Luca Di Gaspero is an Associate Professor of Information Technology at the University of Udine, specializing in metaheuristic optimization techniques. His research enhances combinatorial optimization through hybridization of algorithms for scheduling, routing, and industrial applications. Research spans artificial intelligence in optimization, scheduling algorithms for manufacturing/healthcare, and metaheuristic framework development. Recent publications focus on LLMs in optimization, parallel batch scheduling, and energy-efficient manufacturing. Key Contributions: Developed EasyLocal++ framework for local search algorithms Advanced multi-neighborhood simulated annealing techniques Applied metaheuristics to healthcare logistics and emergency services
Dr. Konstantin Aal is a researcher at the Department of Business Informatics and New Media within the Faculty of Information Systems and New Media at the University of Siegen, Germany. Having joined the university in 2012 after completing his studies in Business Informatics there, Dr. Aal has established himself as a prominent researcher at the intersection of technology, social activism, and human-computer interaction. Dr. Aal's educational background is rooted in Business Informatics at the University of Siegen, where he also completed his major dissertation on the social platform come_NET and its use by children as part of the come_IN project. His academic journey reflects a consistent focus on the social implications of technology. His research interests span several critical areas in contemporary socio-technical studies. Dr. Aal investigates how social media platforms are used in political conflicts and activism, particularly in the Middle East and North Africa region, with specific attention to the Palestinian-Israeli conflict and content moderation practices. He also explores human-technology interaction in contexts of aging and dementia care, human-wildlife conflict, and the digital transformation of rural communities. His work consistently emphasizes participatory design approaches, ethical considerations in technology development, and the importance of cultural sensitivity in global technology deployments. Dr. Aal's publication record shows a strong trajectory of impactful research, with particular emphasis on understanding how marginalized communities appropriate technology for their needs. His recent work on the "PlurAIverse" concept expands design paradigms for artificial intelligence to be more inclusive and culturally sensitive, while his ethnographic work in conflict zones reveals critical insights about digital activism under surveillance. Member of the research team for iStoppFalls (fall prevention for elderly) Contributor to multiple EU-funded projects on digital inclusion and socio-informatics Active participant in the Socio-Informatics research program at the University of Siegen Dr. Aal's work bridges theoretical insights with practical applications, often developing technologies in close collaboration with community stakeholders. His approach emphasizes "grounded design" - developing technological solutions that emerge from deep understanding of local practices and needs.
Marco Aldinucci is a Full Professor and Head of the Parallel Computing group at the University of Torino's Computer Science Department. He leads the HPC Key Technologies and Tools (HPC-KTT) national lab under CINI, involving 38 Italian universities. His expertise spans parallel programming models, HPC systems, federated learning, and energy-efficient computing. Aldinucci has secured over €10M in EU research funding, contributed to frameworks like Fastflow and Streamflow, and pioneered initiatives like the HPC4AI lab and the CINI HPC-KTT lab. His research focuses on advancing exascale computing, cloud-HPC integration, and AI-driven medical solutions. Notable projects include the Gaia AVU-GSR solver for exascale systems and the DeepHealth Toolkit for medical AI. He has held governance roles in EuroHPC and chairs the Observatory on Trends and Applications of Supercomputing in Italy. Aldinucci’s publications (150+) address parallel algorithms, distributed learning, and sustainable HPC infrastructure. His work has been recognized with awards from HPC Advisory Council, NVIDIA, IBM, and Autodesk. Current initiatives include the Software & Integration lab at the Italian National HPC Centre (ICSC) and leadership in the OpenScience working group at Torino. His advising includes Iacopo Colonelli, whose thesis won CINI’s 2023 best award. He actively engages in EU projects, workflow systems, and standards for hybrid computing environments. Aldinucci’s labs and collaborations drive innovations in HPC portability, energy efficiency, and AI scalability.
