Dr. Thomas A. Hughes is an Associate Professor of Cancer Biology at the University of Leeds and Professor of Biosciences at York St John University. As a Group Leader at the Leeds Institute of Medical Research, he focuses on gene regulation, tumour microenvironment, and nanomedicine approaches to improve cancer outcomes. Specializes in breast cancer, colorectal cancer, and rare diseases Develops therapeutic strategies using microRNAs and biomarkers Collaborates with clinicians, engineers, and chemists for translational research His research integrates molecular pathology with clinical data through partnerships with Leeds NHS Trusts, aiming to identify novel biomarkers and targets for therapy. Recent work emphasizes cholesterol metabolism, oxysterol signaling, and nanomedicine-based drug delivery systems. Key contributions include: Over 80 peer-reviewed publications in cancer biology and molecular therapeutics Leadership in MSc programs in Molecular Medicine and Cancer Biology and Therapy Extensive experience in grant review, editorial work, and doctoral supervision Scientific awards include Fellowship of the Higher Education Academy. His lab has mentored 26 doctoral students and numerous alumni in academia, clinical practice, and industry.
Michael S. Horn is a Professor at Northwestern University with a joint appointment in Computer Science and the Learning Sciences. He directs the Tangible Interaction Design and Learning (TIDAL) Lab and coordinates the Learning Sciences PhD Program. His work focuses on leveraging interactive technology to design innovative learning experiences, such as tangible programming languages (e.g., Tern) and music-coding platforms (e.g., TunePad). He holds a PhD from Tufts University and has collaborated with institutions like the California Academy of Sciences and the Museum of Science, Boston. Education: PhD in Computer Science, Tufts University MS in Computer Science, Tufts University BS in Computer Science, Brown University Research Interests: Dr. Horn explores how emerging technologies can create engaging learning environments. His projects include museum exhibits (e.g., DeepTree, Build-a-Tree), educational tools for computational literacy (e.g., TunePad, Strawbies), and collaborative design with educators. Recent work emphasizes integrating music and coding to foster computational thinking. Publications: His recent work addresses computational thinking in STEM education, AI-driven qualitative analysis, and hybrid music-coding practices. Themes include equitable participation, teacher professional development, and immersive AR/VR tools for learning. Awards: Recipient of the 2018 Edith Ackermann Award for innovative work in child-computer interaction. His research has led to commercial products like Osmo Coding and Kibo Robotics. Grants & Labs: Principal investigator on NSF grants (e.g., #1612619, #1451762) and collaborator with labs like the Center for Connected Learning (CCL) and the Collaborative Technology Laboratory (CollabLab).
Aysegul Gunduz, Ph.D., is a Professor and Fixel Brain Mapping Professor at the University of Florida's Herbert Wertheim College of Engineering, Department of Biomedical Engineering. She leads the Brain Mapping Laboratory, focusing on neural networks and clinical translation for neurological disorders. Her work integrates electrophysiology, bioimaging, and neuromodulation to develop diagnostic and therapeutic systems for conditions like Parkinson’s disease, epilepsy, movement disorders, and stroke. Education: B.S., Electrical Engineering, Middle East Technical University (2001) M.S., Electrical Engineering, North Carolina State University (2003) Ph.D., Electrical Engineering, University of Florida (2008) Post-doctoral Fellowship in Neurology, Albany Medical College (2011) Research interests include human brain mapping, closed-loop deep brain stimulation (DBS), neuromodulation strategies for movement disorders, and wearable sensor technologies for neurological monitoring. Her lab emphasizes translational research, bridging basic science with clinical applications to improve patient outcomes. Awards include the BMES Fellowship (2024), AIMBE Fellowship (2022), and PECASE (2019), reflecting her leadership in neural engineering. Her articles explore cutting-edge topics like DBS efficacy, neural network dynamics, and ethical considerations in neural device research. Grants and collaborations focus on advancing adaptive DBS and brain-computer interfaces. She mentors students in neuroengineering and advocates for equitable participation in clinical research. The Brain Mapping Laboratory actively engages in multidisciplinary projects with neurologists, surgeons, and industry partners. Future work includes optimizing closed-loop systems for Tourette syndrome and Parkinson’s disease, developing open-source neuroimaging tools, and expanding wearable sensor applications for real-time neurological monitoring.
