José Barbosa is a Senior Researcher at the Research Centre in Digitalization and Intelligent Robotics (CeDRI) and an Invited Professor at the Department of Electrical Engineering, Polytechnic Institute of Bragança, Portugal. He holds a PhD in Automation and Computer Science from the University of Valenciennes (France) and has extensive experience in European-funded projects like ARUM, GRACE, DA.RE, GO0DMAN, and PERFoRM. His expertise spans Cyber-Physical Systems, Multi-Agent Systems, and manufacturing automation, with over 40 international publications. Research focuses on self-organizing manufacturing architectures, digital twins, and bio-inspired mechanisms. He teaches courses including Microcontroller/Microprocessor Systems, Automation, and Electric Propulsion. Projects emphasize Industry 4.0, zero-defect manufacturing, and intelligent products. His work intersects IoT, data analytics, and human-machine integration in industrial systems.
Emily M. Hastings is an Assistant Professor of Computer Science at the University of Wisconsin-Eau Claire. She holds a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign (2023) and M.S. (2019) and B.A. degrees from Knox College (2016). Her research focuses on algorithmic team formation, human-computer interaction, and computer science education. She has conducted research at NIST and collaborated with institutions like the University of Michigan. Education: Ph.D. in Computer Science, University of Illinois (2016-2023) M.S. in Computer Science, University of Illinois (2016-2019) B.A. in Computer Science, Knox College (2012-2016), with a self-designed minor in Renaissance and Medieval Studies Research Interests: Her work addresses technical, design, and social challenges in algorithmic team formation, particularly in educational and industrial contexts. She explores how stakeholders (instructors, students, technicians) can influence algorithmic decisions to enhance collaborative outcomes. Additional interests include creativity support systems (e-textiles, digital humanities) and the intersection of computer science with historical studies. Awards: Listed as an Excellent Teacher by University of Illinois students (2021-2022) Tau Beta Pi Honor Society (2021) Mavis Future Faculty Fellowship (2020-2021) Teaching & Service: Teaches courses like CS 145 (Programming Fundamentals), CS 146 (Big Picture in CS), and CS 335 (Algorithms). She has led workshops on accessibility in design and served as a mentor for initiatives like Girls Who Code. Her creative projects include a craft business (Realms of Legend) and historical costume construction inspired by Elizabethan England. Labs/Teams: Active in the University of Wisconsin-Eau Claire’s CS department research groups, focusing on educational technology and algorithmic fairness. Previously collaborated with NIST’s Knowledge Extraction and Application team on maintenance workflow optimization.
Dr. Raquel Campos Valverde serves as a Postdoctoral Research Fellow at the School of Media and Communication, University of Leeds, where she investigates digital music cultures through the MUSICSTREAM project. Her work bridges Popular Music studies, Ethnomusicology, and Internet Research with a focus on user experiences in streaming ecosystems and social media environments, particularly within Spanish cultural contexts. Her academic foundation includes: PhD in Arts and Creative Industries from London South Bank University (2019) MMus in Ethnomusicology from SOAS, University of London BHons in Sociology from Universidad de Granada, Spain Campos Valverde's research critically examines how digital infrastructures shape musical experiences, with current emphasis on cultural inequality in streaming taxonomies and algorithmic recommenders. She employs digital ethnography to analyze music circulation across social platforms, exploring moral economies of sharing and imagined listening communities. Her scholarship reveals persistent tensions between platform design and cultural diversity, highlighting how technical architectures reinforce systemic biases in music discovery and consumption. Analysis of her publication trajectory shows evolving focus from social media musicking (2018-2022) toward critical platform studies (2023-2025), with consistent attention to ethical implications of digital music environments. Recent work demonstrates sophisticated interdisciplinary methodology combining interface analysis, ethnographic observation, and critical algorithm studies. Her recognition includes: 2019 Andrew Goodwin Memorial Postgraduate Prize from IASPM UK/Ireland Campos Valverde maintains active engagement with academic communities through editorial contributions to the Open Encyclopedia of Anthropology and IASPM Journal. Her prior teaching role at King's College London demonstrates commitment to knowledge dissemination, while her current research directly addresses urgent questions about equity in digital cultural infrastructure. The MUSICSTREAM project positions her at the forefront of critical platform studies within music scholarship. As core researcher in the MUSICSTREAM initiative, she collaborates with interdisciplinary teams to deconstruct streaming platform architectures, producing actionable insights for more inclusive music technology design through rigorous ethnographic and critical technical approaches.
