Prof. Kerstin Vokinger is an Associate Professor at the Department of Health Sciences and Technology, ETH Zurich. Her research focuses on pharmaceutical economics, healthcare policy, AI in medicine, and regulatory science. She investigates drug pricing strategies, managed entry agreements, and the therapeutic value of medicines. Her work often compares policies between the US, Europe, and Switzerland, addressing issues like cancer drug pricing, orphan drug designation, and AI-based medical devices' regulation. Key research areas include: Clinical trial outcomes and drug approval processes Health technology assessment and cost-effectiveness analysis Legal frameworks governing healthcare innovation Data privacy in medical research and AI applications Her recent articles analyze trends such as the 'cancer premium' in drug pricing, the impact of expedited approvals on therapeutic value, and global disparities in cancer drug access. She also explores regulatory challenges in AI-driven medical devices and the ethical implications of anonymized healthcare data. Prof. Vokinger collaborates with institutions worldwide to shape evidence-based health policies and improve drug affordability. Her work bridges legal, economic, and scientific dimensions of healthcare systems.
Aidan Hogg is an Assistant Professor/Lecturer in Computer Science at Queen Mary University of London (QMUL) and an Honorary Research Associate at Imperial College London. His primary affiliation is with the Centre for Digital Music (C4DM) and the School of Electronic Engineering and Computer Science at QMUL. He co-leads the Virtual, Immersive, Augmented and Binaural Audio Lab (VIABAL) . Education: PhD and MEng from Imperial College London, specializing in engineering and computer science disciplines. His research focuses on deep learning for spatial acoustics , immersive audio , and statistical signal processing with applications to speech and audio systems. Key areas include HRTF upsampling , speaker diarization , and acoustic localization . Grants: Secured funding such as the Online Speech Enhancement in Scenarios with Low Direct-to-Reverberant-Ratio grant (£65,621 from L-ACOUSTICS UK LIMITED, 2024–2025). His work bridges academia and industry, particularly in audio engineering and AI-driven audio solutions. Labs/Teams: Active in the Centre for Multimodal AI and collaborates with institutions like the Central Conservatory of Music, China. His research outputs include datasets like the SONICOM HRTF Dataset and contributions to conferences such as DAFX, ICASSP, and WASPAA.
Helge Rhodin is a full professor at Bielefeld University (since March 2024) and an affiliate at the University of British Columbia (UBC). His research focuses on advancing 3D computer vision, machine learning, and computer graphics to enable non-intrusive human-computer interaction, particularly in augmented reality (AR) and virtual reality (VR) environments. He previously held positions as an Assistant Professor at UBC, a postdoctoral researcher at EPFL, and a PhD candidate at the Max-Planck-Institute for Informatics under Christian Theobalt. Education & Career: PhD in Computer Science, Max-Planck-Institute for Informatics (2016) Postdoctoral Researcher, EPFL (2016–2020) Assistant Professor, UBC (2020–2024) Full Professor, Bielefeld University (2024–present) Research Interests: Rhodin’s work spans 3D human pose estimation, neural rendering, AR/VR applications, and generative models. Key contributions include real-time motion capture systems (e.g., XNect), self-supervised learning frameworks, and synthetic biomarker development for movement disorders. Publications: His work has been published at top venues like CVPR, ICCV, and SIGGRAPH, with notable achievements like the Best Paper Award at CRV 2023 and an IEEE VR Honorable Mention in 2019. Research trends emphasize human-centric computer vision and interdisciplinary applications in healthcare and sports analytics. Awards & Recognition: Best Paper Award at CRV 2023 IEEE VR Best Journal Paper Honorable Mention (2019) Advising & Labs: He leads a multidisciplinary team at Bielefeld, previously mentoring over 30 students at UBC. His group focuses on developing open-source tools and frameworks for 3D vision and AR. Current research directions include mirror-aware neural humans and scalable neural rendering techniques.
