Dr. Mao Suzuki is an Assistant Professor of Political Science at the National University of Singapore, specializing in global governance, international political economy, and global health. She holds a Ph.D. from the University of Southern California, an M.A. from Hitotsubashi University, and a B.A. from Keio University. Her research examines the role of non-state actors in transnational initiatives, particularly in global health governance. Her work analyzes how economic realities and geopolitical factors shape policies related to vaccine diplomacy, non-communicable diseases, and foreign aid effectiveness. Her research interests include analyzing stakeholder influence in global health negotiations, the political economy of health aid allocation, and the interplay between corporate interests and public health objectives. Dr. Suzuki's recent studies have explored how China, India, and Russia employ vaccine diplomacy strategies during the pandemic, revealing how economic strengths and manufacturing capabilities influence geopolitical health initiatives. Her publications consistently address systemic inequities in global health governance, emphasizing the need for balanced multi-stakeholder approaches that prioritize public health over commercial interests. Despite the focus on critical policy analysis, no specific awards or grants are explicitly mentioned in the provided materials.
Armin Kirchknopf serves as a Junior Researcher at the Media Computing Research Group within the Institute of Creative Media/Technologies, Department of Media and Digital Technologies at the University of Applied Sciences St. Pölten. His interdisciplinary work bridges artificial intelligence, computer vision, and social media analysis, with significant contributions to misinformation detection and disaster response systems. Based at Campus-Platz 1 in St. Pölten, Austria, he actively collaborates on EU-funded projects and publishes in top-tier AI venues. His educational journey spans humanities and technology: a Bachelor of Arts in Egyptology and Master of Arts in Classical Archaeology from the University of Vienna (including fieldwork at excavation sites across Austria, Germany, and Egypt), followed by a Bachelor of Science in Media Technology from FH St. Pölten. This unique background informs his human-centered AI research approach. Kirchknopf's research centers on explainable multimodal AI systems for real-world challenges. His recent work demonstrates expertise in transformer-based architectures for cross-lingual fake news detection, sexism identification, and flood monitoring through social media imagery. He pioneers techniques like Grad-CAM for object detection explainability and develops visualization tools for complex data interpretation, emphasizing transparency and social impact in AI deployment. Analysis of his 13 publications (2017-2022) reveals a strategic shift toward applied AI in societal contexts , particularly using social media data for disaster management and combating online toxicity. His projects consistently integrate computer vision with natural language processing, showing increasing sophistication in multilingual capabilities and model interpretability frameworks. His scientific recognition includes: Creative Business Award for co-developing the Tenjin learning quiz application No documented student advisement or grant leadership appears in current records, though he actively mentors through project-based collaborations. His work with the Media Computing Research Group drives innovation in educational technology and public safety applications. Kirchknopf contributes to the Media Computing Research Group's portfolio including Fake News Detection, SAiEX (Safe AI with explainable integrity), InfraBase (building footprint segmentation), and Ressel Center music therapy projects. His cross-disciplinary collaborations span computer scientists, archaeologists, and social scientists, reflecting the group's commitment to human-centric technological solutions .
Dr Anna Sanders is a Research Fellow at the ANU Institute for Climate, Energy & Disaster Solutions, part of the College of Science at The Australian National University. Her research focuses on transformational climate adaptation, environmental governance, and multi-level decision-making in rapidly changing environments. Previously, she held roles at the University of Melbourne, where she remains an honorary fellow at the School of Agriculture, Food and Ecosystem Sciences. Her work spans environmental policy analysis, political ecology, and interdisciplinary research methods. Key areas include climate adaptation strategies, landscape change, and resource governance in Southeast Asia and Australia, particularly in Indonesia’s tropical peatlands, oil palm regions, and the Northern Territory. She emphasizes participatory research approaches, ethical practices, and long-term place-based studies to enhance local capabilities and policy relevance. Anna’s research groups include Agriculture, Food and Nutritional Security; Indigenous Knowledges and Development in Asia/Pacific; and Law, Governance and Institutions. Her contributions address global environmental challenges through nuanced, culturally attuned frameworks.
