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Jie DingView profile

Associate Professor

• Artificial Intelligence
• Statistics
• Scientific Computing
• +6 more

Jie Ding is an Associate Professor at the University of Minnesota's School of Statistics with graduate faculty appointments in Electrical Engineering, Computer Science, and the Data Science Program. He serves as a core faculty member of the Data Science and AI Hub and holds an Amazon Scholar position with the Amazon AGI Team focusing on foundation model training. His educational background includes a Ph.D. in Engineering Sciences from Harvard University (2017), postdoctoral work at Duke University (2018), and a B.S. from Tsinghua University where he participated in both the Math & Physics Academic Talent Program and Electrical Engineering program. Ding's research sits at the intersection of artificial intelligence, statistics, and scientific computing, with focus areas including Agentic AI for autonomous data science workflows, AI Foundations for interpretability and trustworthiness, Scalable Modeling for broader AI accessibility, Decentralized and Collaborative AI systems, and AI Safety addressing privacy and security concerns. He developed the STAT 8931 Generative AI course with open-source materials available at genai-course.jding.org . His recent publications demonstrate strong activity across multiple AI subfields, particularly in value alignment (MAP framework), AI safety mechanisms, federated learning innovations, and statistical foundations for modern AI systems. The breadth of venues (ICML, ICLR, NeurIPS) indicates significant impact across the AI research community. NSF CAREER Award (2024) Army Early Career Program (Young Investigator) Award (2023) Cisco Research Award (2022-25) AWS Cloud Credits for Research (2021-22) Meta/Facebook Faculty Research Award (2021-22) UMN Thank-A-Teacher Teaching Award (2019-20) Ding leads the Agentic AI for Data Science Benchmark initiative, collaborating with University of Minnesota colleagues and Minnesota industry partners to evaluate AI agent capabilities across healthcare, insurance, retail, energy and other sectors. His research group actively recruits PhD students interested in AI/Statistics intersections, with focus on developing theoretically grounded yet practically impactful AI systems.

• Distance Education
• Online Learning
• Educational Technology
• +7 more

Aras Bozkurt is a faculty member and researcher at Anadolu University's Open Education Faculty in Türkiye, holding a PhD in Distance Education. His work focuses on empirical studies in distance education, online learning, educational technology, and AI integration in education through critical theories like connectivism, rhizomatic learning, and heutagogy. He employs emerging methodologies including social network analysis and sentiment analysis, with a particular emphasis on the implications of generative AI and human-machine interaction. Editorial Leadership : Editor-in-Chief of Open Praxis and Asian Journal of Distance Education, Associate Editor for journals including Higher Education Research and Development and Online Learning Research Contributions : Over 250 Web of Science publications, h-index of 60 on Google Scholar, 47 funded projects, and 7 thesis advisories Bozkurt's research explores critical educational paradigms, with recent publications analyzing generative AI's impact on academic integrity, OER transparency, and the sustainability of open universities. His work bridges theoretical frameworks with practical applications in digital education ecosystems, focusing on ethical AI implementation and algorithmic challenges. Scientific contributions include 15 recent articles (2023-2026) covering generative AI literacy, colonial legacy disruptions in education, AI ethics frameworks through activity theory, and dropout analysis in open distance learning systems. These publications demonstrate a consistent focus on critical AI studies, educational sustainability, and digital transformation.

Olexandr IsayevView profile

Professor

• Machine Learning
• Computational Chemistry
• Drug Discovery
• +7 more

Olexandr Isayev is the Carl and Amy Jones Professor of Chemistry at the Department of Chemistry, Carnegie Mellon University (CMU), within the Mellon College of Science. He holds affiliate roles at the Scott Institute for Energy Innovation and the CMU-Pitt Computational Biology Program. His research focuses on applying artificial intelligence (AI), machine learning (ML), and computational chemistry to solve complex problems in drug discovery, materials science, and quantum mechanics. Notable collaborations include work with the CMU Cloud Lab and the development of the AIMNet2 molecular potential. Education: Postdoctoral Fellow at Case Western Reserve University (2009–2012), PhD in Theoretical Chemistry from Jackson State University (2008), M.S. in Chemistry from Dnepropetrovsk National University (2002). His research interests span generative AI for molecular design, ML-driven chemical intuition, and autonomous experimental platforms. Key achievements include groundbreaking work on universal ML potentials for quantum mechanics and GenAI methods for inverse molecular design. Awards include the Scialog Fellowship (2023) and NVIDIA GPU Computing Award (2014). Future goals aim to advance 'Chemical Intelligence' by integrating AI with expert decision-making frameworks. Awards: Scialog Fellow (2023) ACS Emerging Technology Award (2017, 2014) Eshelman Institute for Innovation Award (2016) Labs/Teams: Directs the Isayev Lab, which pioneers AI-driven molecular discovery through synergies between automated experiments and ML agents.

