Ahmed Kamil Hasan Al-Ali is a researcher specializing in signal processing and forensic applications. His work focuses on improving speaker verification systems in challenging acoustic environments, particularly addressing noise and reverberation through advanced techniques like wavelet transforms (DWT), Mel Frequency Cepstral Coefficients (MFCC), and Independent Component Analysis (ICA). His research contributes to enhancing forensic speaker identification accuracy in real-world conditions. Collaborations with experts such as David Dean, Bouchra Senadji, and Vinod Chandran highlight his interdisciplinary approach. Though institutional affiliations are unspecified in the provided texts, his publications in IEEE journals and conferences underscore his active role in the field of speech technologies and machine learning.
Byron Keating is an Adjunct Professor at Queensland University of Technology (QUT), specializing in service management, information systems, and consumer behavior. His work bridges academic research with practical applications in healthcare, public policy, and technology-mediated services. Research interests include AI in service recovery, consumer vulnerability advocacy, and disability employment strategies. He has collaborated extensively with institutions like QUT's Business School and conducted impactful studies on public transport safety, facial recognition payment systems, and youth drug intervention programs. With over 95 publications since 2002, his work spans journals like Journal of Service Management and International Journal of Information Management . Key themes include strategic alignment of IT systems, multichannel service optimization, and ethical considerations in emerging technologies. Recent projects include systematic reviews on frontline employee vulnerability and DEI recruitment practices, as well as policy recommendations for disability employment centers. His interdisciplinary approach integrates marketing, technology, and public health to address societal challenges.
Larry Davis is a Professor in the Department of Computer Science and the Institute for Advanced Computer Studies (UMIACS) at the University of Maryland. He is affiliated with the Computer Vision Laboratory of the Center for Automation Research, where he previously served as head from 1981-1986. His research focuses on visual surveillance, human movement analysis, and advanced computer vision systems such as the Keck Laboratory for the Analysis of Visual Movement. Established in 1998, the Keck Lab uses a 64-camera array to study 3D human motion tracking and shape recognition. His work spans projects like codebook-based background subtraction for surveillance and clothing appearance models for persistent tracking. He leads interdisciplinary research on laser beam propagation through atmospheric turbulence and has secured significant grants, including a $4M Multidisciplinary Research Initiative contract. His recent publications emphasize AI-driven solutions for media forensics, generative models, and adversarial attacks on vision systems. Research contributions include innovations in neural rendering (FlexNeRF), personalized clothing compatibility frameworks, and systems for detecting deepfakes and video tampering. His work bridges theoretical advancements with real-world applications in security, healthcare, and retail technology.
Fernando Marmolejo-Ramos is an academic affiliated with Flinders University's College of Education, Psychology, and Social Work. He holds a PhD in Experimental Psychology from the University of Adelaide and has held roles including Research Fellow at the University of South Australia, Visiting Research Fellow at the University of Adelaide, and Lecturer positions across multiple institutions. His expertise spans experimental psychology, cognitive science, and statistical methodologies. Education: BA in Psychology (Universidad del Valle, Colombia, 2003), MAppSc in Psychology (University of Ballarat, Australia, 2007), PhD in Experimental Psychology (University of Adelaide, Australia, 2011). He completed a postdoctoral fellowship at Stockholm University (2014–2016). Research focuses on embodied and artificial cognition, statistical modeling, and robust research methods. Key interests include language comprehension, cross-modal perception, machine behavior, and statistical cognition. Over 120 peer-reviewed articles and numerous grants highlight his contributions to fields like AI ethics, health informatics, and educational technology. His work has been featured in outlets like Nature Human Behavior and Science . Awards include the IEPRS Postgraduate Research Scholarship and the Young and Innovators Researchers Program Fellowship. He serves on editorial boards for journals such as Cognitive Processing and Frontiers in Applied Mathematics . Notable grants include projects on AI in cardiac care, machine learning for health diagnostics, and AI ethics in governance. Current roles include leading projects on AI in education and collaborative reasoning tools for defense applications.
