جستجوی استاد راهنمای دانشگاهی

Zihao Fuمشاهده پروفایل

مدرس

• Natural Language Processing
• Large Language Models
• Text Generation
• +۵ مورد دیگر

Zihao Fu is an Affiliated Lecturer at the University of Cambridge within the Faculty of Modern and Medieval Languages and Linguistics, specifically at the Language Technology Lab. He also serves as a Research Assistant Professor at The Chinese University of Hong Kong (CUHK). His research spans Natural Language Processing , Large Language Models , and Biomedical Applications with a focus on Parameter-Efficient Fine-Tuning and Algorithmic Fairness . Previously, he was a Postdoctoral Researcher at both University of Cambridge (2021-2024) and University of Oxford (2024-present). Dr. Fu's academic background includes a Ph.D. in Systems Engineering from The Chinese University of Hong Kong (2017-2021), followed by postdoctoral training at Cambridge and Oxford. His technical expertise integrates Computational Linguistics , Machine Learning , and Algorithmic Fairness to address challenges in Biomedical Named Entity Recognition and Knowledge Base-to-Text Generation . His recent publications (2020-2025) demonstrate a trajectory from foundational work in Text Generation and KB-to-Text Systems to cutting-edge research in Biomedical LLMs and Algorithmic Fairness Toolkits . Notable contributions include the BAND Biomedical Alert Dataset (AAAI 2024) and theoretical studies on LLM Watermarking and Parameter Stability . While no scientific awards are explicitly listed, his service as a Reviewer for top conferences (AAAI, ACL, NeurIPS) indicates field recognition. As an educator, he has taught courses like Computational Linguistics at Cambridge (2022-2023) and Advanced Financial Infrastructure at CUHK. His technical projects include open-source tools like StreamTask (parallel processing framework) and CSTL (C++ STL wrapper for Python), reflecting practical implementation skills alongside theoretical contributions.

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۶ مورد دیگر

Vivek Gupta is an incoming Assistant Professor at the School of Computing and Augmented Intelligence , Arizona State University (ASU), starting Fall 2024. Previously, he served as a Postdoctoral Researcher at the University of Pennsylvania's Cognitive Computation Group , and as a Research Fellow at Microsoft Research India . His academic journey includes a Ph.D. in Computer Science from the Kahlert School of Computing, University of Utah (advisor: Prof. Vivek Srikumar), supported by the Bloomberg Data Science Fellowship, and an MTech/BTech Dual Degree from IIT Kanpur . Dr. Gupta's research focuses on Natural Language Processing for semi-structured data , particularly tables, flowcharts, and maps. His work addresses trustworthy AI systems , multilingual tabular inference , and knowledge integration in low-resource environments. Current projects explore temporal reasoning , multimodal table analysis , and neurosymbolic agents for complex data. Recent publications examine adaptive prompting for temporal table reasoning , flowchart attribution , and multimodal benchmarking . His MMTBENCH and TabXEval frameworks evaluate robustness and quality standards in table processing. Recruitments highlight his CORAL Lab seeking candidates for Trustworthy AI projects. Bloomberg Data Science Fellowship (2021-2023) Ericsson Innovation Award (2016) Best Paper, DeeLIO-2022 Outstanding Paper, NLP4ConvAI-2022 As a mentor, Dr. Gupta has guided 30+ students across institutions including ASU, University of Utah, IIT Kanpur, and UPenn. His professional service includes organizing NAACL Student Research Workshops , serving as iKDD Student Ninja , and coordinating the University of Utah Data Science Club . Contact: vgupt140@asu.edu , keviv9@gmail.com

Nedjma Djouhra Ousidhoumمشاهده پروفایل

مدرس

• Natural Language Processing (NLP)
• Computational Social Science
• Automated Fact-Checking
• +۵ مورد دیگر