Yuri Bazilevs is the E. Paul Sorensen Professor of Engineering at Brown University's School of Engineering and Co-Director of the Mechanics of Undersea Science and Engineering Center. His research focuses on computational mechanics, isogeometric analysis, fluid-structure interaction, and high-performance computing. Prior to Brown, he held positions at UC San Diego, where he advanced to Full Professor in 2014 after a rapid tenure. He earned his PhD in 2006 and postdoc training in computational engineering at UT Austin's ICES. Research interests span computational fluid dynamics, solid mechanics, and advanced discretization methods like isogeometric analysis (IGA) and meshfree approaches. He has developed novel formulations for complex phenomena such as underwater explosions, composite material failure, and hypersonic flow dynamics. His work integrates cutting-edge numerical methods with practical engineering applications in aerospace, energy, and biomedical systems. Recent publications highlight advancements in IGA for architected materials, RKPM-based crack modeling, and stabilized formulations for compressible flows. His contributions bridge theoretical mechanics with computational innovation, addressing challenges in multiphysics coupling and large-scale simulations. Collaborations span academia and industry, emphasizing practical validation and real-world impact. Bazilevs' expertise includes variational multiscale methods, peridynamics for fracture mechanics, and immersive particle methods for fluid-structure interaction. His work has been applied to wind turbine aerodynamics, gas turbine optimization, and cardiovascular flow analysis. He actively contributes to computational infrastructure development, such as the tIGAr software framework for IGA automation.
Mohammad Mohammadi Amiri serves as an Assistant Professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI), appointed in Fall 2023. His research focuses on advancing artificial intelligence through strategic data utilization, with emphasis on large language models, data valuation, federated learning, and deep learning. Previously, he held postdoctoral appointments at Princeton University and MIT Media Lab, building on his strong educational foundation from Imperial College London, University of Tehran, and Iran University of Science and Technology. Education: Ph.D. in Electrical and Electronic Engineering, Imperial College London (2019) - Best Ph.D. Thesis Award recipient M.Sc. in Electrical and Computer Engineering, University of Tehran (2014) - Ranked 1st among all M.Sc. students B.Sc. in Electrical Engineering, Iran University of Science and Technology (2011) - Ranked 1st among all B.Sc. students Dr. Amiri's research centers on optimizing artificial intelligence systems through innovative data strategies. His work addresses critical challenges in large language models including efficiency, memory usage, alignment, and reasoning capabilities. In data valuation, he develops principled methods to quantify data worth for fair trading platforms. His federated learning research tackles privacy concerns, heterogeneous data distribution, and communication overhead in decentralized environments. The deep learning component explores theoretical foundations to improve model interpretability and robustness. Analysis of his recent publications reveals a strong focus on making AI systems more efficient and accessible, with particular emphasis on large language model optimization, federated learning advancements, and data valuation frameworks. His work bridges theoretical foundations with practical applications in wireless communications and distributed computing environments. Scientific Awards: IEEE Communications Society Young Author Best Paper Award (2022) Best PhD Thesis Award from IEEE Information Theory Chapter of UK and Ireland (2019) Eryl Cadwallader Davies Prize for Outstanding PhD Thesis (2019) EEE Departmental Scholarship at Imperial College London (2015-2019) Ranked 1st among M.Sc. students at University of Tehran (2014) Ranked 1st among B.Sc. students at Iran University of Science and Technology (2011) Dr. Amiri actively mentors graduate students, currently supervising five Ph.D. candidates and one M.Sc. student working on efficient LLM fine-tuning, inference, and storage. His research has attracted significant attention, evidenced by numerous keynote invitations at prestigious institutions including Bell Labs, MIT, King's College London, and various IEEE conferences. He serves on program committees for major conferences including IEEE Globecom and ICC, demonstrating his growing influence in the academic community. His research group operates at the intersection of machine learning and wireless communications, developing innovative solutions for resource-constrained environments while addressing fundamental theoretical challenges in AI systems. Current projects focus on making advanced AI more scalable and accessible through efficiency improvements in model training and inference.
