جستجوی استاد راهنمای دانشگاهی

• Metacognition AI
• Reinforcement Learning
• Robotics
• +۳ مورد دیگر

An Nguyen An Nguyen is a Researcher in the Department of Computer Science at the University of Oxford. Their work focuses on advancing AI systems through metacognition principles, reinforcement learning, and robotics applications. Key research themes include human-AI collaboration in robotic teleoperation, decision-making frameworks, and spatiotemporal task coordination. Nguyen's recent studies explore confidence calibration mechanisms in joint human-AI systems and their implications for autonomous decision support. Research interests span: Metacognition AI architectures for self-aware systems Reinforcement learning in dynamic environments Robotic teleoperation interfaces Human-robot trust dynamics Publications from 2020-2025 reflect a progression from transportation modeling to cutting-edge AI-robotics integration. Work combines unsupervised learning techniques with real-world robotics applications, demonstrating expertise in both theoretical and applied computer science domains.

Siddhartha Dattaمشاهده پروفایل

پژوهشگر ارشد

• Distributed Machine Learning
• Model Adaptation
• Cybersecurity
• +۴ مورد دیگر

Siddhartha Datta is a Researcher at the University of Oxford's Department of Computer Science, specializing in distributed machine learning and adaptive systems. His research develops end-to-end solutions for model training, security, and deployment. Key research areas include: Adaptive learning algorithms for dynamic environments Defense mechanisms against adversarial attacks Human-centered AI interfaces and tools Cross-reality systems blending digital/physical spaces Efficient model compression techniques Current projects investigate prompt engineering for generative models, online learning under data drift, and 3D object detection refinement. His work combines theoretical frameworks with practical implementations, resulting in tools like GreaseTerminator for digital sovereignty and DeepObfusCode for source protection. Datta has collaborated with Google and Cornell University during his doctoral studies. His open-source contributions include neurocogpy (ECoG processing) and Polysemy Word Tagging Tool, demonstrating commitment to accessible research tools.

• Machine Learning
• Optimization Algorithms
• Deep Learning
• +۷ مورد دیگر

Bin Gu is a professor at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), specializing in machine learning and artificial intelligence. Previously affiliated with institutions including Nanjing University of Information Science and Technology (former position) and Nanjing University of Aeronautics and Astronautics (PhD 2011). His research focuses on optimization algorithms, spiking neural networks, federated learning, kernel methods, adversarial robustness, and neuromorphic computing. Education: PhD in Computer Science (2011) from Nanjing University of Aeronautics and Astronautics. Prior affiliations include Tianjin University, Boston University, University of Science and Technology of China, and Southeast University. Research Interests: Extensive work on machine learning theory and applications, including robust learning, federated systems, neural architecture design, and privacy-preserving techniques. Over 200 publications in top venues such as AAAI, NeurIPS, ICLR, ICML, KDD, and IEEE journals. Publications Trends: Recent focus on spiking neural networks (SNNs), federated learning frameworks, and optimization methods for handling adversarial attacks and privacy constraints. Notable contributions include scalable algorithms for kernel-based learning, robust SVM formulations, and neuromorphic computing architectures. Labs/Teams: Active in AI research groups focused on neural networks, optimization, and distributed learning systems. Collaborates with industry and academic partners on applied AI solutions.

Vijayan Sugumaranمشاهده پروفایل

استاد

• Big Data Management
• Data Science
• Intelligent Agents
• +۵ مورد دیگر

Vijayan Sugumaran is a Distinguished Professor of Management Information Systems at Oakland University's School of Business Administration. He chairs the Department of Decision and Information Sciences and co-directs the Institute for Data Science. He holds a Ph.D. in Information Technology from George Mason University (Virginia, USA). His research focuses on Big Data Analytics, Intelligent Agents, and Semantic Web technologies. He leads a $2M NSF grant for STEM-driven data science training and has authored over 350 peer-reviewed articles across journals like Information Systems Research and IEEE Transactions on Big Data . Teaching interests include Advanced Database Systems, Machine Learning, and Predictive Analytics. He has received awards such as the SAS Educator Award (2025), Janke Scholar (2023-2026), and Fulbright Specialist (2012). He serves as editor-in-chief of the International Journal of Intelligent Information Technologies and chairs conference tracks like the Intelligent Agent mini-track at AMCIS. His work bridges academia and industry through collaborations in data science education, smart city infrastructure, and cybersecurity. He advises on analytics programs and has developed frameworks for urban infrastructure resilience using Digital Twins and multi-agent systems. Current projects include blockchain-based participation systems and AI-driven cyberbullying detection.