Alejandro F. Frangi is the Bicentenary Turing Chair in Computational Medicine and Royal Academy of Engineering Chair in Emerging Technologies at the University of Manchester, with joint appointments in the School of Computer Science and School of Health Sciences. He serves as Director of the Christabel Pankhurst Institute and leads the NIHR Manchester Biomedical Research Centre's Digital Infrastructure theme. His education includes a PhD in Medicine from Utrecht University (2001) and an undergraduate degree in Telecommunications Engineering from Universitat Politècnica de Catalunya (1996). He holds honorary positions at KU Leuven and is an Alan Turing Institute Fellow. Professor Frangi's research bridges medical image analysis and computational modeling, with emphases on: Machine learning for population imaging In silico clinical trials for medical devices Computational physiology in cardiovascular and neurosciences Statistical methods for image-based biomarkers His recent publications demonstrate strong focus on AI-driven medical image reconstruction, computational modeling of vascular diseases, and virtual clinical trial methodologies. Research trends show consistent innovation in deep learning architectures for 3D medical image processing. Awards and honors include: IEEE Engineering in Medicine and Biology Technical Achievement Award (2021) Fellow of Royal Academy of Engineering (2023) ERC Advanced Grant recipient President's International Initiative Award from Chinese Academy of Science He has supervised 28+ PhD students to completion and currently leads multiple major grants including a £2.7m Royal Academy of Engineering Chair award. His laboratory develops open-source platforms (GIMIAS, MULTI-X) and has spun off three companies (GalgoMedical, adSilico). As Director of the Christabel Pankhurst Institute, he oversees interdisciplinary teams working on health technology innovation. He founded the InSilicoUK Innovation Network to advance regulatory science for in silico methods.
Melissa J. Fazzari is an Associate Professor in the Department of Epidemiology & Population Health (Biostatistics) at Albert Einstein College of Medicine. Her research focuses on biostatistical methodologies including meta-analysis of rare events, longitudinal study design, clinical trials, and the analysis of complex genomic/epigenomic data using machine learning approaches like Random Forest and neural networks. Her work spans diverse areas such as bone health, pediatric epidemiology, cancer genomics, and environmental health impacts. Key research interests include statistical consulting, predictive modeling, and the application of advanced computational methods to healthcare data. She has contributed to studies on vitamin D supplementation effects in elderly populations, postoperative outcomes of gynecologic surgeries, and neuropathic symptom analysis in World Trade Center disaster responders. Her publications reflect a multidisciplinary approach, addressing topics from bone metabolism to X-chromosome inactivation mechanisms. Collaborations with clinicians and researchers across disciplines highlight her role in bridging statistical rigor with clinical and biological questions.
Beatriz Blanco Besteiro is an Assistant Professor at the University of Santiago de Compostela's Higher Polytechnic School of Engineering, affiliated with the Department of Electronics and Computing and the GSI Group (Intelligent Systems Group). Her research focuses on computational modeling of tumor dynamics, ultrasound therapeutics, and biomedical engineering applications. She also explores educational methodologies like project-based learning in engineering curricula. She holds a Doctorate from the University of Granada (2023), with a thesis titled Modeling avascular tumor dynamics and low-intensity ultrasound therapeutics , advised by Dr. Guillermo Rus Carlborg and Dr. Juan Manuel Melchor Rodríguez. Her work bridges computational science and medical applications, including mechanotransduction studies and nondestructive material testing via ultrasonics. Her recent articles analyze therapeutic ultrasound effects on cancer stem cells, plagiarism detection in programming assignments, and tumor growth mechanics. Research trends emphasize interdisciplinary approaches combining biophysics with computational tools for medical and educational challenges. Blanco Besteiro contributes to the GSI Group's efforts in intelligent systems and has designed innovative engineering curricula using project-based learning frameworks. While no awards are explicitly listed, her active publication record reflects sustained research engagement in biomedical and educational technology domains.