Laurent DUPONT is a Research Engineer and Co-coordinator of the IUVTT Master’s program at ENSGSI (École Nationale Supérieure de Géologie et de Sciences Industrielles), part of the Groupe INP in Nancy, France. He also serves as Scientific Manager of the Lorraine Fab Living Lab. His work focuses on user-driven innovation, smart and sustainable territories, collaborative engineering, and immersive environments. He holds a PhD in Industrial Systems Engineering from INPL (2009), a DEA (2004), and a degree in Industrial Systems Engineering (2003) from ENSGSI. Research interests include innovation lab strategies, open innovation spaces, territorial resilience, and digital twin applications in manufacturing. He leads projects like INEDIT, exploring co-design frameworks and circular economy solutions. His articles highlight trends in collaborative innovation networks, systemic impact mapping, and the integration of extended reality in industrial contexts. Key contributions include frameworks for evaluating territorial resilience and tools for monitoring innovation lab networks. He has been involved in initiatives such as the DHDA Project for resilience assessment and the Smagrinet project on smart grid training. His work bridges academia and practice through participatory methods and cross-sector collaborations. Current projects emphasize Industry 5.0, open manufacturing, and community-driven innovation.
Jonathan Shihao Ji is an Associate Professor in the School of Computing at the University of Connecticut (UConn), leading the Intelligent Systems Lab. He holds a Ph.D. in Electrical and Computer Engineering from Duke University and previously served as an Associate Professor at Georgia State University and Director of the DoD Center of Excellence (CiARE). His research focuses on deep learning applications in computer vision, NLP, robotics, and high-performance computing, with over 50 publications in top venues like CVPR, NeurIPS, and IEEE journals. He has secured grants from NSF, NIH, DoD, and industry partners including VMware and Nvidia. His work emphasizes efficient algorithms for large-scale data processing, parameter-efficient model fine-tuning (e.g., VB-LoRA), and 3D perception benchmarks for UAVs (UAV3D). Notable contributions include sparse network optimization (Dep-L0), energy-based models (M-EBM), and robust defenses against adversarial attacks (Defense-VAE). He is a Senior Member of IEEE and has developed open-source tools like Parallel Word2Vec and WordRank. Recent projects include accelerating Llama2 models on FPGAs (LlamaF) and improving text-to-image synthesis via contrastive learning. His research spans theoretical advancements and practical applications, with industry collaborations in healthcare, robotics, and embedded systems.
Michael Smith is the McCosh Professor of Philosophy at Princeton University. He holds a DPhil from Oxford University (1989) and has been a faculty member since 2004, previously at the Australian National University. His research focuses on ethics, moral psychology, philosophy of mind, political philosophy, and philosophy of law. Smith’s work integrates constitutivist theories of practical reason with analyses of moral agency. He has contributed to debates on moral rationalism, the nature of reasons for action, and the relationship between rationality and normativity. Education: MA, Monash University (1980); BPhil (1983), DPhil (1989), University of Oxford Smith’s scholarship emphasizes the interplay between ethical theory and psychological explanations of agency. Recent publications explore topics like carbon capture technologies, cultural clashes in moral reasoning, and probabilistic forecasting in oceanography. His philosophical contributions address foundational questions in meta-ethics, including the ‘moral problem’ and the implications of constitutivism for normative frameworks. He advises on interdisciplinary projects at the intersection of philosophy and emerging technologies. Notable research trends include applying philosophical analysis to environmental ethics and developing frameworks for resolving moral dilemmas through rational agency models. His work often bridges analytic philosophy with empirical inquiries in psychology and social science.
Dr. Alireza Nili is a Senior Lecturer in Service Science at QUT's School of Information Systems within the Faculty of Science. His expertise spans digitization of customer-centric services, AI/chatbots, IoT/IIoT, and sustainable technologies. He holds a PhD from Victoria University of Wellington and has coordinated large-scale courses like IT Systems Design (IFB103), achieving top teaching scores. Nili's research focuses on service ecosystems, trust in digital services, and public/retail sector innovations. He has secured over $1.4M in industry grants for projects involving Cisco, Amazon, and Services Australia. His awards include the 2023 Educator of the Year and multiple top conference paper recognitions. Nili supervises PhD students at Level 3 mentoring status and contributes to major conferences as track chair/associate editor. Research highlights include frameworks for chatbot governance, IOT in agriculture, and AI ethics. His work appears in IEEE Software , Communications of the ACM , and MIT Sloan Management Review . Current projects address consumer trust in AI technologies and spatial data systems. Nili's interdisciplinary approach combines design science with empirical methodologies to bridge theory and practice in digital service innovation.