Giovanni Paoliniمشاهده پروفایل

دانشیار

• Combinatorics
• Topology
• Group Theory
• +۳ مورد دیگر

Giovanni Paolini is an Associate Professor of Mathematics at the University of Bologna (Italy) since 2023. Previously, he worked as an Applied Scientist/Senior Applied Scientist at Amazon Web Services and Caltech (2019–2023), and held a postdoctoral position at the University of Fribourg (2019). He earned his PhD in Mathematics from Scuola Normale Superiore (Pisa, Italy) in 2019, under Prof. Mario Salvetti, with a thesis on topology and combinatorics of affine reflection arrangements. His research spans combinatorics, topology, group theory , and machine learning (deep learning and NLP). Notable contributions include resolving the K(π,1) conjecture for affine Artin groups and developing AI for strategic games like 7 Wonders Duel. He organizes events such as MATH-MIND: Mathematics-Industry Networking Days (2025) and has participated in workshops like Artin Groups and Arrangements at MSRI (2024). Teaching roles include courses on geometry, combinatorial topology, and machine learning at the University of Bologna. His work bridges pure mathematics and applied AI, with publications in journals like Inventiones Mathematicae and conferences like ICLR and ICML. Collaborations include projects with Stefano Soatto (UCLA), Mario Salvetti, and interdisciplinary teams at Amazon.

Kernan Freireمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Manufacturing Systems
• Human-Computer Interaction
• +۳ مورد دیگر

Dr. Kernan Freire is a Researcher in the Faculty of Industrial Design Engineering at Delft University of Technology, specializing in Sustainable Design Engineering and Internet of Things (IoT). His work focuses on integrating Artificial Intelligence (AI) and Large Language Models (LLMs) into manufacturing systems to enhance knowledge sharing and operational efficiency. He leads projects like COALA (COgnitive Assisted agile manufacturing for a LAbour force supported by trustworthy Artificial Intelligence) and SAM|XL , which address challenges in AI adoption across industries. Freire holds an MSc and an Ir. (engineer) degree. His research emphasizes human factors in AI systems, including conversational assistants and cognitive tools for factory operators. He explores how LLMs can improve workplace communication, reduce risks, and optimize processes. Recent studies analyze user perspectives on AI assistants, system transparency, and ethical implications of AI integration in socio-technical systems. Key contributions include developing LLM-powered cognitive assistants for knowledge sharing, evaluating conversational AI in healthcare and manufacturing, and safeguarding data integrity against AI-based attacks. His work bridges technical innovation with human-centered design principles.

Michael Laudenbachمشاهده پروفایل

استادیار

• Teaching Writing in Disciplines
• Computational Linguistics
• Corpus Analysis
• +۳ مورد دیگر

Michael Laudenbach is an Assistant Professor in the Department of Humanities & Social Sciences at New Jersey Institute of Technology (NJIT). His research focuses on integrating evidence-based methods to teach writing in disciplines like statistics and data science, using computational linguistics and corpus analysis to inform pedagogical strategies. He has collaborated with engineering and statistics faculty to develop writing interventions and refine curriculum materials. His work includes pioneering corpus analysis of student and professional writing in statistics, leading to revised assignment prompts and grading rubrics. Recently, he has studied stylistic differences between human writing and outputs from Large Language Models (LLMs), contributing to critical evaluations of LLM applications in academia and industry. Education: M.A. in English, The College of New Jersey, 2018 B.A. in Philosophy & English, The College of New Jersey, 2017 Dr. Laudenbach’s teaching emphasizes transferable communication skills for technical fields, including presentation design and collaborative writing. He has provided writing support for undergraduate and graduate engineering courses through in-class workshops and lesson plans. His theoretical framework in rhetorical genre studies allows him to adapt writing instruction across disciplines and student levels. No specific grants or lab affiliations are mentioned in the provided text.

• Artificial Intelligence
• Procedural Content Generation
• Game Design
• +۵ مورد دیگر

Amy Hoover is an Assistant Professor in the Informatics department at New Jersey Institute of Technology (NJIT). Her research focuses on artificial intelligence, procedural content generation, and the intersection of AI with creative domains such as music composition and video game design. She explores topics like evolutionary algorithms, open-ended learning systems, and ethical considerations in AI applications. Her work spans contributions to procedural content generation (PCG) in games, including automated deckbuilding for Hearthstone and generative level design. She also investigates peer learning dynamics in AI systems and the application of large language models (LLMs) for creative tasks. Hoover’s research often bridges computational methods with human-centric design, such as curriculum development in AI education and fostering creativity through interactive tools. Her publications reflect collaborations in AI-driven game design, music composition, and educational technology. Media coverage highlights her work on ethical risks in mixed-reality gaming and AI’s role in mental health support through gaming communities. Notable contributions include frameworks like Watts for open-ended learning, ensemble learning methodologies inspired by human collaboration, and studies on transfer dynamics in evolutionary curricula. Her work emphasizes practical applications of AI in both technical and creative fields.