Dr. Irwanda Laory is an Associate Professor in the School of Engineering at the University of Warwick, specializing in Structural Health Monitoring (SHM), damage detection, and intelligent infrastructure. He holds a BSc from Bandung Institute of Technology (Indonesia), an MSc from Bauhaus-Universität Weimar (Germany), and a PhD from EPFL (Switzerland). His research focuses on data interpretation methods, measurement system design, and computer-aided engineering for infrastructure resilience. Education: BSc Civil Engineering, Bandung Institute of Technology MSc Natural Hazard and Mitigation in Structural Engineering, Bauhaus-Universität Weimar PhD Swiss Federal Institute of Technology Lausanne (EPFL) Research emphasizes SHM techniques, Bayesian structural identification, and the integration of machine learning in civil infrastructure. Key contributions include thermal strain extraction for bridge assessment and anomaly detection using neural networks. His work spans smart materials, sensor networks, and sustainable construction practices. Publications highlight advancements in model-free data interpretation, damage detection algorithms, and infrastructure monitoring. Notable awards include the SHMII-8 Best Paper Award (2017). Grants and Projects: ENHANCE Erasmus+ Project (€1M, 2018) Warwick Impact Fund (£28.3k, 2015) Newton Fund Institutional Links Grant (£67.7k, 2016) Advises PhD students including Mr. Pamuncak (2017–2021) and oversees the Warwick SHM Group. Collaborates with institutions like the Warwick Institute for Science of Cities and the Center for Intelligent Infrastructure in Indonesia (IntelStruct).
Raluca Lefticaru is an Associate Professor in Computer Science at the University of Bradford's School of Computing, Software and Artificial Intelligence & Engineering (CSAI&E), within the Faculty of Engineering & Digital Technologies. She leads the BEng Software Engineering programme and holds a visiting researcher position at the University of Sheffield's Testing group. A Fellow of the Higher Education Academy (FHEA), she specializes in software testing methodologies, particularly model-based testing using evolutionary approaches, formal specification, and P systems verification. Her research interests span software testing, model-based testing, search-based software engineering, membrane computing, and formal verification. Recent professional activities include organizing conferences such as YISEC 2023, AIERC 2022, and A-MOST 2021, serving as a program committee member for SEFM 2025, ICTSS 2023, and ICSE 2022, and reviewing for WCCI 2022. She has held roles including Co-chair of YISEC 2023 and Communication Chair of CMC18 (2017). Raluca's work emphasizes interdisciplinary applications, from IoT security to medical imaging analysis. Her publications reflect contributions to testing frameworks for P systems, fault tree analysis, and AI-driven solutions for cyberbullying detection and industrial fire prevention. She actively contributes to academic journals in membrane computing, optimization, and software engineering. Awards: Fellow of the Higher Education Academy (FHEA) Key Projects: IoT safety-security integration, robotic system testing, and COPD self-management systems Conference Leadership: Organized over 10 international conferences since 2017
Associate Professor Cesar Ortega-Sanchez is affiliated with Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences (EECMS), where he holds the role of Associate Professor since 2005. He has served in leadership roles including Academic Lead of the Engineering Foundation Year (2015-2022), Associate Dean of Teaching and Learning (2013-2014), and Chair of IEEE WA Section (2016-2017). His expertise spans bio-inspired systems, embedded systems, robotics, and engineering education. Education: BEng (Hons) from the Metropolitan Autonomous University (Mexico), MSc from Brunel University (UK), and PhD from the University of York (UK). Specializes in curriculum design, assessment methodologies, and promoting student employability. Mentor of Curtin Robotics Club and IEEE Curtin Student Branch since 2009. Research Interests: Embedded systems, bio-inspired architectures, educational pedagogy, and indigenous content integration in engineering curricula. Over 60 publications in areas like FPGA-based assistive technologies, smart home systems, and energy storage monitoring. Awards include the 2015 Australian Office of Learning and Teaching Citation and M.K. Stott Prize (2000). Teaching roles include leading ELEN1000 (Electrical Systems) and ENGR1000 (Engineering Connections), with a focus on innovative teaching methods like project-based learning (e.g., 'Crazy Machine' lab projects). Active in educational committees at university and national levels.