Dana-Kristin MahView profile

Assistant Professor

• Educational Technology
• Artificial Intelligence in Education
• Digital Transformation in Higher Education
• +5 more

Dana-Kristin Mah is a Junior Professor for Digital Teaching and Learning at Leuphana University of Lüneburg. Her research focuses on educational technology, artificial intelligence in education, and digital transformation in higher education. She explores topics such as AI literacy, open educational resources (OER), learning analytics, and instructional design. Research Areas: Educational Technology, AI in Education, Digital Transformation, Learning Analytics, OER Her recent publications highlight trends in AI-driven pedagogy, digital mindset development for educators, and the integration of generative AI with learning analytics. She has received fellowships from Forschungskolleg KI-Kompetenzen and Zia – Visible Women in Science. Projects: Artificial Intelligence in Education (Germany/Denmark), GenAI-Natives (teacher training for generative AI), and Digital-Didactic Potentials in Transformation. Her work bridges technology and pedagogy, emphasizing practical applications for enhancing teaching and learning experiences.

Tiantai DengView profile

Lecturer

• FPGA-based Hardware Acceleration
• Sparse Processing Architecture for CNN and GEMM
• Number System and Approximation Computing
• +3 more

Dr. Tiantai Deng is a Lecturer in Electronics and Digital Systems at the School of Electrical and Electronic Engineering , University of Sheffield (since 2021). His industrial background includes a senior research engineer role at HiSilicon/Huawei , where he focused on hardware architecture design for CNN, GEMM, and image/video processing on FPGAs/ASICs. Education: BEng, MSc, PhD Research interests span FPGA-based hardware acceleration , sparse processing architecture for CNN/GEMM, number system design , approximation computing , and high-level design environments . His work integrates algorithm-hardware co-optimization for efficiency in AI and mathematical computing. Recent publications emphasize neurodynamic systems for opinion modeling, parallel processing elements for ODE/AI acceleration, and low-power FPGA implementations for clustering/modulation classification. Earlier work addressed combustion dynamics and image processing pipelines. Contact: t.deng@sheffield.ac.uk | Office: G108, Sir Frederick Mappin Building, Sheffield S1 3JD | ORCID 0000-0003-4507-5746

Jenny LawrenceView profile

Professor

• Higher Education
• Academic and Educational Leadership
• Competence-Based Education
• +4 more

Professor Jenny Lawrence is a distinguished academic at Oxford Brookes University , serving as the Director of the Oxford Centre for Academic Enhancement and Development (OCAED) . Her role involves aligning academic development with institutional priorities while mentoring Aurora, Research, and Principal Fellows. She contributes to the HE and Lifelong Learning Research Cluster . Education : 2017: Master of Education in Teaching and Learning in Higher Education, University of Sheffield 2003: Ph.D. in Philosophy & Gender Studies, University of Hull 1997: Bachelor of Arts (2:1) in Gender Studies & Philosophy, University of Hull Research Interests : Academic and educational leadership in higher education Future-facing curricula (competence-based education, GenAI integration) Building scholarly cultures in college-based HE Educator wellbeing and ethics Recent Publications : Focus on generative AI ethics in education and competence-based curricula, with 2024-2025 works addressing sustainable innovation and digital transformation trends. Scientific Awards : National Teaching Fellow Principal Fellow of Advance HE (PFHEA) Senior Fellow, Staff and Educational Development Association Collaborative Award for Teaching Excellence Grants & Projects : Over £50,000 in collaborative grants from Advance HE, QAA, and Association of National Teaching Fellows (2022-2023) for GenAI ethics, inclusive assessment, and competence-based education initiatives involving institutions like University of Hull, Cambridge, and Warwick. Labs & Teams : Leads OCAED and contributes to the HE and Lifelong Learning Research Cluster , fostering cross-institutional networks for programme leader development.