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Anh Nguyen-Duc is a researcher affiliated with the University of South-Eastern Norway (School of Business) and Norwegian University of Science and Technology , focusing on Software Engineering , Artificial Intelligence , and Startup Research . His work bridges technical and entrepreneurial aspects of software development. University of South-Eastern Norway, School of Business Norwegian University of Science and Technology Research Themes : Software startups, AI integration in development, agile practices, technical debt, and requirements engineering. Recent studies include fairness in educational machine learning models and generative AI adoption in software organizations. Collaborative work with Pekka Abrahamsson, Xiaofeng Wang, and Kai-Kristian Kemell. Key Trends : 2025 studies on AI fairness and generative AI in software processes; 2024 work on hybrid work impacts; 2023 research on startup AI tools and education. Advising & Grants : Collaborates with academic institutions and industry partners on empirical studies about software development practices.

• Business Process Management
• Process Mining
• Artificial Intelligence
• +۳ مورد دیگر

Henrik Leopold is a Professor affiliated with Kühne Logistics University and Hasso Plattner Institute. His research focuses on Business Process Management (BPM), Process Mining, and the application of AI technologies like Large Language Models (LLMs) in process automation. He has co-authored over 138 publications, including impactful works on process mining in supply chains, robotic process automation effects, and explainable anomaly detection in event logs. Key research interests include: Process Mining & Business Process Optimization AI-driven Process Automation Process Model Matching & Compliance Checking Natural Language Processing in BPM Process Analytics & Data-Driven Decision-Making Recent work emphasizes interdisciplinary approaches combining process mining with LLMs for tasks like event log extraction and prompt engineering. He actively contributes to BPM conferences such as BPM, CAiSE, and HICSS, often serving as program committee member. His research addresses both technical challenges (e.g., anomaly detection) and organizational aspects (e.g., process automation adoption barriers). Notable contributions include development of Sketch2Process for BPMN sketch recognition and foundational work on process model validation. Current activities explore future directions in BPM through collaborative ranking of research challenges and benchmarking LLM capabilities for process tasks.

Gina M. Londino-Smolarمشاهده پروفایل

استاد آموزشی

• Forensic Science Education
• Online Learning
• Science Education
• +۵ مورد دیگر

Gina M. Londino-Smolar serves as a Teaching Professor and Director of the Forensic & Investigative Sciences (FIS) Program in the Department of Chemistry and Chemical Biology at Indiana University's School of Science. She also holds the position of Director of Programs and Services for FACET (Faculty Academy on Excellence in Teaching). With extensive experience in forensic science education and online learning, Dr. Londino-Smolar has made significant contributions to science education methodology and academic integrity initiatives. Education: Ed.D. in Curriculum and Instruction in Science Education, Indiana University, Bloomington (2024) M.S. in Analytical Chemistry, Purdue University, Indianapolis (2006) B.S. in Chemistry, Ball State University, Muncie (2004) Dr. Londino-Smolar's research focuses on innovative approaches to science education, particularly in forensic science. Her work emphasizes online learning environments, virtual laboratories, and strategies to enhance student engagement and academic integrity. She has pioneered methods for creating accessible and interactive online forensic science courses that maintain rigorous educational standards while adapting to digital formats. Her research on social belonging in online science courses addresses critical challenges in remote education. Analysis of Dr. Londino-Smolar's publications reveals a consistent focus on educational innovation in forensic science. Her work spans from foundational research on academic integrity to cutting-edge applications of AI in forensic education. A notable trend is her progression from developing basic online forensic science courses to implementing advanced technologies like AI prompt engineering to enhance educational experiences. Her research consistently bridges theoretical educational frameworks with practical classroom applications. Scientific Awards: Indiana University President's Award for Excellence in Teaching and Learning Technology (2025) School of Science Full-time Lecturer Service Award (2021) Faculty Academy on Excellence in Teaching (FACET) member since 2019 School of Science Trustees' Teaching Award (2018) IUPUI Favorite Professor (2009, 2010, 2013, 2023, 2024, 2025) Dr. Londino-Smolar has secured substantial grant funding supporting educational technology in forensic science, including multiple awards for acquiring specialized equipment such as digital cameras, microscopes, and analytical instruments. Her grant portfolio demonstrates a strategic approach to building comprehensive educational resources that support both teaching and research objectives within the Forensic & Investigative Sciences Program. These resources have enabled the development of state-of-the-art virtual and physical laboratory experiences for students. As Director of the Forensic & Investigative Sciences Program, Dr. Londino-Smolar has built a cohesive academic team focused on innovative forensic science education. Her leadership in developing the online forensic science curriculum has established Indiana University as a leader in digital forensic education. Through FACET, she contributes to broader educational excellence across the university, sharing her expertise in online and technology-enhanced teaching with colleagues across disciplines.