W. Phil Evans is a Clinical Professor of Radiology at UT Southwestern Medical Center and Chief of its Breast Imaging Division, serving as Director of the Center for Breast Care. He earned a bachelor's in psychology from Trinity University and an M.D. from UT Southwestern. His career includes residency at Baylor University Medical Center and faculty roles since 1989, advancing to Clinical Professor by 2002. His research focuses on breast imaging advancements, including transitioning mammography to digital formats and integrating ultrasound for high-risk patients. He pioneered the Susan G. Komen Breast Center at Baylor, leading multi-institutional studies. Evans chairs professional organizations like the Society of Breast Imaging and the American College of Radiology. Awards include the Gold Medal Award (2015), Lifetime Service Award (American Board of Radiology), and repeated recognition as a Best Doctor in America since 2009. Education: Trinity University (B.A. Psychology), UT Southwestern (M.D.) Leadership: President of American College of Radiology (2009-2011), Society of Breast Imaging (2015 Gold Medal) Key Contributions: Digital mammography evolution, breast cancer screening protocols, first dedicated breast center in Texas Evans’ work bridges clinical practice and innovation, emphasizing early detection and patient care through imaging advancements. He maintains active roles in mentoring, education, and national cancer advocacy.
Dr. Vivian Genaro Motti is an Associate Professor at the Department of Information Sciences and Technology, George Mason University (GMU), where she leads the Human-Centric Design Lab (HCD Lab). Currently on sabbatical at the University of Lisbon's LASIGE until 2025, her research focuses on Human-Computer Interaction (HCI), Wearable Computing, and Usable Privacy. She investigates assistive smartwatches for neurodivergent adults, inclusive workplaces (NSF-funded), and smart home privacy. Her work combines participatory design, social media analytics, and qualitative analysis. Education: PhD in Computer Science, Catholic University of Louvain (Belgium) Masters in Computer Science, University of São Paulo (Brazil) Bachelor's in Biomedical Informatics, University of São Paulo Research Interests: Her expertise spans assistive technologies, mHealth, privacy in IoT, and inclusive design. She emphasizes participatory methods and has led projects funded by NSF, NIDILRR, and CCI. Recent work includes the NSF-funded "FW-HTF-RL" project fostering neurodiverse workplace success through wearables. Publications: Over 50 peer-reviewed articles, including work on wearable privacy, neurodivergent support systems, and smart home technologies. Recent trends highlight AI ethics, mental health monitoring via wearables, and inclusive employment frameworks. Awards: NSF Grant (2023) NIDILRR ACL Project Funding TeachAccess Award Commonwealth Cyber Initiative (CCI) Support Grants & Advising: Secured over $2M in grants; advised projects on accessible chatbots and privacy controls. Collaborates with industry and academia globally, including postdoc contributions to the NSF-funded Amulet project at Clemson University. Labs & Teams: Leads the HCD Lab, fostering interdisciplinary research in human-centric technology. Collaborates with institutions like Université catholique de Louvain and UFABC on neurodiversity and privacy initiatives.
Dr Michael Odetayo is a Principal Lecturer in Computer Science at Coventry University's School of Engineering and Computing. He serves as Course Director for BSc Software Engineering, BSc Network and Mobile Computing, and BEng Digital Forensics and System Security programs. With extensive experience across multiple institutions including De Montfort University and Ahmadu Bello University in Nigeria, he brings a global perspective to his academic work. His teaching portfolio covers diverse computer science topics from fundamental programming to advanced AI concepts. Dr Odetayo's educational background includes a PhD in Computer Science from the University of Strathclyde, an MSc and D.I.C in Computing Science from Imperial College London, and a BSc in Mathematics with Computer Science from Ahmadu Bello University. His academic journey reflects a strong foundation in both theoretical and applied computer science. Ph.D., Computer Science, University of Strathclyde, Glasgow M.Sc., Computing Science, Imperial College of Science and Technology, London D.I.C, Computing Science, Imperial College of Science and Technology, London B.Sc., Mathematics with Computer Science, Ahmadu Bello University, Samaru-Zaria, Nigeria His research spans multiple domains of computer science with particular emphasis on genetic algorithms, neural networks, and biometric security systems. Dr Odetayo has made significant contributions to healthcare informatics through his studies on HIV/AIDS in Lagos State, Nigeria, demonstrating the practical applications of computer science in public health challenges. His work bridges theoretical computer science with real-world implementation in developing countries. Analysis of his recent publications reveals a strong focus on biometric security systems, particularly image enhancement techniques for surveillance applications. He maintains an active research program in wireless networking protocols and has increasingly focused on educational technology applications, especially blended learning models in higher education. His work consistently demonstrates the application of intelligent systems to solve practical problems across diverse domains. As Workload and Timetabling Systems Coordinator, Dr Odetayo plays a significant administrative role within his department. While specific advising information isn't provided in the available materials, his position as Course Director for multiple programs suggests substantial involvement in student guidance and curriculum development. His research has secured attention in both academic and practical implementation contexts, particularly in Nigeria where he maintains strong research connections. Dr Odetayo's laboratory work appears to focus on biometric security systems development and testing, with particular attention to image processing algorithms for security applications. His research team has produced numerous publications on color enhancement, face detection, and content-based image retrieval for biometric applications. His work with Nigerian institutions suggests international collaboration on health informatics projects.