Cameron BrownView profile

Associate Professor

• Pharmaceutical Manufacturing
• Crystallization Processes
• Digital Design Tools
• +4 more

Dr. Cameron Brown is a Reader (equivalent to Associate Professor) at the Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow. He specializes in developing digital design tools and strategies for pharmaceutical manufacturing. Brown joined Strathclyde in 2014 and has progressed through research associate, research fellow, and Chancellor's fellow positions. He currently coordinates the Drug Substance Manufacturing module for the Advanced Pharmaceuticals Manufacturing MSc program. Education: Brown holds a PhD in crystallization process characterization and a Chemical Engineering degree, both from Heriot-Watt University. Research Focus: His work centers on three primary areas: Hybrid modeling approaches : Integrating physics-based and data-driven models to enhance drug substance manufacturing efficiency Self-driving labs : Developing automated systems for drug substance process development with model-based experimental design Digital decision-making : Implementing coupled models through GenAI and LLMs for rapid pharmaceutical process development His research contributes to UN Sustainable Development Goals through improved medicine manufacturing sustainability. Publication Trends: Brown's recent articles focus on pharmaceutical crystallization, digital design methodologies, AI applications in manufacturing, and process optimization. His work demonstrates strong emphasis on translating computational models into industrial practice, particularly in continuous manufacturing and quality-by-design frameworks. Honors: Elected staff officer of British Association of Crystal Growth (2024) Research Leadership: Brown serves as Principal Investigator for PharmaCrystNet and co-investigator on multiple major initiatives including Digital Design and Manufacturing of Amorphous Pharmaceuticals, Future CMAC Manufacturing Hub, Accelerated Discovery and Development of New Medicines Prosperity Partnership, and ARTICULAR. He leads knowledge exchange projects with pharmaceutical companies and manages knowledge transfer partnerships. Professional Engagement: Brown is active in the Acceleration Consortium and serves on the committee of the British Association of Crystal Growth.

• Empirical Software Engineering
• Requirements Engineering
• Applied Natural Language Processing
• +7 more

Dr. Chetan Arora is a Senior Lecturer in Software Engineering at Deakin University's School of Information Technology, part of the Faculty of Science Engineering and Built Environment. He holds a PhD from the University of Luxembourg where he received the best PhD thesis award in the ICT domain. His research focuses on applied Artificial Intelligence in Software Engineering, with particular emphasis on Empirical Software Engineering, Requirements Engineering, and Applied Natural Language Processing. PhD in Computer Science from University of Luxembourg Masters in Software Engineering from Technische Universitat Kaiserslautern (Germany) Bachelors in Engineering (CS) from Thapar University (India) Arora's research interests center on the intersection of AI and Software Engineering, particularly how machine learning and natural language processing can enhance software development processes. His work explores requirements engineering, test automation, software trustworthiness, and human-centric software development. He investigates how large language models can be effectively deployed for tasks like test case generation, requirements analysis, and traceability. His recent publications reveal a strong focus on practical applications of AI in software engineering, with numerous studies examining the real-world implementation challenges and benefits. His publication record shows significant activity in top software engineering venues, with a notable emphasis on AI applications in software engineering processes. His recent work demonstrates expertise in retrieval-augmented generation systems, requirements-driven testing, and human-centric software development approaches. The publications collectively highlight his focus on bridging theoretical AI advancements with practical software engineering challenges. Best Ph.D. thesis award in the ICT domain at University of Luxembourg Arora actively supervises doctoral students working on cutting-edge topics including satellite communication systems, extended reality applications, and human-centered AI requirements engineering. His industry collaborations include work with Department of Defence on projects like Contextually Situated Anomaly Detection and Planning and Optimisation of Resources in Defence Satellite Communication Systems. He previously worked at SES Satellites on applied AI for IoT and Satcom, and as an FNR-PPP research fellow at the University of Luxembourg in software quality assurance. His laboratory work focuses on developing practical AI solutions for software engineering challenges, particularly in requirements engineering and test automation. Current projects involve multi-orbit satellite constellation optimization, dynamic radio resource management, and extended reality enabled human-centric requirements engineering.