Nedjma Djouhra Ousidhoum is a Lecturer at the School of Computer Science and Informatics, Cardiff University, and a Visiting Academic at University of Cambridge. She leads the Cardiff NLP Group and focuses on Natural Language Processing and Computational Social Science. Cardiff University (2021–present) University of Cambridge (2021–2025) Hong Kong University of Science and Technology (PhD, 2014–2021) Her research explores NLP for low-resource languages , automated fact-checking , and toxic content detection , with recent work on emotion recognition datasets across 28 languages (ACL 2025 Best Resource Paper) and creating benchmarks for culturally grounded NLP (NAACL 2025 Best Theme Paper). Selected publications demonstrate her impact in multilingual dataset creation and cross-cultural NLP : BRIGHTER (ACL 2025): Best Resource Paper for emotion datasets across 28 languages WorldCuisines (NAACL 2025): Best Theme Paper for multicultural visual question answering AfriHate (NAACL 2025): Multilingual hate speech datasets for African languages Awarded Best Task Description Paper at SemEval 2025 and Outstanding Senior Area Chair at EMNLP 2023, she actively contributes to NLP community through workshop organization and program committee roles.

Abdelkader Oudaمشاهده پروفایل

دانشیار

• Information Security
• Cryptography
• Network Security
• +۹ مورد دیگر

Dr. Abdelkader Ouda is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Western Ontario, with over three decades of experience in academia and the software industry. He holds a Ph.D. in Computer Science from Western University (2005), an M.Sc. in Computer Science and Pure Mathematics from Ain Shams University (1993), and a B.Sc. (Hons) in the same disciplines from Ain Shams University (1986), graduating with the highest honor (96.80%). His research spans information security, cryptography, network security, big data security and privacy, and data analytics . He leads the Information and Computer Networks Security (iCNS) Research Laboratory, focusing on innovative solutions for IoT, fog–cloud computing, and behavioral biometrics. His recent work includes developing the ADG Engine for synthetic data generation and HSM4SSL for intra-domain security. Dr. Ouda’s publications highlight advancements in authentication protocols, lightweight IoT security frameworks, database benchmarking, and machine translation . His industry experience includes 14 years in software development, project management, and system analysis, which he integrates into his teaching of courses like Software Design, Algorithms & Data Structures, and Information Security. He also contributes to engineering accreditation through the CEAMS application. Key trends in his articles include secure communication in hybrid architectures, energy-efficient IoT protocols, and reinforcement learning for continuous authentication . His work bridges academic theory with practical applications, emphasizing efficiency and scalability in modern computing environments.

• Distributed Systems
• Blockchain Technology
• Middleware Integration
• +۴ مورد دیگر

Julian Kalinowski is a researcher at the University of Hamburg's Department of Computer Science within the Faculty of Mathematics, Informatics, and Natural Sciences (MIN). His work focuses on distributed systems, blockchain technology, and middleware integration for mobile environments. Key projects include Jadex BDI Agent System and the cadeia initiative for distributed code execution in information markets. PhD candidate in Computer Science Email: kalinowski@informatik.uni-hamburg.de Room F510, Office hours by appointment Research interests span decentralized information markets, blockchain compliance (e.g., GDPR), and mobile middleware optimization. His 2015 best paper award at MATES conference highlights contributions to agent platform customization. Publications from 2012-2020 reveal trends in blockchain applications, smart grid optimization, and IoT security. Supervised 9 student theses covering decentralized billing, smart home systems, and localization technologies. Key awards: Best Paper Award (MATES-2015).

Joshua Oehmsمشاهده پروفایل

پژوهشگر

• Information Retrieval
• Conversational Systems
• NLP for Healthcare Applications
• +۱ مورد دیگر

Joshua Oehms is a Researcher at the Technical University of Munich (TUM) within the School of Computation, Information and Technology, specifically in the Department of Computer Science (I19 Software Engineering for Business Information Systems). He joined sebis in July 2024 and focuses on Natural Language Processing (NLP) applications in healthcare, conversational systems, and low-resource NLP tasks. B.Sc. and M.Sc. in Games Engineering from TUM Research expertise in text simplification and NLP for healthcare Teaching role as lecture organizer for "Software Engineering for Business Applications" (WS 24/25, Bachelor level) His recent work addresses challenges in German text simplification through style-specific pre-training of language models, targeting scenarios with limited parallel data. He collaborates with external partners like MRI (Medical Research Institute) on automating medical literature screening processes. Key technical skills include PyTorch/Keras, transformer models, and traditional information retrieval systems. Joshua actively supervises student thesis projects focusing on AI applications in healthcare contexts.

