جست‌وجوی استاد و پژوهشگر

Ninghao Liuمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Explainable AI (XAI)
• +۶ مورد دیگر

Dr. Ninghao Liu is an Assistant Professor of Computer Science in the School of Computing at the University of Georgia, part of the Franklin College of Arts & Sciences - Division of Physical & Mathematical Sciences. He holds a Ph.D. in Computer Science from Texas A&M University (2021) and an M.S. in Electrical and Computer Engineering from Georgia Institute of Technology (2015). His research focuses on Explainable AI (XAI), Graph Mining, Model Fairness, Recommender Systems, and Outlier Detection, with notable contributions to foundational AI techniques and their applications in education, healthcare, and environmental sciences. Dr. Liu has secured significant funding, including a three-year NSF grant (2022–2025) for 'Graph-Oriented Usable Interpretation' and a five-year $10 million grant from the U.S. Department of Education (2024–2029) for the GenAI Empowered National Initiative for STEM+C Education. He has also been honored with the Outstanding Paper Award at ICML 2022, Best Paper Award Shortlist at WWW 2019, and other distinctions. His work emphasizes interpretable machine learning, graph neural networks, and addressing algorithmic bias. He collaborates across disciplines, contributing to radiology AI, climate-smart forestry, and pandemic prediction through knowledge-enhanced deep learning. His lab is based at the Boyd Research and Education Center, where he advances research in trustworthy AI systems and data-centric solutions.

Federico Nutarelliمشاهده پروفایل

استادیار

• International Trade
• Health Economics
• Machine Learning
• +۳ مورد دیگر

Federico Nutarelli is an Assistant Professor of Economics at the IMT School for Advanced Studies Lucca, Italy. His research focuses on the intersection of machine learning and economic analysis, particularly in international trade, health economics, and industrial organization. He holds a Ph.D. in Economics from IMT Lucca, and previously conducted postdoctoral research at Bocconi University. In 2024, he was a Visiting Scholar at MIT Sloan School of Management. Key research interests include causal machine learning methods to analyze heterogeneous firm responses to economic shocks, pharmaceutical market pricing strategies, and structural demand models. His work bridges methodological rigor with applied relevance, contributing to health economics, trade dynamics, and innovation policy. Recent publications (2020–2025) explore topics such as matrix completion for world trade analysis, machine learning applications in economic complexity, and modeling innovation ecosystems. His work often employs advanced statistical techniques like Shapley values and reinforced Bernoulli processes. No scientific awards were explicitly mentioned in the provided texts. Federico collaborates with institutions like Bocconi University and MIT Sloan, reflecting his interdisciplinary network in economics and data science.

Jeff Bardaمشاهده پروفایل

مدرس ارشد

• Poetics
• Contemporary French Poetry
• Sound Arts
• +۶ مورد دیگر

Jeff Barda serves as Senior Lecturer in French Cultural Studies at the University of Manchester, joining in 2020 after a Junior Research Fellowship at Cambridge's Murray Edwards College. Awarded the Manchester Humanities Outstanding Teaching Award in 2020 and promoted to Senior Lecturer in 2023, he maintains active international affiliations including visiting positions at Bordeaux-Montaigne University and London's Institute of Languages, Cultures & Societies in 2024. His research centers on contemporary French poetic practice with emphasis on digital poetics, sound arts, and avant-garde traditions. Key interests include the intersection of media and literature, lettrism, and data-driven creative processes, reflected in his extensive publications on figures like Pierre Alferi and Christophe Tarkos. His second monograph Data Poetics: Contemporary French Poetic Practice in the Age of Digital Overload is under contract with Liverpool University Press. Dr Barda's scholarly impact is evidenced by the 2021 Literary Encyclopedia Book Prize for his first monograph Experimentation and the Lyric in Contemporary French Poetry . His recent publications demonstrate evolving focus from historical avant-gardes to contemporary digital poetics, with increasing attention to OSINT methodologies and cross-disciplinary practices like sports-literature intersections. Manchester Humanities Outstanding Teaching Award (2020) Literary Encyclopedia Book Prize (2021) As an active supervisor welcoming PhD inquiries, Dr Barda contributes to multiple research networks including Marge (Lyon), the European Neo-Avant-Garde Network (Ghent), and 'After Social Networks' (Paris). His teaching excellence complements substantial grant activity supporting international collaborations, particularly in digital humanities initiatives exploring poetic practice in public spheres. His research infrastructure includes affiliations with three major transnational networks examining contemporary creation, with recent projects focusing on image manipulation in poetry and OSINT applications in literary analysis.