Dr. Amanda Coles is a Senior Lecturer in Computer Science at the Department of Informatics , King's College London , within the Faculty of Natural, Mathematical & Engineering Sciences . She is a leading researcher in Artificial Intelligence Planning , focusing on temporal, continuous, and preference-based planning, with applications in robotics, space, healthcare, and autonomous systems. University: King's College London School: Faculty of Natural, Mathematical & Engineering Sciences Department: Department of Informatics Academic Rank: Senior Lecturer Email: amanda.coles@kcl.ac.uk ORCID: https://orcid.org/0000-0002-1838-8301 Her research centers on advanced AI planning techniques, including planning under uncertainty, numeric and temporal reasoning, and explainability in planning systems. She investigates how AI can support decision-making in complex domains such as space robotics (e.g., ERGO, ADE projects), multimorbid patient management, and power systems. Her work often integrates constraint programming, heuristic search, and optimization to improve planner efficiency and expressiveness. Her recent publications (2019–2024) reflect a strong focus on explainable AI in planning, with user studies informing the design of interpretable planning systems. She also continues to advance core planning technologies, such as handling nonlinear change, disjunctive scheduling, and metastate abstractions. Her work bridges theoretical AI with practical deployment in real-world autonomous systems. EPSRC Post-Doctoral Research Fellowship (2010–2013) Invited speaker at IJCAI Early Career Spotlight (2016) Dr. Coles has led multiple externally funded research projects, including from EPSRC and the European Commission (e.g., ERGO, ADE, POLARIS), focusing on scalable planning, continuous change, and autonomy in robotics. She has edited major conference proceedings (e.g., ICAPS 2016) and co-developed influential planning systems like COLIN and PDDL+. She actively supervises research students and collaborates across disciplines, contributing to the development of trustable autonomous systems at King's College London. She is a key member of the Planning, Reasoning and Planning research group and the Trusted Autonomous Systems Hub , where her work supports the development of reliable, explainable, and efficient autonomous decision-making systems for future applications.
Manuel Brack is an Applied Research Scientist at Adobe Firefly in San Jose, USA, with an adjunct research affiliation at hessian.AI in Darmstadt, Germany. His academic foundation includes a Ph.D. from TU Darmstadt's Machine Learning Lab where he specialized in generative AI systems. He co-founded the Occiglot research collective focused on open-source LLM development. Brack's research centers on large-scale generative models at the intersection of natural language processing and computer vision. His work addresses critical challenges in monosemanticity measurement , multilingual data curation , AI safety frameworks , and text-to-image generation ethics . He has pioneered techniques for bias mitigation in multilingual systems and developed novel architectures for memory-efficient language modeling. His publications reveal significant trends toward neuro-symbolic integration (DeiSAM), privacy-preserving mechanisms (CLIP identity attacks), and community-driven open science (Occiglot/Community OSCAR). The research consistently bridges theoretical innovation with practical deployment considerations for generative systems. Best Runner-Up Paper Award RBFM Workshop at NeurIPS 2024 (LlavaGuard) Best Paper Award at DPFM 2024 (Homoglyphs research) Brack actively contributes to open-source initiatives including Community OSCAR (345+ TiB multilingual dataset) and Occiglot (open LLM development). His work emphasizes ethical deployment through frameworks like Fair Diffusion for bias attenuation and Safe Latent Diffusion for content moderation, demonstrating commitment to responsible AI advancement.
Thaddeus A. Roppel is an Associate Professor in the Department of Electrical and Computer Engineering at Auburn University's College of Engineering. His work spans teaching, research in robotics and sensor systems, and academic outreach. He is actively involved in curriculum development, senior design coordination, and lab leadership. University: Auburn University School: College of Engineering Department: Electrical and Computer Engineering Position: Associate Professor His research focuses on cooperative robotics, sensor fusion, MEMS sensors, and neural network applications in odor analysis. He leads the Sensor Fusion Laboratory and has contributed to interdisciplinary projects involving intelligent systems and technology readiness assessment. His educational initiatives include Java-based electronics demos, wireless curriculum development, and capstone design mentoring. The recent publications reflect a strong trend in intelligent sensing, robotics, and engineering education. Key themes include real-time signal processing, neural networks for pattern recognition, technology maturity assessment (TRL), and innovative teaching tools. His work bridges theoretical research with practical implementation in academic and outreach contexts. Scientific Awards: No formal awards listed in available texts. Dr. Roppel advises students through senior design and graduate research, particularly in robotics and sensor systems. He has led projects funded through academic and outreach grants, including senior design initiatives and the proposed Auburn Technology Museum. He is also involved in service, such as coordinating Engineers Without Borders and maintaining educational web resources. He leads the Sensor Fusion Laboratory at Auburn University, which focuses on integrating sensor data using neural networks and intelligent algorithms. The lab supports student research in mobile robotics, odor detection, and cooperative systems. He also promotes broader engineering outreach through virtual museum development and safety education.