Michael Mahoneyمشاهده پروفایل

استاد

• Randomized Numerical Linear Algebra
• Machine Learning
• High Dimensional Statistics
• +۳ مورد دیگر

Michael Mahoney is Professor of Statistics at the University of California, Berkeley, with additional affiliations at the International Computer Science Institute (ICSI) where he is Vice President and Director of the Big Data Group, the Lawrence Berkeley National Laboratory (LBNL) where he leads the Machine Learning and Analytics Group, and the EECS department's RISELab. He is also an Amazon Scholar. Education: While specific degrees are not listed in the provided text, his extensive record of teaching, research leadership, and publications indicates doctoral-level training in Statistics and Computer Science. Research Interests: Mahoney's work centers on the applied mathematics of data , spanning algorithmic and statistical foundations of big data, randomized numerical linear algebra (RandNLA), high-dimensional statistics, machine learning, and scientific machine learning. He develops theory, scalable implementations, and real-world applications in internet analytics, social networks, genetics, astronomy, and climate science. Recent software contributions include the RandBLAS and RandLAPACK libraries (standardizing RandNLA routines), Landscaper for visualizing deep-learning loss landscapes, and packages such as FreeAlg , DetKit , Imate , and LeaderBot . Awards & Honors: NeurIPS 2020 Best Paper Award (co-authored work on column subset selection) Director, NSF TRIPODS UC Berkeley FODA Institute Key contributor to the BALLISTIC project for next-generation BLAS/LAPACK Grants & Leadership: Principal Investigator, NSF TRIPODS FODA Institute (Foundations of Data Analysis) Group Lead, Machine Learning and Analytics, LBNL Vice President & Director, Big Data Group, ICSI Advising & Mentoring: Mahoney has an extensive network of current and former PhD students, postdocs, and visiting researchers, including placements at MIT, Stanford, Waterloo, Stevens, Tsinghua, and Georgia Tech. Current advisees include Shengaho Yang, Zhichao Wang, Hyunsuk Kim, and Pu Ren, among many others. Labs & Teams: He directs research efforts across UC Berkeley Statistics, ICSI’s Big Data Group, LBNL’s Machine Learning and Analytics Group, and the RISELab (formerly AMPLab), fostering cross-disciplinary collaboration between statistics, computer science, and domain sciences.

Cristian A. Galvis Florezمشاهده پروفایل

پژوهشگر

• Quantum Machine Learning
• Quantum Algorithms
• Quantum State Tomography
• +۷ مورد دیگر

Cristian A. Galvis Florez is a doctoral researcher at Aalto University's School of Electrical Engineering, supervised by Professor Simo Särkkä. As part of the QuantLearn project funded by the Research Council of Finland, he explores quantum machine learning algorithms with applications in computational science. His academic journey spans Colombia, Oxford, and Finland, bridging quantum mechanics and machine learning. Education: Master’s in quantum computing, PhD ongoing at Aalto University Research Focus: Quantum state tomography, Gaussian process algorithms, and NISQ device optimization His work integrates quantum computing with machine learning , emphasizing probabilistic modeling and quantum hardware implementation . Recent publications highlight advancements in quantum-assisted regression and state estimation techniques . The QuantLearn project underpins his research, developing algorithms with potential to revolutionize computational domains. His publications demonstrate cross-disciplinary expertise in quantum theory and statistical modeling , leveraging low-rank Gaussian processes for quantum applications.