• Internet of Things (IoT)
• Wireless Communications
• Statistical Signal Processing
• +۳ مورد دیگر

Professor Jinho Choi is a Chair and Professor in Radio Frequency at the School of Electrical and Mechanical Engineering, University of Adelaide, Australia. He holds a B.E. (magna cum laude) from Sogang University, and M.S.E. and Ph.D. degrees from KAIST. His research focuses on advancing wireless communication and sensing technologies, particularly in IoT, 5G/6G, non-terrestrial networks, and cognitive satellite systems. He authored three books and has been recognized with the 1999 EURASIP Best Paper Award, IEEE Fellowship, and inclusion in Stanford's Top 2% Scientists list since 2020. He currently serves as a Senior Editor of IEEE Wireless Communications Letters and editorial roles in multiple journals. Education: B.E. (Electronics Engineering) - Sogang University, Seoul (1989) M.S.E. (Electrical Engineering) - KAIST (1991) Ph.D. (Electrical Engineering) - KAIST (1994) Research Interests: Professor Choi's work addresses connectivity challenges in non-terrestrial networks, leveraging statistical signal processing and machine learning. Current projects include UAV-assisted LEO satellite technologies, cognitive satellite radios, and semantic communication protocols. His research aims to enhance global connectivity and efficiency in terrestrial and satellite networks. Publications: His recent work spans semantic communication, satellite quantum key distribution, federated learning optimization, and coverage diversity in mega constellations. These studies reflect trends in 6G-ready technologies, AI-driven communication systems, and hybrid satellite-terrestrial networks. Awards: 1999 Best Paper Award for Signal Processing (EURASIP) IEEE Fellow (Leadership in technical excellence) World’s Top 2% Scientists (Stanford University, 2020–present) Grants & Supervision: As a senior academic, he oversees grants in wireless innovation and has advised numerous students on advanced communication systems. His lab focuses on next-generation networks, integrating theoretical insights with practical implementations. Labs/Teams: Active in interdisciplinary teams at the University of Adelaide, collaborating on projects funded by industry and government to bridge gaps between academic research and real-world applications.

Xiaohan Yuمشاهده پروفایل

مدرس

• Ultra-Fine-Grained Visual Categorization
• Smart Farming
• Automated Crop Cultivar Identification
• +۳ مورد دیگر

Dr. Xiaohan Yu is a Lecturer in Artificial Intelligence at Macquarie University's School of Computing, joining in December 2023. Previously, he completed his doctoral studies at Griffith University and served as a Research Fellow at the ARC Research Hub for Driving Farming Productivity. His research focuses on Ultra-Fine-Grained Visual Categorization (Ultra-FGVC), Smart Farming, and Automated Crop Cultivar Identification, with over 70 publications in top-tier venues like ICCV, CVPR, and IEEE Transactions. He holds editorial roles at Pattern Recognition and SN Computer Science , and received the APRS Early Career Award (2022) and ACM MM 2024 Outstanding Area Chair distinction. Education: Completed doctoral studies in Artificial Intelligence at Griffith University, Australia. Research Interests: Ultra-Fine-Grained Visual Categorization (Ultra-FGVC) Smart Farming and Agricultural Robotics Computer Vision Applications in Healthcare (e.g., trachoma detection) Deep Learning, Continual Learning, and Domain Adaptation Key Contributions: Pioneered Ultra-FGVC research, developed frameworks like Mix-ViT and CLE-ViT, and contributed to benchmarking multi-object tracking in farming. His work bridges pattern recognition with real-world applications in agriculture and healthcare. Scientific Awards: Australian Pattern Recognition Society (APRS) Early Career Researcher Award 2022 ACM Multimedia 2024 Outstanding Area Chair Award Advising & Grants: Actively involved in editorial roles (Area Chair for ACM MM, IJCNN) and grant-funded research through ARC hubs. His work is supported by collaborations in agriculture and AI-driven solutions for crop cultivar identification. Labs & Affiliations: Member of Macquarie's Smart Green Cities Research Centre and Frontier AI Research Centre , advancing interdisciplinary AI applications.