Professor Daniel Vogel is a faculty member at the University of Waterloo, specializing in Human-Computer Interaction (HCI). His research focuses on interaction techniques, virtual/augmented reality, and novel input methods for diverse computing platforms including wearables, mobile devices, and large displays. He holds a Ph.D. from the University of Toronto (2010), alongside degrees in Art & Design and Liberal Arts. Ph.D., University of Toronto (2010) M.Sc., University of Toronto (2005) B.FA., Emily Carr University of Art + Design (1996) B.A., Western University (1993) His research interests span interaction design principles, gesture-based systems, and accessibility in VR/AR. Key areas include mid-air gestures, wearable computing, and improving user engagement through innovative input mechanisms. Recent work explores psychological ownership in AI-assisted writing, sustainable 3D printing techniques, and spatial augmented reality interfaces. Publications span over two decades, addressing topics like touch interaction, gesture recognition, and the ergonomics of virtual environments. His work often bridges theoretical HCI principles with practical system implementations. Notable contributions include frameworks for contextual visualizations in AR, finger-based input sensing hardware, and studies on user behavior in semi-automated fabrication tasks. He advises on emerging technologies while maintaining a focus on human-centered design principles.
Džemila Šero is a Researcher at the University of Twente's Data Management and Biometrics (DMB) group, affiliated with the Electrical Engineering, Mathematics and Computer Science (EEMCS) faculty. Her work focuses on applying biometric and data analysis techniques to historical artifacts, such as examining fingerprints and hand impressions on 17th-century sculptures by Dutch master Artus Quellinus. This research contributes to understanding artistic processes and verifying authorship. Her interdisciplinary approach bridges forensic science, digital humanities, and cultural heritage preservation. Her recent collaboration led to an exhibition opening attended by King Willem-Alexander of the Netherlands, highlighting her innovative methods in uncovering hidden historical layers through scientific analysis. While no awards are explicitly mentioned in the text, her work demonstrates contributions to art forensics and technological applications in cultural studies.
Dr. Luigi La Spada is a Lecturer in Electrical and Electronic Engineering at Edinburgh Napier University's School of Computing Engineering and the Built Environment. His academic journey includes a PostDoctoral Research Assistant position at Queen Mary University of London (2014-2017) and a Lecturer role at Coventry University (2017-2018). He is actively involved with multiple research groups including the Centre for Artificial Intelligence and Robotic, Centre for Conservation and Restoration Science Engineering Research Group, and Centre for Cybersecurity, IoT and Cyberphysical Systems. His educational background includes: Bachelor's and Master's degree (summa cum laude) in Electronics Engineering from University of RomaTre (2008, 2010) PhD in Electronic Engineering (Biomedical Electronics, Electromagnetics, and Telecommunications) from University of RomaTre and University of Pennsylvania (2011-2014) Dr. La Spada's research spans metamaterials engineering, electromagnetic wave control, and advanced sensor development, with significant contributions to metasurface applications and nanoparticle technology. His work has expanded into AI applications for security systems, quantum cryptography for UAV communications, and medical diagnostics. His interdisciplinary approach bridges theoretical electromagnetic concepts with practical engineering solutions across aerospace, healthcare, and agricultural technology sectors. His publication record shows a clear evolution from fundamental electromagnetic research toward applied technologies, particularly in quantum-enhanced security systems, AI-driven biometrics, and medical applications of metamaterials. Recent work demonstrates strong interdisciplinary connections between electromagnetic theory, quantum physics, and artificial intelligence, with increasing focus on practical implementations in aerospace, healthcare, and agricultural monitoring systems. Dr. La Spada has received significant recognition for his research contributions: 2018 Advances in Engineering (AIE) 'key scientific contributor to excellence in science and engineering research' 2017 URSI Young Scientist Award (Canada) Finalist for 2017 IEEE Young Scientist Award 2016 ISAP Best Paper Award (Japan) 2015 EAI recognition for 'new technologies in telecommunications and sensing' His research has received international scientific recognition and media coverage from CNN, CBS, Times, and Aspen Institute. Dr. La Spada currently supervises PhD student Nida Zeeshan on AI-based biometrics facial recognition. He has secured substantial research funding including a £184,194 European Commission grant for Intelligent Multi-Agent Robotic Systems (iMARS) and multiple Scottish Funding Council projects totaling over £74,000. His current grants span robotics, AI visual systems, medical device development (Airglove technology), and wireless power transfer. Dr. La Spada is actively involved in the Centre for Artificial Intelligence and Robotic and Centre for Cybersecurity, IoT and Cyberphysical Systems, where he contributes to developing innovative methods in AI, Robotics, IoT, and 5G technologies. His work connects theoretical electromagnetic concepts with practical applications in healthcare, aerospace, and security systems.