• Energy Efficiency
• Sustainable Transportation
• Data Center Management
• +۴ مورد دیگر

Jukka Nurminen serves as an Adjunct Professor and Visitor within Aalto University's Department of Computer Science, maintaining active affiliation with the Myllymäki Petri research group at the Helsinki Institute for Information Technology (HIIT). His institutional presence bridges theoretical computer science and sustainability applications through cross-disciplinary collaborations. Research focuses span three critical domains: energy-efficient computing systems (data centers, distributed networks), sustainable urban mobility via smartphone data analytics, and AI ethics in educational contexts. His work consistently translates computational frameworks into real-world sustainability solutions, such as developing smartphone-based tools for low-carbon travel optimization and energy-aware data center management. Recent publications (2025) reveal emerging expertise in quantum algorithm measurement techniques and LLM ethics assessment, building on established contributions in sustainable transportation (2020) and green computing (2018-2019). This trajectory demonstrates continuous adaptation to computational frontiers while maintaining core sustainability objectives. No scientific awards are documented in available sources, though his work appears in premier venues including IEEE Quantum Software, ACM Transactions, and Sustainability journals. As an Adjunct Professor, he likely engages in graduate supervision within Aalto's Computer Science department, with research supported by institutional resources at HIIT and Aalto. Collaborative patterns indicate international partnerships, particularly with CERN in green computing initiatives and transportation researchers in sustainable mobility projects. His affiliation with the Myllymäki Petri group provides access to HIIT's machine learning infrastructure and cross-institutional researcher network, facilitating the data-intensive approaches central to his transportation and energy studies.

• Machine Translation
• Multilingual NLP
• Bias and Fairness in NLP
• +۶ مورد دیگر

Christian Hardmeier is an Associate Professor in Data Science at the IT University of Copenhagen, specializing in Natural Language Processing (NLP) and computational linguistics. His research spans machine translation, multilingual NLP, bias and fairness, coreference resolution, and discourse analysis. Key research areas include: Cross-lingual pronoun prediction and anaphora resolution Discourse structure in multilingual contexts Ethical considerations in NLP (dehumanizing language, bias statements) Low-resource language processing and dataset creation Evidential deep learning for uncertainty estimation His recent publications focus on Egyptian Arabic discourse relations, uncertainty modeling, and biomedical translation. He contributes to community efforts through the Pioneer Centre for Artificial Intelligence and SafeNet initiatives. Notable recognition includes an Outstanding Paper Award at the ML Evaluation Standards Workshop 2022. He actively participates in assessment committees and NLP community-building activities.

• Artificial Intelligence
• Machine Learning
• Big Data
• +۷ مورد دیگر

Salvatore Mario Carta is Full Professor at the Department of Mathematics and Computer Science of the University of Cagliari. He founded the Artificial Intelligence and Big Data Laboratory and co-founded 4 hi-tech companies. His research spans multiple AI applications including large language models, financial forecasting, road safety, and health informatics. PhD in Electronics and Computer Science (2003, University of Cagliari) Assistant Professor (2005–2014) Associate Professor (2014–2021) Full Professor (2021–present) His research focuses on Artificial Intelligence, including Large Language Models for knowledge representation, AI Algorithms for smart mobility and financial forecasting, Clustering Algorithms for behavioral pattern analysis, and E-coaching Platforms for health applications. Recent work explores Knowledge Graph Engineering , Monocular 3D Object Detection , and Zero-Shot Learning in urban systems. Scientific output trends include Smart Cities (2024), Knowledge Graphs (2024), Medical Imaging (2024), and Financial AI (2024). His 15 most recent articles (2025–2024) emphasize Deep Learning for security, GAN for biometrics, and Generative Models for language preservation. As lab director and founder of spin-offs like The Cloud Alchemist Srl and Visioscientiae Srl, he bridges academic research and industrial innovation. Current affiliations include ACM membership, with past responsibilities as Local Unit Responsible for CINI.