• Credit Scoring
• Consumer Credit Risk Modelling
• Predictive Analytics
• +۳ مورد دیگر

Christophe Mues is a Professor of Data Science and Information Systems at the University of Southampton's School of Management, within the Department of Decision Analytics and Risk. His research focuses on credit scoring, consumer credit risk modeling, and applications of predictive analytics, including machine learning techniques for credit risk assessment. He leads the Information Systems & Business Analytics section and supervises multiple PhD students in Business Studies and Management. His work spans advanced statistical methods for predicting Probability of Default (PD), Loss Given Default (LGD), and loan profitability. He is actively involved in the academic community, serving on the organizing committee for the Credit Scoring and Credit Control conference. His teaching includes topics in information systems and business analytics. Contact: C.Mues@soton.ac.uk. Research Interests: Credit Scoring and Consumer Credit Risk Modelling Predictive Analytics in Finance Machine Learning Applications (Deep Learning, Graph Neural Networks) Non-Traditional Data Integration Credit Model Transparency and Fairness Debt Collection Optimization PhD Supervision: Currently guiding four students in Business Studies & Mngt: Kameswara Rao Korangi, Sarthak Gurnani, Pablo Casas, and Nora Agyei-Ababio. Professional Activities: Leads research groups and contributes to international conferences. His work bridges academic research with practical financial risk solutions, emphasizing ethical AI and regulatory compliance in credit modeling. Biography: Holds a PhD in Applied Economics from KU Leuven (Belgium). Joined the University of Southampton in 2004, advancing from researcher to his current leadership role in Decision Analytics and Risk.

Ming Liمشاهده پروفایل

استاد

• Audio and Speech Processing
• Multimodal Behavior Signal Analysis
• Speech Synthesis
• +۳ مورد دیگر

Ming Li is a Professor of Electrical and Computer Engineering at Duke Kunshan University's Division of Natural and Applied Science, and a Principal Research Scientist at the Digital Innovation Research Center. He holds an adjunct position as a Professor at Wuhan University's School of Computer Science. His research focuses on audio/speech processing, multimodal behavior signal analysis, and applications in autism spectrum disorder diagnosis. Li has over 200 publications and serves on editorial boards of journals like IEEE Transactions on Audio, Speech and Language Processing. Education: Ph.D. in Electrical Engineering from the University of Southern California (2013). Awards include the IBM Faculty Award (2016), ISCA 5-Year Best Paper Award (2018), and Youth Achievement Award (2020). He leads initiatives in anti-spoofing countermeasures, voice conversion, and speech synthesis. Recent Courses: Random Signals and Noise Speech Recognition Data Science Key Research Contributions: Development of datasets like KunquDB, TMCSpeech, and systems for speaker verification, deepfake detection, and autism diagnosis tools. His work bridges signal processing with clinical applications, leveraging AI for social interaction improvement in neurodiverse populations.

Ilan Shomoronyمشاهده پروفایل

استادیار

• Information Theory
• Bioinformatics
• DNA Data Storage
• +۴ مورد دیگر

Ilan Shomorony is an Assistant Professor at the University of Illinois at Urbana-Champaign, affiliated with the Grainger College of Engineering, Electrical and Computer Engineering Department, and Coordinated Science Lab. He also holds an affiliation with the Carl R. Woese Institute for Genomic Biology. His research focuses on genomic data science, information theory, and their applications in DNA storage, bioinformatics, and machine learning. He has received an NSF CAREER Award for his work on genomic data science. Shomorony’s academic journey includes roles in multiple departments and labs, reflecting his interdisciplinary approach. His recent publications explore topics such as molecular communication channel capacity, metagenomic binning, and efficient sequence alignment algorithms. Education: Not explicitly stated in provided text, but his academic roles suggest advanced degrees in electrical engineering or computer science. Research Interests: His work bridges theoretical information theory and practical genomic applications. Key areas include DNA storage systems, algorithmic improvements for sequence analysis, and the application of machine learning to biological data. He develops novel coding schemes for molecular data storage and explores fundamental limits of genomic data reassembly. Grants & Awards: NSF CAREER Award (2021): Supported research on genomic data science, integrating informational theory and algorithm design. Labs & Teams: Active in the Coordinated Science Lab and collaborates with the Carl R. Woese Institute for Genomic Biology, emphasizing interdisciplinary research in genomics and computational biology.