Dr. Carson Kai-Sang Leung is a Full Professor in Computer Science at the University of Manitoba's Faculty of Science. He founded and directs the Database & Data Mining Lab. His research focuses on big data science, data mining, machine learning, health informatics, and visual analytics. He holds SMIEEE and SMACM fellowships, reflecting his contributions to the field. Education: B.Sc., M.Sc., and Ph.D. from the University of British Columbia (UBC). Research interests include human-centered exploratory data mining, image databases, and scalable algorithms. He emphasizes user-driven constraints in mining processes and has developed techniques like the segment support map and OSSM for optimized frequency counting. His work on subimage queries in large image databases addresses real-world challenges in visual data retrieval. Publications span data mining, healthcare analytics, and transportation systems. His lab collaborates on projects like visual analytics for motor vehicle accidents and environmental data science for smart cities. He is affiliated with institutions such as the Institute of Industrial Mathematical Sciences (IIMS) and TRLabs. Key awards: Senior Member of IEEE (SMIEEE) and Senior Member of ACM (SMACM).
Dr. Luke Tredinnick is a Reader in Media, Information, and Communications at London Metropolitan University, serving as Course Leader for the Media and Communications BSc program. He holds editorial roles for the Sage journal Business Information Review and the Edinburgh University Press journal Journal of Library and Information History . His academic background includes a BA in English and American Literature from the University of Kent, an MSc in Information Science from City University London, and a PhD in Media and Communications from London Metropolitan University. His research focuses on digital culture, digital history, and information theory, with specializations in post-structuralist methodologies and semiotics. Tredinnick has authored three books, including Digital Information Culture (2008) and Digital Information Contexts (2006), and has published widely on topics such as complexity theory, artificial intelligence, information security, and social media. He is a member of the Media, Culture, and Communications Association (MECCSA) and a Fellow of the Higher Education Academy (FHEA). Tredinnick’s recent work examines trends in information warfare, ubiquitous information systems, and the evolving role of technology in business contexts. His contributions to the field span academic publications, editorial leadership, and keynote presentations on digital transformation and ethical information practices.
Dr. Muhammad M. Sherif is an Assistant Professor in the Department of Civil, Construction, and Environmental Engineering at the University of Alabama at Birmingham (UAB), part of the School of Engineering. He joined UAB in Fall 2019 after completing his Ph.D. at the University of Virginia and M.S. at Carnegie Mellon University, both in structural engineering. His research focuses on smart materials, structural systems, and machine learning applications in civil infrastructure. He is particularly interested in additive manufacturing for construction and the development of innovative materials like engineered cementitious composites. Education: B.S., United Arab Emirates University M.S., Carnegie Mellon University Ph.D., University of Virginia Research Interests: Dr. Sherif’s work spans material characterization, machine learning models for structural analysis, and the integration of advanced materials into infrastructure systems. He explores topics like crack detection using UAVs, superelastic shape memory alloys, and multi-objective optimization in welding processes. His Advanced Materials and Smart Infrastructure Systems (AMSIS) lab emphasizes interdisciplinary approaches to solving civil engineering challenges. Publications: His recent work includes studies on UAV-based pavement crack detection, machine learning for concrete strength prediction, and optimization of tube-to-tubesheet joints. These reflect trends toward AI-driven solutions and sustainable material innovations. Advising: He actively mentors students in multidisciplinary research projects, emphasizing self-motivation and innovation. His lab collaborates on topics like composite materials, structural health monitoring, and infrastructure resilience. Labs/Teams: His AMSIS lab at UAB focuses on advancing smart materials and infrastructure systems through cutting-edge research and collaboration.
Dr. Christopher Collins is a Professor of Computer Science at Ontario Tech University, leading the Visualization for Information Analysis Lab (vialab). He holds a PhD from the University of Toronto (2010) and focuses on interdisciplinary research in information visualization, human-computer interaction, and natural language processing. His work addresses challenges in information overload, text analytics, and novel interfaces such as touch, pen, VR/AR. Collins' research has been featured in top-tier venues like ACM CHI and IEEE Transactions on Visualization and Computer Graphics, earning honorable mentions and over $3M in funding as sole PI. He serves on the IEEE VIS Executive Committee and Board of Governors at Ontario Tech University. Education: PhD in Computer Science, University of Toronto (2010) MSc in Computer Science, University of Toronto (2004) BSc (Hons) in Computer Science, Memorial University (2001) Research Interests: Collins' work spans information visualization , pen+touch interfaces , visual analytics , and text-driven systems . He explores how interactive technologies can democratize complex data analysis, particularly in education, healthcare, and creative domains. Recent projects include gaze-driven learning tools, context-aware camera interfaces, and bias-mitigating product review analysis. Awards: ACM CHI Honorable Mention Award IEEE VIS Honorable Mention Award Grants & Impact: Secured $3M+ in research funding. Media coverage includes New York Times and CBS Sunday Morning for innovations in visualization and text analytics. Teaches courses in human-computer interaction, computer graphics, and information visualization. Labs & Collaborations: vialab develops tools like Lexichrome , ConToVi , and NeuroSight . Active in IEEE Visualization and ACM Interactive Media communities. Collaborates with academia and industry globally.