Seokhyun Chung is an Assistant Professor at the University of Virginia, located in Lab 257 of Olsson Hall. His research focuses on IoT-enabled systems, leveraging data-driven methods such as federated learning, multi-task learning, and Bayesian probabilistic modeling to address challenges in statistical heterogeneity, scalability, and personalization in connected systems. Applications span smart healthcare and manufacturing systems, emphasizing reliability and efficiency. Research Interests: Chung's work integrates IoT, machine learning, and systems engineering to develop collaborative analytics frameworks. He explores federated learning architectures for distributed data fusion, probabilistic modeling for uncertainty-aware predictions, and optimization techniques for resource allocation in edge computing environments. His healthcare focus includes gait analysis and load estimation for wearable devices, while manufacturing applications involve job scheduling and additive manufacturing quality control. Key Contributions: Recent work highlights include federated multi-output Gaussian processes for heterogeneous systems, real-time adaptation of time-series predictions, and fairness-aware machine learning for load carriage tasks. His interdisciplinary projects address both technical and operational challenges, such as emergency department layout optimization and toxic gas monitoring networks. Labs & Infrastructure: Chung's research is conducted in Olsson Hall's advanced labs, leveraging IoT sensor networks, edge computing setups, and collaborative simulation environments to prototype innovative smart systems solutions.
Roland Dunbrack, Jr. is a Professor and Co-Leader of the Cancer Signaling and Microenvironment Program at Fox Chase Cancer Center. He also serves as Director of both the Molecular Modeling Facility and the Organic Synthesis Facility. He holds adjunct professorships at the University of Pennsylvania School of Medicine and Drexel University College of Medicine, reflecting his broad academic engagement. His research lies at the core of computational structural biology and bioinformatics, focusing on protein structure prediction, statistical analysis of protein conformations, and the development of software tools such as SCWRL, MolIDE, and BioAssemblyModeler. His work integrates Bayesian statistics, machine learning, and computational geometry to improve the accuracy of protein modeling and to apply these methods to cancer biology, DNA repair, and antibody design. He maintains several widely used public databases, including the backbone-dependent rotamer library and ProtCID. The analysis of his recent publications reveals a sustained focus on protein structure and function, with significant contributions to understanding kinase conformations, biological assemblies, antibody CDR loops, and the structural basis of disease mutations. His work increasingly bridges computational methods with clinical applications in precision medicine, particularly in cancer. Health Equity & Social Justice Award (2024) Dr. Dunbrack leads a research group that includes graduate students and postdoctoral researchers, and he actively collaborates with experimentalists across Fox Chase and beyond. His lab has been involved in major community efforts such as CASP and CAGI, assessing the state of the art in protein and genome structure prediction. He has directed the NCI-supported Molecular Modeling Facility since 2003, providing critical resources to cancer researchers. His lab, the Dunbrack Lab, is dedicated to advancing structural bioinformatics through method development, software engineering, and collaborative science. The team works on large-scale analyses of the Protein Data Bank, develops user-friendly graphical interfaces for modeling, and applies computational insights to problems in cancer signaling and microenvironment.