• Machine Learning
• Bayesian Optimization
• Gaussian Processes
• +۴ مورد دیگر

Ti John is a Research Fellow at Aalto University's Department of Computer Science within the School of Science. He is affiliated with Professor Marttinen's research group and the Probabilistic Machine Learning group led by Professor Samuel Kaski. His work connects with the Finnish Center for Artificial Intelligence (FCAI) and the Helsinki Institute for Information Technology (HIIT). Dr. John's research focuses on machine learning, particularly Bayesian optimization, Gaussian processes, and point process models. His work spans theoretical developments in neural processes and practical applications in healthcare analytics and large language models. He has made significant contributions to equivariant neural processes, causal mediation analysis in healthcare, and interpretability of additive models. His publication record shows consistent output with 17 publications between 2021-2024, including multiple papers at top AI conferences like NeurIPS, ICML, and ICLR. His research demonstrates strong interdisciplinary connections between statistical modeling, artificial intelligence, and healthcare applications. Active reviewer for NeurIPS, ICLR, AISTATS Reviewer for Journal of Machine Learning Research Member of Finnish Center for Artificial Intelligence project Dr. John has been actively contributing to the machine learning community through peer review and conference participation, demonstrating expertise across multiple subfields of artificial intelligence and statistical modeling.

Roman Matuszewskiمشاهده پروفایل

دانشیار

• Automated Reasoning
• Formalized Mathematics
• Computer Science
• +۳ مورد دیگر

Roman Matuszewski is a retired Associate Professor at the University of Bialystok, affiliated with the Faculty of Philology's Department of Applied Linguistics. His research focuses on automated reasoning, formalized mathematics, and the Mizar Project, which he has been involved with since its inception in 1973. He holds a PhD in Computer Science from Shinshu University (2000) and has held academic positions at multiple institutions, including part-time roles at Bogdan Janski University. Education: PhD in Computer Science (2000), Master of Science in Mechanics (1975), Engineer (1973), all from Polish institutions. His work emphasizes formal proof systems, mathematical knowledge management, and education integration of automated reasoning tools. Research interests include automated deduction, formal proof verification, and the application of these methods to mathematics education. His contributions to the Mizar Mathematical Library and its 50-year history (celebrated in 2023) are foundational for interactive theorem proving. Key awards include the Silver Cross of Merit (2004) and multiple Rector’s prizes. He has organized major conferences like MKM2004 and served on program committees for events such as IJCAR and Tableaux. Grants include leadership roles in EU-funded projects like TYPES and CALCULEMUS. His work bridges computer science and mathematics through formalized systems, impacting both research and education.

Abdolmajid Erfaniمشاهده پروفایل

استادیار

• Construction Economics
• Data-driven Infrastructure Management
• Project Delivery and Procurement
• +۵ مورد دیگر

Dr. Abdolmajid Erfani is an Assistant Professor in the Department of Civil, Environmental, and Geospatial Engineering at Michigan Technological University. He holds a PhD in Civil Engineering from the University of Maryland, College Park (2023), an MSc in Construction Engineering and Management from the University of Tehran (2019), and a BSc in Civil Engineering from the same university (2017). His research focuses on construction economics, smart construction technologies, data-driven infrastructure management, workforce development, and AI applications in project delivery. Dr. Erfani leads studies on workforce equity in transportation and construction industries, leveraging big data and natural language processing. He has published over 30 peer-reviewed papers and received prestigious ASCE awards including the 2024 Arthur M. Wellington Prize and Thomas Fitch Rowland Prize. He serves on the editorial board of the ASCE Journal of Management in Engineering. His recent grants include a National Cooperative Highway Research Program project (PI, 2024–2027) on price adjustment clauses for construction risk sharing and a Minnesota DOT-funded initiative (PI, 2025–2027) on leveraging transportation investments for economic equity. He also co-leads a Federal Railway Administration project (Co-PI, 2025–2028) aimed at promoting railroading careers. Research interests span equity analysis, AI modeling, and predictive analytics for infrastructure resilience. He integrates LinkedIn data and machine learning to study gender disparities in career progression, achieving groundbreaking insights in leadership dynamics within construction sectors.

Derrick R. Spiresمشاهده پروفایل

دانشیار

• Early Black Print Culture
• Citizenship Studies
• African American Intellectual History
• +۳ مورد دیگر