Natesh Pillai is a Professor in the Department of Statistics at Harvard University and a Distinguished Engineer at LinkedIn, focusing on Responsible AI. He holds a Bachelors from IIT Madras, a PhD from Duke University's Department of Statistical Science (2008), and completed a postdoc at the University of Warwick's CRiSM (2008-2010). His research spans applied probability, computational methods, MCMC theory, algorithmic fairness, and climate science. He serves on editorial boards for journals like SIAM Journal on Mathematics of Data Science and Harvard Data Science Review . Key awards include the 2018 Young Statistical Scientist Award and 2021 Fellowship in the Institute of Mathematical Statistics. His work emphasizes bridging theory and practice, with contributions to statistical methodology, causal inference, and scalable computational techniques. Recent collaborations include industry roles at Amazon (2021-2023) and interdisciplinary climate science projects analyzing agricultural yield predictability. Education: Bachelor's: Indian Institute of Technology (IIT) Madras PhD: Duke University, Department of Statistical Science Research Focus: MCMC mixing times, Bayesian methodology, reinforcement learning, climate data modeling Publications emphasize algorithmic efficiency, fairness in AI, and probabilistic frameworks for complex systems. His lab integrates theoretical rigor with real-world applications, including climate modeling and healthcare analytics.
Dr. Andrew Lin is a Senior Lecturer and School Director of One University at the University of Sheffield's School of Biosciences. He holds a PhD from the University of Cambridge and a BA in Biology from Harvard University. His career includes roles as a Lecturer (2019-2022), Vice-Chancellor’s Fellow (2015-2019), and Postdoctoral Fellow at the University of Oxford (2009-2015). Research focuses on how the brain encodes sensory information for memory formation, using Drosophila's olfactory system as a model. Key areas include sparse coding in Kenyon cells, synaptic inhibition/excitation balance, and neural circuit dysfunction links to epilepsy. Teaching includes modules like BMS11004 Introduction to Neuroscience and BMS248 Neural Circuits, Behaviour and Memory. He has secured grants from the European Research Council, BBSRC, and Wellcome Trust. Professional memberships include the FENS-Kavli Network and BBSRC Pool of Experts. Lab research employs techniques like in vivo two-photon imaging, electrophysiology, and genetic manipulation. PhD opportunities are available in neural circuitry and sensory processing.
Evimaria Terzi is a Professor and Department Vice Chair at Boston University (BU), affiliated with the Data Management Lab@BU. Her research focuses on algorithmic data mining with applications in network analysis, recommendation systems, ranking, and clustering. She holds a PhD from the University of Helsinki and has held prior roles at IBM Almaden Research Center (2007–2009) and the Helsinki Institute for Information Technology (HIIT) before 2007. Her work spans theoretical and applied domains, including team formation algorithms, fairness in AI, and large language model evaluation. Notable contributions include studies on LSM tree optimization, counterfactual explanations for auditing fairness, and the dynamics of memorization in LLMs. Her recent publications emphasize flexibility in database systems and ethical AI practices. Evimaria’s research has been recognized through her contributions to conferences like WSDM and KDD, where she has served in organizing roles. The themes of her work consistently bridge algorithmic innovation with real-world applications in social networks, healthcare, and collaborative systems.
Thao (Vicky) Nguyen is a Professor of Mechanical Engineering at Johns Hopkins University, with a secondary appointment in the Department of Materials Science and Engineering. She is co-Deputy Director of the Hopkins Extreme Materials Institute (HEMI). Her research focuses on biomechanics of soft engineering and biological materials, including adaptive polymers, fracture mechanics, and ocular biomechanics related to glaucoma. Key collaborators include the National Eye Institute and National Science Foundation. Nguyen holds a B.S. from MIT (1998), and M.S. and Ph.D. from Stanford (2000, 2004). She previously worked at Sandia National Laboratories. Awards include the James R. Rice Medal (2025), NSF CAREER Award, and multiple ASME honors. Her lab integrates experimental and computational approaches, with notable work on shape-memory polymers and scleral biomechanics. Research interests include collagen growth, liquid crystal elastomers, and architected materials. She leads studies on optic nerve head mechanics, funded by DOD, NEI, and BrightFocus. Nguyen serves on editorial boards for ASME journals and professional societies.