Xuming He is an Associate Professor at the School of Information Science and Technology (SIST), ShanghaiTech University, where he leads the PLUS Lab. His research spans computer vision and machine learning with a focus on developing algorithms that operate effectively under limited supervision and evolving data conditions. His core research interests include weakly-supervised and few-shot learning for scenarios with sparse annotations, continual learning frameworks for knowledge retention during sequential task acquisition, semantic segmentation techniques for scene understanding, and multimodal vision-language representations. He emphasizes interpretable machine learning to build transparent AI systems capable of human-understandable reasoning, addressing critical challenges in model trustworthiness and deployment reliability. Recent publications reveal strong trends toward novel class discovery in long-tailed recognition scenarios, physics-informed generative modeling for scientific applications, and robust segmentation under distribution shifts. His work increasingly integrates large language models for multimodal reasoning while maintaining focus on efficiency in resource-constrained environments like robotic grasping and medical imaging analysis. He actively mentors students, having supervised Qian He to PhD completion and Chuanyang Hu to Master's degree in 2023. He welcomes prospective graduate students through ShanghaiTech's Computer Science & Technology program and offers undergraduate research projects requiring minimum six-month commitments. The PLUS Lab under his direction drives innovation in learning under supervision constraints, with recent work spanning medical tumor analysis, cross-view geolocation, photonic computing, and semiconductor design verification. The lab's research bridges theoretical advances with practical applications across healthcare, robotics, and scientific discovery domains.
Dr. Quynh Do is an International Lecturer (Assistant Professor) in Logistics and Supply Chain Management at The Management School, Lancaster University . Her research focuses on innovative pathways towards sustainable and circular supply chains , addressing critical issues such as waste reduction, decarbonisation, worker rights, and empowerment of marginalized actors like farmers and workers. Her work explores the digital and social innovations that drive ethical sourcing and systemic change, with applications in the textile, food, and manufacturing sectors . She collaborates with organizations such as Reverse Resources, Renewcell, and the Global Fashion Agenda to promote transparent and responsible sourcing practices. 2025: Big data analytics and supply chain learning for resilience and financial performance. 2024: Circular food waste management in Italian fish manufacturing, stakeholder collaborations in fast fashion, digital platforms for waste exchange, and power dynamics in circular supply chains. 2023: Organizational resilience during the pandemic, legitimacy-seeking behaviors in circular transitions, and data-driven supply chain learning. 2022: Global value chain restructuring post-COVID, institutional adoption of circular practices in seafood, and resource mobilization via bricolage. 2021: Systematic reviews on food waste and supply chain agility during crises.
Dr. Andy Nguyen is a Senior Lecturer in Structural Engineering at the University of Southern Queensland, within the School of Engineering. He is an active researcher and educator, specializing in the Structural Health Monitoring (SHM) of critical civil infrastructure such as bridges, buildings, and transport tunnels. Bachelor of Engineering (BEng), NUCE, 1999 Master of Engineering (MEng), NUCE, 2003 Doctor of Philosophy (PhD), Queensland University of Technology (QUT), 2014 Dr. Nguyen's research is at the forefront of integrating advanced technologies into civil engineering. His primary focus is on developing and deploying sophisticated SHM systems that utilize sensors, data analytics, and machine learning to provide real-time insights into the structural integrity of ageing infrastructure. His work aims to enable proactive maintenance, extend the lifespan of structures, and enhance public safety. He has successfully implemented monitoring systems on major bridges and high-rise buildings in Queensland and New South Wales, with systems capable of even detecting distant earthquake events. His research interests span Structural Health Monitoring, Machine Learning for Engineering, Damage Detection, Finite Element Model Updating, Sustainable Building Materials like bamboo, and the application of AI for automated condition assessment of transport infrastructure. The analysis of his recent publications reveals a strong and consistent research trajectory centered on the application of data-driven and AI methods to solve practical problems in civil infrastructure. His work frequently combines signal processing techniques (like Stockwell Transform) with deep learning models for tasks such as crack detection in concrete and pavement. He also conducts significant research on model updating for complex structures like cable-stayed and arch bridges, using vibration data and optimization algorithms. The integration of machine learning for overload classification and the development of cost-effective, automated monitoring systems are key trends in his recent output. Advanced Queensland Fellow (2024-2027) Dr. Nguyen is actively involved in research supervision and collaboration. He is currently supervising several postgraduate students on projects related to AI-powered condition assessment, bamboo as a sustainable building material, and railway track design. He receives research funding from the Queensland Government through his Advanced Queensland Fellowship. His research has direct practical applications, as evidenced by his public engagement, such as writing for The Conversation on safeguarding ageing bridges, and his work with the Australian Network of Structural Health Monitoring. Dr. Nguyen's work embodies the development of a next-generation 'Living' Laboratory for engineering education, where research, teaching, and real-world infrastructure monitoring are integrated. His current projects involve creating smart, automated fault detection systems and advancing 'digital twin'-based monitoring platforms for infrastructure.