Derrick R. Spires serves as Associate Professor of English in the College of Arts & Sciences at the University of Delaware, specializing in early Black print culture, citizenship studies, and African American intellectual history. His scholarly mission centers on recovering the rich imaginative worlds African-descended people generated through print media and how these imaginings facilitated material change, spanning from tragicomic expressions to mundane daily practices. Spires' research interrogates how Black writers articulated expansive, practice-based theories of citizenship through robust print networks including newspapers, the Colored Conventions movement, and ephemeral publications. His work reveals the centrality of seriality, pseudonymity, and collaborative performance in Black political thought, demonstrating how print culture enabled Black communities to navigate and reshape citizenship frameworks despite systemic exclusion. He examines how early African American literature cultivated aesthetic sensibilities that sustained resistance and community building. Analysis of his 2016-2024 publications reveals consistent thematic threads: the material conditions of Black bibliography, gendered dimensions of political expression, and the performance aspects of print culture. His scholarship increasingly engages with digital humanities methodologies while maintaining deep archival rigor, particularly regarding Dorothy Porter's bibliographic mission and liberation bibliography frameworks. Key publications map connections between early Black social media practices and contemporary digital activism. Spires' accolades include: Modern Language Association Prize for First Book (2020) St. Louis Mercantile Library Prize (2020) National Endowment for the Humanities Fellowship Ford Foundation Fellowship Social Science Research Council Fellowship Mellon/Mays Initiatives Fellowship American Antiquarian Society Fellowship His editorial leadership encompasses the Broadview Anthology of American Literature and the University of Pennsylvania Press series 'Black Print and Organizing in the Long Nineteenth Century.' Research has been supported by major fellowships examining Black print networks, though specific grant details beyond institutional fellowships aren't specified. Spires contributes significantly to recovering marginalized intellectual traditions through meticulous bibliographic work and theoretical innovation in citizenship studies.

• Computer Science
• Machine Learning
• Health Monitoring Systems
• +۷ مورد دیگر

Muhammad Waqas is a researcher affiliated with COMSATS University Islamabad , where he holds a position in the Department of Meteorology under the School of Applied Sciences and Humanities . His academic collaborations span institutions like Bahria University, National University of Technology, and University of Bahrain, indicating a multidisciplinary approach. Research interests include Mechanisms for integrating fuzzy logic and machine learning in health monitoring Application of deep learning to medical imaging and clinical diagnostics Development of smart sensors for wearable technology in biomechanics Analysis of social media data for public health surveillance and sentiment analysis Investigation of digital citizenship and ICT leadership in educational contexts Trends in his 15 most recent publications (2025-2024) reveal a focus on medical diagnostics (e.g., monkeypox, breast cancer), smart infrastructure (e.g., sensor placement, structural health monitoring), and social media analytics for health and behavioral insights. These works leverage machine learning , fuzzy systems , and multi-objective optimization .

• Speech Technology
• Machine Learning
• Signal Processing
• +۳ مورد دیگر

Shashi Kumar is a doctoral student in the Doctoral Program in Electrical Engineering (EDDEE) at École Polytechnique Fédérale de Lausanne (EPFL) , affiliated with the School of Engineering (STI) and the IDIAP Research Institute (LIDIAP) . He holds the role of Doctoral Assistant at LIDIAP, contributing to research in speech technology and machine learning. His work focuses on advancing automatic speech recognition (ASR), optimal transport frameworks, and variational autoencoders for speech enhancement and signal processing. Research interests include speech recognition systems , multimodal task unification , far-field speech processing , and machine learning applications in signal processing and computer vision. His publications highlight contributions to SLAM-ASR performance analysis, joint speaker change detection, and PCB defect classification using image segmentation techniques. Shashi's research is anchored at the IDIAP Research Institute , where he collaborates on projects involving deep learning, audio signal processing, and speech technology. While no awards or grants are explicitly listed, his work reflects active engagement in international challenges like the Interspeech DiCOVA competition.

Nigel Boschمشاهده پروفایل

استادیار

• Machine Learning
• Human-Computer Interaction
• Educational Technology
• +۳ مورد دیگر

Nigel Bosch is an Assistant Professor in the School of Information Sciences (iSchool) at the University of Illinois Urbana-Champaign, with a joint appointment in the Department of Educational Psychology. He is also a faculty affiliate at the National Center for Supercomputing Applications (NCSA) and Illinois Informatics. His primary research focuses on machine learning and human-computer interaction applications in education, with particular emphasis on affective computing, metacognition, and online learning environments. Bosch holds a PhD in Computer Science from the University of Notre Dame, followed by a postdoctoral research position at the National Center for Supercomputing Applications. His research explores machine learning applications in education, including automatic emotion measurement in programming education, metacognition analysis through natural language processing, and ethical implications of AI in learning. He also investigates wearable technologies for health monitoring and algorithmic bias mitigation in educational data. Bosch’s work is supported by grants from the National Science Foundation (NSF), the Institute of Education Sciences (IES), and the University of Illinois. He leads the (Human + Machine) Learning lab, which develops innovative technologies for educational analytics, AI ethics, and human-centered computing.