Nebojša S. Doncov is a Full Professor at the Faculty of Electronics, University of Niš, Serbia, where he is affiliated with the Department of Telecommunications. He has been a leading academic and researcher in computational electromagnetics and antenna systems since earning his PhD in 2002 from the same institution. His research interests include: Computational Electromagnetics, particularly the Cylindrical TLM Method Antenna Design and Optimization using AI and Neural Networks Wearable and Smart Textile Antennas Direction of Arrival (DoA) Estimation Electromagnetic Compatibility and High-Frequency Modeling Biomedical and UAV-based GPR Applications His recent publications show a strong trend toward integrating artificial intelligence with electromagnetic modeling, especially in wearable and conformal antenna systems. He has published extensively in top IEEE and Wiley journals, with a focus on numerical methods and practical antenna applications for wireless and biomedical systems. His scientific awards include: URSI Young Scientist Award (2002) Aleksandar Marinčić Award (2017) Best Diploma Thesis Award (1995) Early Graduation Charter (1995) He has led or participated in numerous national and international research projects, including NATO Science for Peace, Royal Society International Exchange, and multiple COST Actions. He has advised students through research collaborations and co-authored works, though no formal list is provided. He has also contributed to academic education through textbooks and problem collections. He is actively involved in research labs and teams, including the Serbian research teams in SmartBridges, Predictive Design of Wearable Antennas, and Advanced UAV-Based GPR Imaging. He collaborates with institutions such as WIPL-D, University of Nottingham, and Technical University of Munich.
Niklas Kühl is a W3 Professor and Chairholder of Business Information Systems and Human-Centered Artificial Intelligence at the University of Bayreuth. He also serves as Director at the FIM Research Institute for Information Management and holds a Senior Expert role in Artificial Intelligence at IBM. His work bridges academia and industry, with affiliations at Fraunhofer FIT and extensive international collaborations including with Carnegie Mellon University, MIT-IBM Watson AI Lab, and the University of Warwick. His research lies at the intersection of machine learning and human factors, focusing on the development of socio-technical information systems. Key interests include explainable AI, fairness in algorithmic decisions, human-AI collaboration, trust calibration, and the application of AI in sustainability, healthcare, and digital business. He emphasizes data-centric AI and robust, scalable AI products, with a strong focus on ethical and societal implications. The 15 most recent publications highlight a consistent trend toward human-centered AI, with a focus on explainability, fairness, and appropriate reliance in human-AI teams. There is growing emphasis on generative AI, multi-agent systems, and AI applications in healthcare and sustainability. Publications span top venues in AI (AAAI, CHI), information systems (ECIS, ICIS, HICSS), and ethics (FAccT), reflecting interdisciplinary impact. Best Paper Awards (multiple) Summa Cum Laude, PhD, Karlsruhe Institute of Technology Niklas Kühl has advised numerous researchers and students, many of whom appear as co-authors in his publications, though specific advisees are not listed. He has led significant research projects in human-AI collaboration, inter-organizational analytics, and AI for sustainability, often funded by public and industrial partners. His work at IBM and Fraunhofer demonstrates strong industry engagement. He leads the Applied AI in Services Lab (formerly at KIT) and is deeply involved in the FIM Research Institute, contributing to digital transformation in business and society. His collaborations span global institutions, and he actively promotes digital education through initiatives like Education for Refugees, which he co-founded.
Timothy Reissman is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Dayton’s School of Engineering. He is a full-time faculty member actively engaged in research, teaching, and professional service. His work bridges engineering and healthcare, focusing on human-machine interfaces and assistive technologies. Education: Ph.D., Mechanical Engineering, Cornell University, 2013 M.S., Mechanical Engineering, Cornell University, 2008 B.S., Mechanical and Aerospace Engineering, Cornell University, 2002 Dr. Reissman's research centers on developing mechatronic systems to improve medical and assistive devices such as prostheses, exoskeletons, rollator walkers, and canes. His work integrates biomechanics, control systems, and wearable technology. He maintains clinical collaborations with physical therapy faculty and hospitals in the Dayton area, ensuring real-world relevance. His group also investigates coupled electromechanical systems and energy harvesting for autonomous devices. His recent publications span from 2025 to 2020, showing sustained productivity in interdisciplinary areas including rehabilitation engineering, robotics, smart thermostats, and engineering education. The research demonstrates a strong trend toward human-centered design, sensor integration, and the application of virtual reality and wearable sensors in mobility assessment. Scientific Awards: University Teaching Fellow, University of Dayton, 2017–2018 Kern Entrepreneurial Engineering Network Faculty Fellow, 2017 National Institutes of Health NRSA T32 Postdoctoral Fellow, 2013–2015 Intelligence Community Research Fellow, Department of Defense, 2010–2012 Dr. Reissman advises student research and teaches courses such as Mechatronics, Robotics, and Dynamic Systems. He has secured research grants related to assistive technology and engineering education, including NSF IUSE grants. He serves as an Associate Editor for the Journal of Assistive Technology and is active in ASME, IEEE, and ASEE. His work is supported by strong institutional and clinical partnerships. He leads a research group focused on autonomous systems and human augmentation, with access to labs in Kettering Laboratories. His team develops novel solutions such as smart prosthetic liners, energy-harvesting structures, and feedback devices for mobility aids. Future work includes expanding the use of VR and AI in rehabilitation and enhancing the functionality of wearable assistive devices.