• Artificial Intelligence
• Machine Learning
• Inverse Reinforcement Learning
• +5 more

Aaron Snoswell is a Research Fellow at Queensland University of Technology (QUT), affiliated with the Faculty of Creative Industries, Education & Social Justice and the School of Communication. His work bridges technical AI development with social implications, focusing on ethical implementation of AI systems across multiple domains including healthcare, legal systems, and public policy. Snoswell's research interests span artificial intelligence, machine learning (particularly inverse reinforcement learning), AI ethics, automated decision-making systems, and the societal implications of AI technologies. His work demonstrates a consistent focus on making AI systems more transparent, accountable, and beneficial for society, with particular attention to healthcare applications, legal systems, and public understanding of AI technologies. Analysis of his most recent publications reveals a clear trajectory toward responsible AI deployment, with increasing focus on policy frameworks, public education about AI capabilities and limitations, and practical applications that address real-world problems in healthcare and justice systems. His work often combines technical AI development with critical social perspectives, reflecting an interdisciplinary approach that connects computer science with social sciences. Snoswell has been actively involved in policy submissions to governmental bodies including the Australian Senate Select Committee on Adopting Artificial Intelligence and responses to the G7 Guiding Principles for organizations developing advanced AI systems. His work with the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S) demonstrates his commitment to shaping responsible AI governance frameworks. He has established productive collaborations across multiple institutions and disciplines, working with researchers in communication studies, computer science, healthcare, and legal fields. His recent work on the GenAI Arcade project represents an innovative approach to public engagement with AI technologies through interactive learning environments.

Tim HulsenView profile

Professor

• Artificial Intelligence in Healthcare
• Data Science in Healthcare
• Generative AI
• +6 more

Dr. Tim Hulsen is a Professor of AI & Data-Supported Healthcare at the Knowledge Center for Healthcare Innovation, Rotterdam University of Applied Sciences, where he leads research on the application of data science and artificial intelligence in healthcare. He is also actively involved in the HR Datalab Healthcare and maintains a dual role as Senior Data & AI Scientist at Philips. His work bridges academic research and industry application, focusing on practical implementations of AI technologies in healthcare settings. Tim completed his Biology studies at Radboud University Nijmegen with a strong medical-biological component. After internships in Molecular Animal Physiology and Bioinformatics, he pursued a PhD and postdoctoral position at Radboud University Nijmegen in collaboration with NV Organon (later Schering-Plough). His academic journey transitioned into industry when he joined Philips Research in Eindhoven in 2009, where he has held various scientific positions focused on data management, big data, and artificial intelligence in healthcare. Dr. Hulsen's research focuses on the practical application of data science and AI in healthcare, emphasizing the importance of good data quality through sound data management practices, adherence to the FAIR Guiding Principles, and the use of ontologies and standards. He places particular emphasis on the explainability and responsible use of AI systems in clinical settings. His recent research interests have expanded to include generative AI (GenAI) applications in healthcare, where he seeks to connect various professorships and departments within the Rotterdam University of Applied Sciences with the broader medical technology sector. An analysis of Dr. Hulsen's recent publications reveals a strong focus on AI applications in healthcare, particularly in oncology and prostate cancer research. His work demonstrates a progression from foundational data management and bioinformatics to cutting-edge AI applications, with increasing emphasis on responsible implementation and practical healthcare solutions. The publications span technical aspects of data science, clinical applications, ethical considerations, and future directions for AI in healthcare. Dr. Hulsen has made significant contributions to the academic community through his editorial work, serving as an Editorial Board Member for BMC Cancer and Frontiers Medicine and Public Health, and regularly reviewing scientific publications. While specific awards aren't detailed in the available information, his extensive publication record (over 50 scientific publications) and leadership roles indicate recognition within his field. Throughout his career, Dr. Hulsen has demonstrated strong leadership in research projects, having led various initiatives, co-authored international project proposals, and managed work packages within grant projects. His collaborative approach is evident in his work connecting academic research with industry applications, particularly through his dual roles at Rotterdam University of Applied Sciences and Philips. His work with the Movember GAP3 consortium and PIONEER big data platform for prostate cancer demonstrates his commitment to large-scale collaborative research that addresses real-world healthcare challenges. Dr. Hulsen is actively involved with the HR Datalab Healthcare and the AI & Data-Supported Healthcare research group. He collaborates extensively with various stakeholders in the healthcare ecosystem, including medical institutions like Erasmus MC, technology companies, and research consortia. His current work focuses on practical applications such as registration burden reduction using generative AI, non-invasive monitoring, and optimization of diagnostics and prevention strategies. Through these initiatives, he aims to develop explainable knowledge that will train future healthcare professionals in the responsible use of AI.

