime security optimization for embedded systems, and ethical considerations in crowdsourced data labeling.

Benjamin Bergenمشاهده پروفایل

استاد

• Cognitive Science
• Linguistics
• Language Comprehension
• +۵ مورد دیگر

Benjamin Bergen is a Professor in the Department of Cognitive Science at UC San Diego, affiliated with the Language and Cognition Lab. His research focuses on language processing, metaphor, profanity, and embodied cognition. He holds a PhD from UC Berkeley (2001) and has authored over 150 peer-reviewed publications. Bergen's work bridges cognitive science, linguistics, and AI, investigating how humans and machines process meaning. Research interests include: (1) Embodied simulation in language understanding, (2) Neural language models' cognitive plausibility, (3) Impact of swearing on communication, (4) Multimodal interaction effects during driving. Recent projects explore LLM capabilities in theory of mind tasks and cross-lingual transfer learning. Public engagement includes over 100 media appearances since 2016, including interviews with Communications of the ACM (2023), Discover Magazine (2023), and Netflix's History of Swear Words (2021). Authored popular science books on profanity and cognitive linguistics.

Thanasis Korakisمشاهده پروفایل

عضو هیئت علمی

• Wireless Networks
• Access Layer Protocols
• Cooperative Networks
• +۷ مورد دیگر

Thanasis Korakis is a Research Assistant Professor in the Electrical and Computer Engineering Department at NYU Tandon School of Engineering, affiliated with the Center for Advanced Technology in Telecommunications (CATT). He holds a Ph.D. in Computer and Communication Engineering from the University of Thessaly and has been involved in visiting research roles at UC Riverside and CATT. His research focuses on wireless networks, with an emphasis on access layer protocols, cooperative networks, directional antennas, and QoS provisioning. Education: Bachelor of Technology in Informatics, University of Athens (1994) M.S. in Data Networks and Telecommunications, University of Athens (1997) Ph.D. in Computer & Communication Engineering, University of Thessaly (2005) Research Interests: Dr. Korakis’ work spans experimental testbeds (e.g., Witest Lab), 802.11/802.16 standardization, and implementation of cooperative MAC protocols. His contributions include frameworks for cooperative handoff in wireless mesh networks, MAC protocols leveraging directional antennas, and dynamic rate adaptation for video multicast. Recent work explores 5G V-RAN reliability, AI-driven security systems, and IoT testbeds. Publications: His articles cover topics like 5G network optimization, blockchain applications in telecom, and AI in forensic investigations. Notable trends include experimental validation of network functions, security-enhanced systems, and cross-layer protocol design. Scientific Awards: Ericsson Award of Excellence in Telecommunications (2006) Advising & Grants: He leads the Witest Lab and has served on technical committees for ICC, WCNC, and SECON. His work includes grants related to wireless testbeds and standardization efforts. Collaborations involve institutions like CATT and NYU’s Tandon School. Labs & Teams: He directs the Wireless Implementation Testbed Laboratory (Witest Lab), focusing on real-world experimentation with wireless protocols and technologies.

Tirthak Patelمشاهده پروفایل

استادیار

• Quantum Computing
• High-Performance Computing (HPC)
• Quantum Machine Learning
• +۳ مورد دیگر

Tirthak Patel is an Assistant Professor in the Department of Computer Science at Rice University and Director of the Positive Technology Lab. His research focuses on systems-level challenges at the intersection of quantum computing and high-performance computing (HPC), emphasizing reliability, performance, and energy efficiency trade-offs. He holds a PhD from Northeastern University (2023) and prior degrees from Northeastern and the University of Toronto. Education: PhD in Computer Engineering, Northeastern University (2023) MS in Electrical and Computer Engineering, Northeastern University (2019) Bachelor of Applied Science in Electrical Engineering, University of Toronto (2017) His research explores quantum system software, compiler design for neutral atom quantum architectures, and quantum machine learning. Notable contributions include frameworks like PARALLAX (compiler for neutral atom quantum computers) and GEYSER (compilation for neutral atom systems). He prioritizes open-source tools and reproducible research. Research Trends in Publications: Recent work emphasizes quantum noise utilization, quantum GANs, and compiler optimizations for NISQ-era hardware. He also addresses challenges in hybrid quantum-classical systems and quantum cloud security (e.g., OpaQue for program obfuscation). Awards: 2024 ACM SIGHPC Doctoral Dissertation Honorable Mention 2021 ACM-IEEE CS George Michael HPC Fellowship 2024 Rice Outstanding Undergraduate Research Mentor Award Advising & Grants: While specific grant details aren't listed, his work is supported by open-source contributions and industry collaborations. He advises students through Rice's Quantum Computing programs and teaches courses like COMP 448/558: Quantum Computing Algorithms. Labs & Teams: Directs the Positive Technology Lab, focused on advancing quantum computing systems through interdisciplinary approaches. Collaborates with industry partners and international conferences as a TPC member for venues like SC, ISCA, and ICCAD.