Md. Zoheb Hassan serves as an Assistant Professor in the Department of Electrical Engineering and Computer Engineering at Laval University, where he leads cutting-edge research in wireless communications and spectrum management. His academic role includes graduate recruitment and active participation in the university's research ecosystem, particularly through the Establishment of the Next Generation of Professors program funded by FRQNT. Dr. Hassan's research centers on spectrum sharing and management, wireless communication systems, and communications network control systems. He pioneers the integration of digital twin technology and machine learning to solve critical challenges in next-generation networks, including interference management in 5G/6G aerial corridors, Internet of Vehicles, and satellite-terrestrial integration. His work emphasizes practical implementations such as proof-of-concept demonstrations for tactical networks and proactive resource allocation in dynamic environments. Analysis of his 2024-2025 publications reveals a dominant trend toward AI-driven wireless resource optimization, with 12 of 15 recent papers featuring digital twins for interference management, spectrum sharing, and energy efficiency. Key thematic clusters include vehicular communications (4 papers), underwater IoT networks (2 papers), and hardware-impairment resilient designs (3 papers), demonstrating his focus on bridging theoretical advances with real-world deployment challenges across diverse network topologies. Dr. Hassan has secured significant competitive funding for his research initiatives: Digital Twin-Enhanced Interference Management for Next-Generation Radio Access Networks in the FR3 Band (FRQNT, 2025-2027) Center for Radio Frequency and Communications Systems, Technologies and Applications (FRQNT, 2024-2030) Context-Aware Spectrum Sharing and Management for Next Generation Wireless Networks (NSERC, 2024-2029) Development of innovative technologies for modeling predictive systems in urban mobility (MITACS, 2022-2026) Springboard to Discovery supplement for Context-Aware Spectrum Sharing (NSERC, 2024-2025) He actively mentors doctoral candidates, currently supervising Mahima Karim (PhD in Electrical Engineering, expected 2025) and Mohammadamin Parhizgar (PhD in Electrical Engineering, expected 2024). His supervisory approach combines theoretical rigor with practical problem-solving, focusing on spectrum management algorithms and digital twin implementations for next-generation networks. While specific laboratory affiliations aren't detailed in the source material, his projects indicate strong alignment with Laval University's wireless research infrastructure and the Center for Radio Frequency and Communications Systems.
Professor Elena Giovannoni is a full-time faculty member at the University of Birmingham , where she holds the position of Professor of Accounting and serves as Head of the Department of Accounting within the Birmingham Business School . She is an active researcher and academic leader with a strong international presence. Research Interests: Elena Giovannoni's research bridges critical and historical perspectives in accounting and organization studies. She investigates performance measurement and management control systems across diverse sectors—including the space industry, food industry, knowledge-intensive organizations, and the arts—with a focus on organizational change and sustainable development. Her work explores how calculative practices shape responses to climate change, often through a temporal lens. Methodologically, she employs case studies , archival research , and multimodal approaches . Recent Publications Trends: Her recent scholarly output (2018–2025) reveals a consistent focus on the interplay between accounting, history, and visuality. She examines accountability in cultural contexts (e.g., music, art), the materiality of organizational objects, and the future of sustainability reporting. Her editorial work on the Handbook of Historical Methods for Management underscores her leadership in advancing historical methodologies in management research. Scientific Recognition: Higher Education Academy Fellowship (2017) Editorial Board Member, Accounting Forum Editorial Board Member, Accounting, Auditing & Accountability Journal Editorial Board Member, Accounting History Editorial Board Member, Family Business Review Editorial Board Member, Organization Studies Advising and Grants: She has led multiple projects funded by international bodies, resulting in publications in top-tier journals. While no specific advisees are listed, her role as department head and PhD supervisor implies significant mentoring responsibilities. She contributes to academic knowledge dissemination through editorial leadership and collaborative research. Labs and Research Groups: While no formal lab is mentioned, her research is closely tied to the Department of Accounting and its research clusters, particularly those focused on critical accounting, sustainability, and historical methods. Her collaborative work with scholars across Europe indicates strong international research networks.