Daniel T. Ramotsoela is an academic researcher at the University of Pretoria's Department of Electrical, Electronic and Computer Engineering, within the College of Engineering, Built Environment and Information Technology. His research focuses on cybersecurity applications for critical infrastructure, particularly water distribution systems and industrial control environments. With over 30 publications spanning from 2015 to 2024, he has established himself as a significant contributor to the fields of intrusion detection, machine learning applications in critical infrastructure protection, and wireless sensor network security. Dr. Ramotsoela's research interests center around applying machine learning techniques to enhance security in critical infrastructure systems. His work particularly emphasizes water distribution networks, where he has published extensively on anomaly detection methods using neural networks and other AI approaches. He also investigates security challenges in 5G networks, industrial environments, and microgrids, with a strong focus on practical implementation challenges. His recent work shows an increasing emphasis on reinforcement learning applications for network resource allocation and admission control in next-generation communication systems. Analysis of his publication trends reveals a consistent focus on applying machine learning to infrastructure security problems, with a clear progression from foundational surveys to more sophisticated technical implementations. His early work (2017-2019) established survey papers on anomaly detection in industrial wireless sensor networks, particularly using water systems as case studies. From 2020 onward, his research became more specialized, addressing specific challenges like behavioral intrusion detection, data imputation in sensor networks, and biometric authentication systems for industrial applications. The most recent publications (2023-2024) demonstrate advanced applications of deep reinforcement learning and multi-agent systems for 5G network optimization and security.
Delphine Caruelle is an Associate Professor of Marketing at the School of Communication, Leadership and Marketing, Kristiania University of Applied Sciences. She holds a Ph.D. from BI Norwegian Business School (2019). Her research focuses on service marketing, consumer behavior, and emotional dynamics in customer experiences. Key areas include customer experience design, influencer marketing ethics, and interdisciplinary approaches to human-centered service systems. Education: Ph.D. in Marketing, BI Norwegian Business School (2019) Research Interests: Delphine explores emotional arousal in service encounters, the impact of waiting time perceptions, and the ethical implications of woke advertising. Her work bridges consumer psychology with operational service design, emphasizing measurable outcomes through biometric tools like EDA and affective computing technologies. Awards & Recognition: Liam Glynn Research Scholarship Award (2018) Finalist - 2020 SERVSIG Best Dissertation Award Professional Background: Before academia, Delphine worked as a Consumer Insights Specialist at Opera Software, bringing industry实践经验 to her academic research. Her recent publications emphasize triadic influencer-brand-follower dynamics and the intersection of CX/EX/HX systems.
Pierre Roduit is a Professor and Head of the Institut Energie et environnement at HES-SO Valais-Wallis. His expertise spans Energy Systems, Demand Side Management, and Machine Learning applications in sustainability. He leads research on smart energy solutions, including grid flexibility, non-intrusive load monitoring, and hydropower maintenance. Current projects include the EU-funded domOS (H2020) for smart building OS and the Innosuisse-backed Industrialisation of energy services for small buildings. His work integrates IoT and data science to enhance energy efficiency in residential and industrial contexts. Key Projects: GOFLEX (H2020), SEMIAH (FP7), Cavitation Monitoring System Focus Areas: Thermal Energy Storage, Predictive Maintenance, Smart Grids His research bridges academic innovation with industrial applications, advancing technologies such as NILM and acoustic-based turbine monitoring. Over 20 years, he has authored over 30 publications and secured €16M+ in EU and industry funding.
Asma Shakil is a researcher in computer science with a focus on software engineering, biometrics, and education technology. Her work spans empirical studies on code readability, pedagogical strategies for capstone courses, and biometric signature verification systems. She collaborates with scholars across institutions, contributing to conferences like ITiCSE, ACE, and CHI. 2025: Co-authored a paper on team-based capstone projects. 2024: Authored multiple studies on student engagement and capstone course design. 2019: Explored gaze-based code navigation in CHI proceedings. 2008-2010: Pioneered offline signature verification research with Hidden Markov Models. Research Interests: Asma's work bridges software engineering practices, biometric authentication, and educational innovation. Her recent papers emphasize scalable teaching methods and team-based learning in computing education, while her earlier contributions focus on statistical modeling for signature verification. Publication Trends: Her research has evolved from biometrics to education technology, with a recurring emphasis on empirical validation. Key subfields include functional decomposition, code navigation, and pedagogical interventions for student engagement. Collaborations: Regular co-authors include Paul Denny, Sara Hooshangi, and Ewan D. Tempero, indicating sustained partnerships in education technology research.