• Data Science
• Artificial Intelligence
• Computer Science Education
• +2 more

Martin Goodfellow is a Senior Lecturer in Computer and Information Sciences at the University of Strathclyde. He serves as Director of Undergraduate Teaching and Deputy Group Lead of the Computer Science Education Research Group. His work bridges software engineering, data science, and AI with a focus on pedagogy and outreach. First Class BSc in Software Engineering, University of Glasgow (2008) PhD in Computer Science, University of Strathclyde (2014) Postgraduate Certificate in Learning and Teaching in Higher Education (2021) His research spans computer science education , data science , and artificial intelligence , emphasizing pedagogical innovation and ethical implications of emerging technologies. Recent publications highlight the use of GenAI, LLMs, and chatbots in education, database teaching, and software engineering curricula. Selected awards include the Euan Minto Prize (2018) , Fellow of Advance HE (2021) , and multiple recognitions from the Teaching Excellence Awards (2022-2023). He actively collaborates on projects like Exploring the use of Chat GPT by Engineering Employers and contributes to curriculum design for data systems education.

Michael HarrView profile

Researcher

• Artificial Intelligence
• Recruiting
• Digitalization and digital Transformation of Human Resource Management
• +4 more

Michael Harr is a doctoral researcher and research assistant at the University of Duisburg-Essen, affiliated with the Faculty of Computer Science and the Chair of Business Informatics and Integrated Information Systems. His work focuses on artificial intelligence, digital transformation of HR management, enterprise systems, new work arrangements, and digital communication. He has published extensively on these topics in leading journals and conferences. Education: M.Sc. in Business Information Systems (2020-2023), University of Duisburg-Essen B.Sc. in Business Information Systems (2016-2020), University of Duisburg-Essen His research explores the intersection of AI and human-centric systems, including studies on retail service robots, intelligent HRIS, generative AI in MOOCs, and user annoyances in voice assistants. Recent publications analyze digital communication trends and digitalization challenges in the construction sector. Publications: Harr has contributed to key areas such as retail automation, HRIS optimization, and AI-driven e-learning, with a focus on practical applications and theoretical frameworks. Supervised Theses: Exploring ChatGPT for MOOCs AI in Knowledge Management Technostress and Quiet Quitting Taxonomy of AI Recruitment Tools Talent Recruitment on Social Networks Labs and Teams: Harr is involved in the Retail Artificial Intelligence Lab (retAIL) and SAP Innovation Lab, contributing to projects on digital transformation and enterprise systems.

Akanksha SainiView profile

Lecturer

• Cybersecurity
• Health Informatics
• Distributed Computing
• +4 more

Dr. Akanksha Saini is a Lecturer at RMIT University's School of Accounting, Information Systems, and Supply Chain. Her research focuses on cybersecurity, distributed systems, health informatics, and blockchain applications in healthcare. She holds an ORCID identifier (0000-0002-7191-2854) and is open to supervising Masters and PhD students in cyber security and related fields. Research Interests: Cybersecurity and Privacy Blockchain Technology in Healthcare Artificial Intelligence Applications Quantum Computation Supply Chain Management Health Informatics Systems Key Contributions: Pioneering work on securing distributed networks for IoT intrusion detection Developed blockchain-based frameworks for medical data sharing and access control Established collaborations with industry and international researchers Publications Highlight: Recent articles (2021–2025) emphasize blockchain applications in healthcare, federated learning, and cybersecurity challenges in the GenAI era. Over 30+ peer-reviewed papers in journals like Journal of Information Security and Applications and IEEE Internet of Things Journal . Supervision and Collaboration: Available to supervise research in cyber security and AI Industry partnerships align with national research priorities Co-authored papers with global collaborators in cryptography and health informatics Labs and Teams: Engaged in interdisciplinary projects at RMIT's School of Accounting, Information Systems, and Supply Chain, with a focus on real-world industry applications.