Charles Yangمشاهده پروفایل

استاد

• Linguistics
• Cognitive Science
• Computational Linguistics
• +۵ مورد دیگر

Charles Yang is a Professor at the University of Pennsylvania's Department of Linguistics, with joint appointments in Computer and Information Science and Psychology. As Chair of Linguistics and Director of the Program in Cognitive Science since 2011, he co-directs the Integrated Language Science and Technology group with John Trueswell. PhD in Computer Science, MIT AI Lab Faculty at Yale (2000-2008) Current roles: Chair of Linguistics, Director of Cognitive Science Program His research bridges linguistics, cognitive science, and computational modeling, focusing on human and machine language acquisition, phonological and morphological learning, and computational modeling of historical language change. He develops the Tolerance Principle for quantifying language acquisition thresholds and investigates neural language models as cognitive theories. Recent publications analyze language acquisition through computational models (2021-2024), with the 2025 work evaluating LLMs for low-resource languages. His 2016 book The Price of Linguistic Productivity won the Leonard Bloomfield Award and explores productivity in language systems. Guggenheim Fellowship (2018) Bloomfield Book Award (2018) NSF GRFP Fellowship Leonard Bloomfield Book Award (2016) Yang advises students in language acquisition, computational linguistics, and cognitive modeling. His lab collaborates with researchers like Bob Berwick, Johan Bolhuis, and Noam Chomsky on integrated approaches to language science.

• Human-Centered AI
• Speech Processing
• Multimodal Fusion
• +۳ مورد دیگر

Dr Andrew Abel is a Lecturer at the Department of Computer and Information Sciences, University of Strathclyde, specializing in Human-Centered AI technologies that enhance educational inclusion and accessibility. His work bridges artificial intelligence with multimodal signal processing to address real-world challenges in speech perception and human-computer interaction. Education : PhD in Computer Science (Speech Processing), University of Stirling (2007-2012) Research Focus : Dr Abel leads the Human-centred AI Technologies for Inclusion in Education and Society project (2023-2027), focusing on AI-driven educational accessibility. He also contributed to AV-COGHEAR (2016-2019), developing cognitively-inspired hearing aid technologies that combine audio-visual inputs for speech enhancement. Publications span affective computing, speech reconstruction, multimodal fusion, and educational technologies. Recent works include valence-arousal prediction systems, lightweight lip-to-speech models, and automated programming assessment frameworks. Awards : Strathclyde Chancellor's Fellowship Collaborations : Dr Abel collaborates across biomedical engineering and computer science domains, with emphasis on explainable AI and sustainable educational technologies aligned with UN SDG4 (Quality Education).

• Computational Linguistics
• Natural Language Processing
• Unsupervised Learning
• +۵ مورد دیگر

Dr. Steffen Remus is a postdoctoral researcher at the University of Hamburg , affiliated with the Department of Informatics and the Language Technology Group (LT) . He holds a Ph.D. in 2023 from the University of Hamburg under Prof. Dr. Chris Biemann and earned his MA in 2012 at Technische Universität Darmstadt. Research Interests : Unsupervised methods, computational linguistics, distributional semantics, information extraction, knowledge induction, and focused web crawling. Projects : JOIN-T2, BIMDANUBE, WebAnno-MM, KDSL, AIPHES. Scientific Awards : KDSL scholarship holder (2017), Best Mentoring award (2015) for Algorithms of Language Technology course. Academic Contributions : Co-lecturer in Research Software Engineering at University of Hamburg (2024), teaching assistant in multiple NLP and software engineering courses since 2014. Supervised over 20 B.A./M.A. theses and independent studies. Active reviewer for major conferences (ACL, EMNLP, AAAI, EACL, COLING) and organizer for GermEval shared tasks.

Andreas Kochمشاهده پروفایل

پژوهشگر

• Computational Modeling
• Compressible Multiphase Flows
• CutDG Methods
• +۳ مورد دیگر

Andreas Koch is a Research Associate at the Professorship of Simulation for Additive Manufacturing at the Technical University of Munich (TUM), Germany. His research focuses on computational modeling of compressible multiphase flows, CutDG methods, and high-performance computing with software development. He holds a Master of Science (M.Sc.) in Mechanical Engineering from TUM (2024). Research Interests Koch's work bridges computational mechanics and machine learning, with emphasis on cut discontinuous Galerkin methods for simulating complex flows and high-performance computing systems. His publications demonstrate expertise in machine learning applications for aerospace systems, including anomaly detection in spacecraft telemetry and deep learning acceleration for spaceborne hardware. Scientific Awards ERC Starting Grant Publications (2024-2013) His research portfolio includes 15 recent publications spanning edge AI solutions for spacecraft , RF synchronization systems, and machine learning frameworks for aerospace applications. Earlier work explores robot perception and geoinformatics implementations.