Mathew Thomson is a Professor of History at the University of Warwick, specifically within the Department of History under the Faculty of Arts. He holds a BA in History from University College London (1987) and a D.Phil. from the University of Oxford (1992). His research focuses on the cultural and social history of medicine, eugenics, and psychological practices in 20th-century Britain. He has been a Wellcome University Award Holder at the University of Sheffield (1993-1998) and has held roles such as Lecturer and Reader at Warwick (1998-2015) before his current professorship. Thomson's teaching includes undergraduate modules like 'The Cultural History of the NHS' and 'Eugenics Lecture,' as well as postgraduate courses on medical humanities. His publications, including books like *The Problem of Mental Deficiency* (1998) and *Psychological Subjects* (2006), explore themes of mental health policy, eugenics, and the intersection of psychology with societal structures. His recent work examines the NHS's cultural representation and post-war childhood landscapes. He has contributed to public engagement through BBC documentaries (e.g., *The NHS: A People's History*), museum consultations (V&A Museum of Childhood), and policy initiatives like the British Academy Childhood Policy Programme. His research on mental deficiency policies, wartime mental health, and the history of psychological practices underscores his interdisciplinary approach to societal and medical history.
Preet Singh is a Professor and Associate Chair for Graduate Studies in the School of Materials Science and Engineering at Georgia Tech, with affiliations to the College of Engineering. His research focuses on corrosion science, electrochemistry, and environmental degradation of materials, particularly metals and alloys. Prior to joining Georgia Tech in 2003, he was a faculty member at the Institute of Paper Science and Technology (IPST), where he investigated corrosion issues in the pulp and paper industry. Professor Singh's work explores fundamental mechanisms of material degradation in industrial environments, aiming to develop mitigation strategies against environment-induced failures. Key research areas include corrosion fatigue, hydrogen embrittlement, stress corrosion cracking, and oxidation behavior. His group employs experimental approaches to study material reliability under varying chemical and mechanical conditions. Recent publications demonstrate interdisciplinary collaboration across oncology, agriculture, and energy systems, reflecting broad applications of materials science principles. Research trends show increased focus on biomedical materials and sustainable technologies alongside core corrosion studies. Professor Singh advises graduate students including Abdullah Alzubail, Yousif Al Rabie, Sai Shreeya, Yara, and Sean Li. He directs the Corrosion and Materials Reliability Laboratory (CMCRL), which partners with industry to solve practical engineering challenges related to material performance.
Wenping Wang is a Professor in the Department of Computer Science & Engineering at Texas A&M University, part of the College of Engineering. His research focuses on computer graphics, computer vision, geometric modeling, and visualization. He holds Fellowships from ACM and IEEE, and has received notable awards including the 2021 AsiaGraphics Outstanding Technical Contributions Award and the 2017 John Gregory Memorial Award. Wang's educational background includes a Ph.D. from the University of Alberta and M.Eng. and B.Sc. degrees from Shandong University. His work spans advancements in neural implicit surfaces, 3D reconstruction, and medical imaging applications such as orthodontic treatment prediction. He has authored numerous influential papers in top-tier conferences like SIGGRAPH and journals like ACM Transactions on Graphics. His research interests emphasize bridging geometric modeling with machine learning, particularly in neural rendering, surface parameterization, and medical visualization. Recent projects include developing frameworks for automatic tooth alignment and high-fidelity 3D geometry generation. Wang's contributions have significantly impacted both theoretical foundations and practical applications in computer graphics.
Aleksandar Kostic is a Lecturer in the Department of Architecture and Built Environment at South East Technological University (SETU), where he also serves as Lead Researcher. He holds a PhD from University College Dublin, awarded in 2022, and is actively contributing to the academic and professional architecture community. PhD in Design Theory, University College Dublin (2022) His research lies at the intersection of philosophy and architectural design, with a strong focus on design theory, epistemology, ethics, and aesthetics. He explores fundamental questions such as aporia (intellectual impasses) in design, the influence of Platonic philosophy, and the ethical responsibilities of architects. His work emphasizes critical thinking and philosophical inquiry in architectural practice and education. The trends in his publications reveal a consistent engagement with philosophical concepts applied to architectural problems. From examining 'aporetic' design challenges to analyzing Plato’s views on expertise, his research bridges abstract thought and practical design. Recent works continue this trajectory, addressing ethical values, non-material aspects of design, and the role of contradiction in innovation. Nomination for MIES EU Award for Architecture (2009) Aleksandar Kostic advises PhD students and is actively involved in research dissemination through publications, peer-review, and conference organization. He serves on the steering committee of the All Ireland Architecture Research Group and is a member of the Centre for Platonic Studies at Trinity College Dublin and the Royal Institute of the Architects of Ireland. His peer-review activities include journals such as She JI and Building Material . He is a key member of the Architecture Research Group at SETU and collaborates across disciplines, particularly with philosophy. His upcoming activity includes organizing the 'Ethics in Architecture' conference in 2025, highlighting his leadership in integrating ethical discourse into architectural research.