Dr. Kirill Krinkin is an Adjunct Professor at Constructor University and Visiting Professor at Neapolis University , with a PhD in Software Engineering (2004). He serves as Head of Research Lab at JetBrains , focusing on the intersection of AI, robotics, and education technology. Research Focus : Co-evolutionary Hybrid Intelligence : Developing human-AI collaboration frameworks Mobile Robotics : Lightweight perception algorithms (VinySLAM, Multi-agent SLAM) Flipped Learning : LLM-powered lifelong education systems Next-Gen OS : Agent-based scheduling and real-time feedback models Scientific Contributions : Co-authored 6 publications (2017-2023) in hybrid intelligence, robotics, and education 2 granted patents (2022) in flexible manufacturing and autonomous vehicle design
Volker Schwieger is a Professor at the Institute of Engineering Geodesy , affiliated with the Faculty of Aerospace Engineering and Geodesy at the University of Stuttgart . As a Principal Investigator in the Cluster of Excellence IntCDC, he focuses on integrating geodetic measurement technologies into computational design and construction workflows, with emphasis on robotic control, 3D scanning, and quality modeling. Key research areas: Geodesy, Computational Design, Robotics in Construction, Quality Assurance Notable projects: RP 16-1 (Robotic Assembly), RP 18-1 (Holistic Quality Model), AP 7 (Space-Time Point Cloud Modeling) Recent publications demonstrate his work in terrestrial laser scanning (TLS) for deformation analysis, point cloud processing algorithms, and holistic quality models for sustainable construction. He collaborates with institutions like Technical University of Munich and contributes to applications in bio-composites, timber structures, and climate-resilient urban planning. His methodological innovations include patch-based M3C2 analysis and supervoxel registration techniques. Despite extensive research output, no specific awards or educational background details are mentioned in the provided texts.
Sophia Brueckner is an Associate Professor at the University of Michigan's School of Information and Digital Studies Institute, combining speculative design with technical expertise. As co-director of the Center for Ethics, Society, and Computing (ESC), she explores algorithmic bias and human-machine relationships through interdisciplinary collaborations. Sc.B. in Computer Science and Applied Mathematics, Brown University MFA in Digital + Media, Rhode Island School of Design MS in Media Arts and Sciences, MIT Media Lab Her research spans: Wearable technology for embodied knowledge Algorithmic accountability frameworks Critique of tech industry practices Speculative design futures Breathing-performance interdependencies Digitized emotional expression Her 2017-2023 publications reveal patterns in: Human-body interface ethics Museum algorithmic bias detection Emotional data sublimation Engineering empathy integration Sonic tactile communication Computational creativity critique Awardee of $470k Biosciences Initiative grant for 2INSPIRE research. Key projects include: Bowerbot: AI curatorial behavior critique Warming Wall: Incarceration isolation mitigation ESC Swag: Tech industry ethics intervention Empathy Amulet: Networked emotional connections White Cube/Black Box: Museum algorithmic bias visualization
Dr. Michael Bain is a Senior Lecturer at the School of Computer Science and Engineering, University of New South Wales (UNSW). His research focuses on integrating machine learning with declarative programming to create explainable AI systems, particularly for complex domains like bioinformatics, social networks, and medical informatics. He has taught courses including Machine Learning and Data Mining and Computational Bioinformatics . Key Research Areas: Explainable AI through logic programming Bioinformatics applications in systems biology Medical claim fraud detection using graphical models Swarm robotics and epigenetic learning Recent Publications highlight his work on fairness-aware AI, knowledge acquisition for event extraction, and hybrid models combining temporal features with collaborative filtering. He actively mentors students, with 8 current advisees and over 30 graduates, and has contributed to projects in online dating recommendation systems and dynamic systems control. Education: PhD in Statistics and Modelling Science from University of Strathclyde; BSc (Hons) from University of Edinburgh. He is affiliated with the Smart Services Cooperative Research Centre for industry grants.