Dr. Philip G Zhao is a Senior Lecturer in Robotics and AI at the University of Manchester's Department of Computer Science. Prior to this role (since 2024), he held positions at the University of Glasgow from 2018 to 2023. He leads the Machine Intelligence Alliance across multiple universities and is a Senior Member of IEEE and IET member. His research focuses on AI-driven cross-system design and optimization for robotics, Cyber-Physical Systems (CPS), IoT, communication networks, and computer vision. His work emphasizes practical applications such as edge intelligence, teleoperation systems, and medical robotics. Dr. Zhao has secured £3M in total research funding, including £800k as Principal Investigator, and holds two U.S. patents. Notable achievements include three Best Paper Awards and over 2,800 Google Scholar citations. His recent projects involve edge-enabled industrial CPS co-design, metaverse teleoperation frameworks, and dynamic human-robot interaction studies. He actively supervises PhD students and promotes collaborative robotics in healthcare and education. Labs/Teams: Machine Intelligence Alliance (MIA), leading interdisciplinary research across multiple universities.
Daniele Antonioli is an Assistant Professor in Digital Security at EURECOM, France. His research focuses on securing Cyber-Physical Systems (CPS), Mobile/Wireless Systems, Embedded/IoT devices, and Industrial Control Systems (ICS). He specializes in applied cryptography and system-level security, addressing vulnerabilities in emerging technologies such as Bluetooth, FIDO2, and vehicular networks. Maintains a lab focused on reverse engineering, hardware-software co-analysis, and automated security testing frameworks. Developed tools like MiniCPS and CPSBot for CPS/IoT security research. Research interests include: - Bluetooth Exploitation : BIAS, KNOB, BLURtooth attacks. - Embedded Systems Security : E-Trojans, E-Spoofer, Breakmi. - Privacy-Preserving Systems : Decentralized contact tracing protocols. - IOT/IICS Threat Modeling : AttackDefense Framework. Publications highlight both technical contributions (e.g., SimProcess simulation framework) and practical impact (e.g., EmuOCPP for EV charging security). Recipient of Singaporean Presidential Graduate Fellowship (2015-2019) and ST Engineering Research Excellence Award (2017). Active in international collaborations, including EU-funded projects. Advises on CPSBot botnet simulation and FP-tracer browser fingerprinting detection systems. Engages in standardization efforts for secure industrial communication protocols.
Imran Naseem serves as an Adjunct Associate Professor in the School of Engineering at The University of Western Australia, specifically within the Department of Electrical, Electronic and Computer Engineering. His academic profile shows significant research contributions with 1,533 citations and an h-index of 13 according to Scopus metrics. His research expertise spans several interconnected domains: Machine Learning algorithms, particularly least mean square variants (76% research focus) Deep learning architectures for computer vision and biometric security Neural networks and radial basis function applications (41% research focus) Fast convergence techniques in signal processing (39% research focus) Biomedical applications including anticancer peptides classification Dr. Naseem's recent publication trends demonstrate strong focus on developing robust AI systems for security applications, particularly in biometric authentication systems that can detect presentation attacks. His work bridges theoretical signal processing with practical applications in computer vision and healthcare diagnostics. The research fingerprint shows significant activity in Mean Square Mathematics (100%) and Least-Mean-Square Algorithm development. His collaborative network includes multiple international co-authors across different research institutions, with recent publications appearing in IEEE Access, Applied Intelligence, and Frontiers in Physiology. The University of Western Australia profile indicates he has supervised at least one research project as noted by the 'Supervised Work (1)' designation in his academic profile.
Hany Farid is a Professor at the University of California, Berkeley with a joint appointment in the Department of Electrical Engineering & Computer Sciences (EECS) and the School of Information. He specializes in digital forensics, forensic science, misinformation analysis, image analysis, and human perception. His research focuses on detecting manipulated media (photos, videos, audio) and understanding societal impacts of AI-generated content. Education: PhD in Computer Science (University of Pennsylvania, 1997), Postdoc at MIT (1999). Affiliations: Co-founder and Chief Science Officer at GetReal Security. Grants: Supported by NSF, DARPA, Adobe, Meta, Oak Foundation, and others. His work bridges computational techniques with human perception, addressing challenges like deepfake detection and forensic science reliability. He has authored over 200 papers and two book-length studies on photo forensics and synthetic media. Research Highlights: Developed algorithms to detect photo/video manipulation via lighting/shadow inconsistencies. Investigated AI-generated voice and facial synthesis detection. Explored societal impacts of misinformation and predictive algorithms in criminal justice. Awards: Alfred P. Sloan Fellowship (2002) John Simon Guggenheim Fellowship (2006) Fellow of the National Academy of Inventors (2020) IEEE Fellow (2018) Advising: Mentored over 40 students, including PhD candidates in computer vision and forensic science. Current focus includes M.S./PhD students in digital forensics and AI ethics.