Noura Howell is an Assistant Professor in the School of Literature, Media, and Communication at the Georgia Institute of Technology. Her work focuses on ethical AI, emotion AI, and design futuring, emphasizing inclusivity and critical reflection through artistic and technical explorations. She holds a PhD in Information & Management Systems from UC Berkeley and a BS in Engineering from Olin College. Research interests include biosensing technologies, queer/crip design methodologies, and the intersection of embodiment with emerging technologies. Notable projects include the Future Feelings Lab, which critiques emotion AI through participatory audits and fabulative design practices, and investigations into thermal feedback systems and Sufi spiritual practices mediated by technology. Awards include an NSF CAREER Award for reimagining emotion AI, a Google TensorFlow Faculty Award for educational outreach, and the Ralph E. Powe Junior Faculty Enhancement Award. Teaching spans computational media, interaction design, and design futuring courses. Her lab explores speculative design through projects like the Heart Sounds Bench (life-affirming biosensing) and Salaam, an inflatable sculpture addressing Islamophobia. She has collaborated on interdisciplinary STEAM education initiatives like PREMIER artist residencies.
Marina Papatriantafilou is an Associate Professor in the Department of Computer Science and Engineering at Chalmers University of Technology and University of Gothenburg. Her research focuses on distributed computing, fault-tolerance, parallel algorithms, and concurrency control. She has contributed to methods for fault-tolerant distributed systems, visualization tools for distributed algorithms, and scalable overlay networks. Her academic roles include teaching advanced courses on distributed systems, computer communication, and operating systems. She advises graduate students in areas like distributed algorithms and parallel computing. Key research interests include lock-free synchronization, memory reclamation, and self-stabilizing systems. She has authored over 100 publications in top-tier conferences and journals, with recent work on data streaming frameworks, energy-sharing optimization, and vehicular network processing. Professional involvement includes roles in program committees for conferences like OPODIS, SWAT, and SSS, plus membership in research evaluation boards for Swedish and European funding agencies. She pioneered educational tools like the Lydian environment for distributed algorithm visualization.
Dr. Tony Stockman is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. His teaching focuses on Database Systems, Interaction Design, and Semi-structured Data Modelling across undergraduate and postgraduate programs. His research interests include Human-Computer Interaction, Auditory Displays, and Data Sonification, with a strong emphasis on accessibility and cross-modal interfaces. Dr. Stockman has contributed to over 100 publications, exploring topics such as biofeedback systems, assistive technologies for visually impaired individuals, and collaborative design methodologies. His work frequently bridges technical innovation with user-centric design principles. Notable projects include the development of non-visual navigation tools like the Audiom web-based map viewer and co-designed haptic wearables for music synchronization. His research also addresses challenges in education technology, such as dyslexia screening through serious games.
Anne McLaughlin is a Professor in the Department of Psychology at North Carolina State University, affiliated with the College of Humanities and Social Sciences. She directs the LACElab (Learning, Aging, and Cognitive Ergonomics), focusing on human factors, cognitive aging, and technology usability. She holds a Ph.D. in Engineering Psychology from Georgia Tech (2007) and has been at NC State since 2007. Her education includes a B.A. in Psychology and English Literature from Trinity University (1998), an M.S. in Engineering Psychology from Georgia Tech (2003), and her Ph.D. from the same institution (2007). Her research integrates cognitive science principles with real-world applications, emphasizing aging populations and technology design. Key research interests include cognitive aid design, augmented/virtual reality applications, human-robot interaction, and medical device usability. Recent work explores diminished reality techniques for attention management, trust dynamics in autonomous systems, and veterinary patient safety culture. Her articles highlight trends in human-centered technology development, particularly addressing individual differences in attention control, automation trust, and healthcare system optimization. She advocates for inclusive design principles to enhance older adults' engagement with technology and improve medical screening accessibility. McLaughlin’s work bridges academic research and practical implementation, with collaborations in healthcare, robotics, and educational technology. Her lab’s focus on aging-related challenges underscores her commitment to improving quality of life through human-centered solutions.
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