• Learning Analytics
• Educational Technology
• Artificial Intelligence in Education
• +۳ مورد دیگر

Rafael Ferreira Leite de Mello is an academic affiliated with the Federal Rural University of Pernambuco in Brazil. His research focuses on Learning Analytics, Educational Technology, and Artificial Intelligence applications in education. He has contributed to the development of AI-driven tools for automated feedback, essay scoring, and equity in educational systems. His work often addresses challenges in under-resourced regions and emphasizes explainable AI, fairness, and human-AI collaboration. Dr. Mello has co-authored numerous publications in top-tier conferences like AIED, EC-TEL, and LAK, and has edited conference proceedings (e.g., EC-TEL 2024). His research spans topics such as automated essay evaluation, rhetorical structure analysis, and the impact of generative AI on educational practices. He collaborates extensively with institutions globally, advocating for inclusive technology solutions in education. His efforts include designing systems like MathAIde for underserved regions and frameworks like MMALA to guide Learning Analytics adoption in institutions. He actively engages in initiatives to bridge the digital divide and improve accessibility through technology.

• Human-Computer Interaction
• Gesture Recognition
• Child-Computer Interaction
• +۵ مورد دیگر

Lisa Anthony is a Professor affiliated with the University of Florida, specializing in Human-Computer Interaction (HCI) with a strong focus on gesture recognition, touchscreen interfaces, and child-computer interaction. Her research emphasizes the design of user-centered technologies for diverse populations, including children, older adults, and individuals with disabilities. Key contributions include studies on children's touchscreen interaction patterns, multimodal authentication systems, and mHealth applications for behavior change. Her work spans over two decades, with publications in top-tier venues such as CHI, ICMI, and IEEE Transactions. Notable projects include the MTAGIC initiative exploring child motion characteristics, the design of MyTrack+ for weight management, and studies on spherical interfaces. She collaborates extensively with researchers in computer science, education, and healthcare to address real-world challenges in technology accessibility and usability. Lisa's research has implications for improving educational tools, healthcare apps, and collaborative learning environments. While no grants or awards are explicitly listed, her prolific publication record underscores her sustained contributions to HCI and related fields.

• Bioinformatics
• Artificial Intelligence
• Computer Science
• +۳ مورد دیگر

Jie Hao is a researcher at the Information Security Center of Beijing University of Posts and Telecommunications , with a focus on interdisciplinary applications spanning Bioinformatics , Artificial Intelligence , and Medical Informatics . His work bridges computational methods with real-world challenges in healthcare, ecology, and network optimization. Recent publications highlight his contributions to Single-cell RNA sequencing deconvolution (2025) AI-driven intergenerational communication in VR (2025) Digital health applications for COPD management (2025) Deep reinforcement learning for vehicle routing (2025) His methodological innovations include adaptive attention mechanisms for object detection (2025), memory-efficient DNN accelerators (2025), and bilevel optimization algorithms with unbounded smoothness (2024). Collaborations span institutions like University of Melbourne and Chinese Academy of Sciences , reflecting his cross-disciplinary impact.

• Agile Methodologies
• Software Engineering
• DevOps
• +۳ مورد دیگر

Prof. Martin Kropp is a Lecturer for Software Engineering and Programme Manager for the CAS Agile Organisation at FHNW University of Applied Sciences and Arts Northwestern Switzerland, within the School of Computer Science and FHNW Institute of Mobile and Distributed Systems. His research focuses on Agile Methodologies, Tool-supported Agile Collaboration, and Automated Software Construction/Testing. He actively contributes to the Swiss Agile Research Network (SARN) and Swiss Agile Study initiatives. Teaching responsibilities include courses on Software Construction, Testing & Quality Management, and .Net Framework/C# for the Bachelor of Computer Science, as well as the Master of Science in Engineering (MSE) in Software Engineering and Architecture. He has published extensively on Agile practices, DevOps metrics, and collaborative tools like aWall, emphasizing empirical studies and practical applications. Key research themes include Agile team dynamics, leadership in software development, and the integration of AI in testing and DevOps. His work bridges academic research and industrial practice, with notable contributions to conferences like ICSE, XP, and CHASE.