Bing LiuView profile

Adjunct Professor

• Natural Language Processing
• Large Language Models
• Dialogue Systems
• +4 more

Bing Liu serves as Director of Applied Research at Scale AI and Adjunct Professor in the Computer Science and Engineering department at the University of California, Santa Cruz. Previously, he held leadership roles at Meta (GenAI and Reality Labs), Google Research, and Capio.ai (acquired by Twilio), with expertise spanning generative AI, NLP, and spoken dialogue systems. His educational background includes: Ph.D. in Electrical and Computer Engineering from Carnegie Mellon University B.Eng in Electrical and Electronic Engineering (First Class Honors) from Nanyang Technological University, Singapore Exchange studies at KTH Royal Institute of Technology, Sweden Liu's research focuses on advancing large language models, dialogue systems, and reinforcement learning for conversational AI. His work bridges theoretical innovation with industrial-scale applications, particularly in zero-shot learning, multilingual capabilities, and evaluation frameworks for generative AI. He has pioneered techniques in dialogue state tracking, knowledge-enriched task-oriented systems, and continual learning to address catastrophic forgetting in neural dialogue models. Analysis of his 15 most recent publications reveals a clear trajectory toward industrial-scale generative AI: early work (2018-2021) established foundational methods in task-oriented dialogue systems, while recent publications (2022-2024) focus on LLM post-training, multimodal integration, and evaluation benchmarks like Humanity's Last Exam. Key thematic clusters include cross-lingual transfer, knowledge grounding in dialogue, and robust evaluation frameworks for frontier models. As an educator, Liu guides graduate research at UC Santa Cruz in LLM and multimodal AI while serving in critical conference roles including Publication Chair for ACL 2024 and Area Chair for ACL 2023's Large Language Models track. His industry leadership includes building Scale AI's 40+ member research team and driving Meta's Llama3 development, managing multimillion-dollar data roadmaps that scaled the Meta AI Assistant to 700M MAU. Liu directs Scale AI's applied research lab focused on GenAI data and evaluation, having previously built Meta's NLU team for AR/VR voice assistants deployed across Portal, Oculus, and Ray-Ban Smart Glasses. His current work centers on creating evaluation leaderboards adopted by top AI labs and developing the data engine for next-generation generative models.

Sammy TaggartView profile

Lecturer

• Educational Technology
• Virtual Reality in Education
• Teacher Professional Development
• +5 more

Sammy Taggart is a Lecturer in Education at Ulster University's School of Education within the Faculty of Arts, Humanities & Social Sciences. He serves as a Teacher Educator in Technology and Design Education with expertise in educational technologies and their application in Northern Ireland's educational system. His work bridges academic research with practical implementation in schools across Northern Ireland. His research interests focus on leveraging educational technologies to enhance learning experiences, with particular emphasis on creating blended and balanced digital environments that stimulate creativity and critical thinking. Taggart has contributed extensively to teacher professional learning, digital safeguarding measures, research, and policy development related to educational technology. His work examines the intersection of technology, design, and engineering education within the specific context of Northern Ireland's educational landscape. Taggart's publication record shows a clear trajectory toward increasingly sophisticated applications of technology in education, with recent work focusing on generative AI implementation in schools, blended learning effectiveness, and teachers' digital competences. His research consistently centers on the Northern Ireland context while addressing universal challenges in educational technology adoption. Distinguished Education Excellence Award (2021) Learning and Teaching Awards 2023 - Educator of the Year Award (Shortlisted, 2023) As Principal Investigator and Co-Investigator on multiple research projects since 2018, Taggart has secured consistent research funding with a notable increase in project volume since 2022. His current projects include the NI Schools | GenAI Pilot - MS and TRANSFORMING EDUCATION FINAL PHASE, demonstrating his leadership in cutting-edge educational technology research. He also serves as an External Examiner at the University of Roehampton since 2020. Taggart collaborates extensively with examination authorities, STEM-focused charitable groups, and local organizations to promote education, design, and engineering across Northern Ireland. His work aims to create practical pathways for technology integration that respect the unique characteristics of Northern Ireland's educational system while preparing students for a technologically advanced world.