Adlen Ksentini is a Professor at EURECOM, a leading graduate school and research center in Sophia Antipolis, France, specializing in digital science and communication systems. His extensive research focuses on next-generation mobile networks (5G/6G), network management, and the integration of artificial intelligence with telecommunications infrastructure. Dr. Ksentini actively contributes to major EU research initiatives including 6G-BRICKS and AC3, serving as a key researcher and project leader in the development of future network architectures. Dr. Ksentini's research interests center around network slicing, intent-based networking, edge computing, and the application of machine learning to network management problems. His work bridges theoretical advancements with practical implementations in 5G/6G systems, with particular emphasis on zero-touch network management, energy efficiency optimization, quality of service assurance, and the integration of large language models with network operations. His research has significantly contributed to the development of O-RAN (Open Radio Access Network) frameworks and the evolution of network automation. His recent publication trends reveal a strategic shift toward AI-native network architectures, with increasing focus on integrating large language models (LLMs) with network management systems. His work demonstrates a clear progression from traditional network management approaches to more autonomous, AI-powered systems capable of intent-based configuration, self-optimization, and predictive maintenance. The publications show strong emphasis on practical implementations within the 6G research ecosystem, addressing critical challenges in network slicing, resource allocation, and energy efficiency. As a research supervisor, Dr. Ksentini mentors several PhD students including Abdelkader Mekrache, Karim Boutiba, Bouziane Brik, and Houda Hafi, who frequently appear as co-authors on his publications. His research is primarily funded through major EU research projects such as 6G-BRICKS (Building Reusable Testbed Infrastructures for Cloud-to-Device Breakthrough Technologies) and AC3 (which focuses on Cloud Edge Continuum). Dr. Ksentini is actively involved with the 6G-BRICKS project consortium and the AC3 project team, where he contributes to developing next-generation network architectures that integrate communication, computing, and sensing capabilities. His work within these projects focuses on creating reusable testbed infrastructures and addressing security and trust management challenges in the cloud-edge continuum.
Marek Ilnicki is a Lecturer at the University of Gdańsk , affiliated with the Faculty of Social Sciences and specifically the Department of Strategic and Security Studies . His academic focus lies at the intersection of political science, security studies, and maritime law. Fields of Interest : Political Science, Security Studies, Maritime Law, Counterterrorism, International Relations, and Crisis Management. Research Trends in his publications emphasize legal frameworks for state security, maritime governance, terrorism prevention, and international cooperation. His work often addresses Poland's strategic challenges in maritime environments and border security. Contact Information : Email: marca.ilnicki@ug.edu.pl Phone: +48 58 523 41 81
Jianwen Su is a Professor in the Department of Computer Science at the University of California, Santa Barbara (UCSB), where he has been since 1990. He holds a Ph.D. in Computer Science from the University of Southern California and B.S./M.S. degrees from Fudan University in China. His research focuses on databases, formal verification, web services, business process management (BPM), and workflow systems. He has contributed to data-centric workflow modeling, artifact-based BPM frameworks, and tools like the Web Service Analysis Tool (WSAT). Adjunct professorships at Peking, Fudan, and Donghua Universities in China. Key roles: General co-chair of ICSOC 2013, PC chair of PODS 2009, and general chair of SIGMOD 2001. Recipient of the 2000 Outstanding Faculty Award (UCSB College of Engineering) and IBM Faculty Awards (2007, 2008). Research spans database query languages, incremental query evaluation, spatial databases, and formal verification techniques for software systems. Current emphasis is on data modeling for workflows and BPM systems.
Ahmed Bin Zaman serves as an Assistant Professor in the Department of Computer Science at George Mason University, where his research bridges computational methods with biological discovery. His academic profile emphasizes innovative approaches to protein structure prediction and optimization challenges. His educational foundation includes: PhD in Computer Science, George Mason University (2021) Master of Science in Computer Science, George Mason University (2020) Zaman's research program centers on computational biology, with specialized expertise in evolutionary computation and artificial intelligence applied to protein conformation analysis. He develops stochastic optimization frameworks to enhance protein structure prediction accuracy, focusing on conformational space mapping and decoy ensemble generation. His methodology integrates evolutionary algorithms with multi-objective optimization to navigate complex molecular landscapes, contributing significantly to template-free protein structure determination. His publication trajectory from 2017-2022 reveals distinct research phases: initial work in cybersecurity threat detection evolved into a concentrated focus on computational structural biology. Thirteen protein-related publications demonstrate consistent innovation in conformational sampling techniques, while maintaining methodological rigor through evolutionary computation and machine learning integration. Key contributions include conformation space mapping frameworks and adaptive stochastic optimization systems that address decoy diversity challenges. Professional development shows progression from industry experience at Technext Limited (as team leader/researcher) and lecturing at Metropolitan University to his current academic role. His teaching philosophy emphasizes cultivating independent problem-solving capabilities in students through cognitive tool development.