Dingchang Zheng is a Professor and Director of the Research Centre for Intelligent Healthcare. He specializes in medical device development, particularly in physiological measurements and bio-signal processing, with a focus on cardiovascular technologies, wearable devices, and IoT monitoring systems. His work addresses unmet clinical needs such as novel blood pressure measurement techniques and pre-term labor prediction. Education: PhD in Medical Physics from Newcastle University, UK. Research Interests: Healthcare device innovation, wearable sensors, bio-signal processing, computer modeling, and multidisciplinary collaboration across engineering, medicine, and industry. His work contributes to UN Sustainable Development Goals related to health and well-being. Awards: IPEM Martin Black Prize (2012) IET JA Lodge Award (2009) Grants & Projects: Principal Investigator on projects including: Development of a hearing aid IoT platform (2018–2020) Wearable respiratory rate device for infants (2018–2021) Uterine electrohysterogram system for preterm labor prediction (2016–2021) funded by the Bill & Melinda Gates Foundation Labs/Teams: Leads the Research Centre for Intelligent Healthcare, fostering international collaborations in China, Jordan, and Nigeria to advance healthcare technology adoption.
Bernd Münzer is a researcher at the Institute of Information Technology at Alpen-Adria-Universität Klagenfurt. His work focuses on medical multimedia, video retrieval systems, and human-computer interaction, particularly in endoscopic and laparoscopic video analysis. He contributes to projects involving deep learning for content identification, interactive exploration tools, and medical data visualization. Medical video analysis and retrieval Human-computer interaction in multimedia systems Endoscopic imaging and surgical skill assessment Dynamic content descriptors for video processing Collaborative video search frameworks Temporal analysis of clinical multimedia data His research includes developing tools like ECAT for endoscopic annotation, diveXplore for interactive exploration, and datasets such as Cataract-101 for surgical analysis. Projects emphasize medical multimedia applications, efficient video encoding, and augmented interfaces for clinical workflows.
Gabriel DANCIU is a Lecturer at the Department of Electronic and Computers, Faculty of Electrical Engineering and Computer Science, Technical University of Banat. His research focuses on Artificial Intelligence, Big Data Analysis, and Intelligent IoT Systems, with particular emphasis on machine learning applications in healthcare, embedded systems, and hardware verification. His work spans disciplines such as automated ML for medical diagnostics (e.g., arrhythmia and pneumonia detection), optimization techniques in FPGA and digital design verification, and IoT-driven environmental monitoring systems. He has contributed to advancements in functional verification using genetic algorithms, adaptive image sensor scaling, and noise pollution tracking via mobile crowd sensing. Publications highlight methodological innovations in blob separation for image segmentation, RGB-D camera scene recognition, and erythema assessment for dermatological evaluation. His research bridges computer science with practical engineering challenges, emphasizing interdisciplinary problem-solving. No scientific awards or grants are explicitly mentioned in the provided texts. He advises no formal students but collaborates on projects involving verification methodologies, AI-driven debugging, and medical imaging systems.