Prof. Gisela Detrell is a Professor of Human Spaceflight Technology at the TUM School of Engineering and Design, Technical University of Munich. She specializes in developing technologies for astronautical spaceflight, including life support systems (e.g., microalgae photobioreactors), mission simulations (e.g., Mars/Moon concepts), and virtual reality tools for astronaut training. Her work bridges engineering, biotechnology, and interdisciplinary collaboration. Education: Bachelor/Master in Aerospace Engineering at the Polytechnic University of Catalonia (UPC) PhD from the University of Stuttgart and UPC (2015), focusing on reliability analysis of life support systems for long-duration space missions Research Interests: Prof. Detrell’s research emphasizes sustainable life support systems for extraterrestrial habitats, VR-driven astronaut training, and interdisciplinary design approaches for space stations. Her photobioreactor studies explore algae-based solutions for oxygen and food production on lunar/mars bases, while simulations address mission realism and team performance under extreme conditions. Articles Overview: Her publications span VR docking simulators, ISS-based photobioreactor experiments, and biofiltration systems for closed-loop life support. These reflect a focus on practical, scalable technologies for long-term space habitation. Awards/Grants: No specific honors or grants listed in the text. Her academic contributions are highlighted through her professorship and research group leadership. Labs/Teams: She previously led the research group at the Institute of Space Systems in Stuttgart and currently heads the Human Spaceflight Technology group at TUM.
Dr. Alain Bonneville is a Lab Fellow and Geophysicist at Pacific Northwest National Laboratory (PNNL) and holds a Courtesy Professor appointment at Oregon State University's College of Earth, Ocean, and Atmospheric Sciences. With extensive experience in geological storage of CO2, geothermal energy, and geophysical monitoring techniques, Dr. Bonneville leads diverse research projects that bridge fundamental science and practical applications for energy and environmental challenges. Dr. Bonneville's educational background includes: PhD in Geophysics from the University of Montpellier, France MS in Petroleum Geophysics from IFP-School, Paris, France BS in Geology from the University of Lyon, France Dr. Bonneville's research spans several critical areas in Earth sciences and energy systems. His work on geothermal energy focuses on super-hot enhanced geothermal systems (EGS), site characterization, monitoring, and stimulation fluids. In geological CO2 storage, he investigates project management, site characterization, numerical modeling, and monitoring methods using potential fields and remote sensing. His expertise in geophysical methods includes heat flow measurements, gravity surveys, muon tomography development for borehole deployment, and remote sensing applications. Additional research areas encompass marine heat flow instrumentation development, thermal monitoring of active volcanoes, and intraplate volcanism studies in the Indian and Pacific Oceans. Dr. Bonneville has received significant recognition for his contributions to science, including: Membership in the Washington State Academy of Sciences Lab Fellow position at Pacific Northwest National Laboratory Executive Committee membership on the U.S. National Risk Assessment Partnership Scientific Committee membership at IFP-Energies Nouvelles, France He also holds two U.S. patents related to electrophilic acid gas-reactive fluids for enhanced fracturing and recovery of energy producing materials. Throughout his career, Dr. Bonneville has led significant research initiatives, including the PNNL Carbon Sequestration Initiative (2009-2013) and the European Marie Curie Research Training Network on Greenhouse Gas Removal (GRASP), which involved 14 academic and industrial institutions across 7 countries and supported 35 PhD students and post-docs. His work on the FutureGen 2.0 project demonstrates his leadership in large-scale carbon storage site characterization and monitoring program design. Dr. Bonneville maintains active collaborations with research teams at PNNL's Environmental Molecular Sciences Laboratory and works closely with Oregon State University's geoscience researchers. His laboratory work focuses on developing novel instrumentation for geophysical monitoring, particularly in the areas of muon tomography for subsurface characterization and thermal monitoring systems for geothermal and carbon storage applications.