Professor Farookh Hussain is a distinguished academic at the School of Computer Science , University of Technology Sydney , specializing in Artificial Intelligence , Cloud Computing , and Software Engineering . His research spans diverse sectors including agriculture, manufacturing, healthcare, and transportation. Affiliated with the Australian Artificial Intelligence Institute (AAII) , he leads impactful work in business intelligence and carbon credit systems. Key research areas: AI applications, blockchain for provenance, carbon credit analytics Active in Masters/PhD supervision and cloud computing education Research Highlights : Developed KACINO framework for carbon dynamics modeling Created hybrid cybersecurity frameworks for supply chain risk management Advanced chatbot dialogue breakdown solutions through systematic reviews Proposed hypercomplex knowledge graph recommenders Published extensively on carbon credit price prediction and blockchain storage methods Contributions to water demand forecasting and collaborative robotics adoption Grant Activities : Secured funding from Hampton Capital Asset Management , Innovation Connections , and Science and Industry Endowment Fund Projects include LLM-driven text-to-SQL conversion , blockchain for melanoma data , and AI for storm water management
Professor Allan Rennie serves as Professor in Manufacturing Engineering at Lancaster University's School of Engineering and holds the administrative position of Associate Dean for Engagement within the Faculty of Science and Technology. With a career spanning over 30 years since initiating work in additive manufacturing during the mid-1990s, he has established himself as a leading figure in industrial applications of advanced manufacturing technologies across diverse sectors. His research expertise centers on Additive Manufacturing , Engineering Design , and Manufacturing Process Optimization , with current specializations including design for additive manufacturing (as co-leader of the UK's EPSRC DfAM Network), industrial digitalisation of manufacturing processes, and innovative tooling development using metallic and hybrid approaches. Rennie has significantly contributed to Engineering Education , particularly examining the integration of business and management principles into engineering curricula and analyzing the impacts of online/hybrid delivery modes on student engagement and graduate employability following the COVID-19 pandemic. Recent publication trends reveal Rennie's dual focus on practical manufacturing applications and scholarly analysis of technological evolution. His 2025 bibliometric study maps a decade of Design for Additive Manufacturing research, while his structural analysis of musical instruments demonstrates cross-disciplinary applications of manufacturing techniques. These works reflect his commitment to both advancing manufacturing technology and documenting its academic trajectory through rigorous analysis. Professor Rennie actively supervises PhD candidates including Jenny Roberts, Eunike Sembiring, and Joe Taylor while leading substantial research projects such as the EPSRC DfAM Network (2020-2023), Automating Design for Additive Manufacture with AI (2023-2024), and multiple Engineers in Business Competitions. His extensive grant portfolio spans industrial digitalization, sustainable manufacturing, and educational innovation, with notable projects including RENDER (powder recycling), TecHnology and EntrepreneUrship Education, and Production Capable Additive Manufacturing of Polymers. Rennie contributes to Lancaster's research ecosystem through affiliations with the Centre for Global Eco-innovation, Energy Lancaster initiative, and the Lancaster Product Development Unit. These platforms enable him to bridge academic research with industrial applications across multiple sectors, particularly supporting his work on sustainable manufacturing practices, technology commercialization, and industry engagement strategies that translate research into real-world impact.
Professor Leah Morabito is a Professor (Research) - UKRI Future Leaders Fellow at Durham University, affiliated with the Department of Physics and the Institute for Computational Cosmology. She specializes in high-resolution imaging at low frequencies using the LOFAR telescope to study how supermassive black holes co-evolve with their host galaxies. As leader of the LOFAR Imaging of Resolved AGN (LIRA) group, she has made significant contributions to our understanding of active galactic nuclei and galaxy evolution through numerous high-impact publications. Professor Morabito's research primarily focuses on AGN physics, galaxy surveys, and radio interferometry. She has pioneered techniques for sub-arcsecond imaging at low radio frequencies, which has opened new windows for studying radio jets, galaxy evolution, and the interstellar medium. Her work reveals critical insights about AGN feedback mechanisms and the connection between supermassive black holes and their host galaxies across cosmic time. The analysis of her recent publications shows a strong emphasis on utilizing LOFAR's unique capabilities to study radio sources with unprecedented resolution at low frequencies. Scientific Recognition: UKRI Future Leaders Fellowship Professor Morabito actively mentors the next generation of astronomers, currently supervising PhD students Benite Tantely, Ciera Sargent, and Emmy Escott. Her research is supported by significant funding through her UKRI Future Leaders Fellowship and her role as co-Principal Investigator of the new LOFAR2.0 Large Programme, which extends her work on high-resolution low-frequency radio surveys. She has secured substantial research funding that enables cutting-edge observations and supports her research team. As leader of the LOFAR Imaging of Resolved AGN (LIRA) group, Professor Morabito oversees a collaborative research effort focused on advancing our understanding of how AGN help shape galaxy evolution. Her team utilizes unique high-resolution, low-frequency observations to study radio jets, AGN feedback mechanisms, and the connection between supermassive black holes and their host galaxies, contributing significantly to one of the most fundamental questions in modern astrophysics.
