Simon Yang is a Professor in the School of Engineering at the University of Guelph, part of the College of Engineering and Physical Sciences. His research focuses on artificial intelligence, robotics, sensors, control systems, and bio-inspired intelligence. He has contributed to advanced robotics applications, including mobile robot navigation, underwater vehicle control, and agricultural automation. Dr. Yang holds editorial roles for journals such as the International Journal of Robotics and Automation and IEEE Transactions on Cybernetics . His work bridges theoretical advancements with practical implementations in areas like sensor networks, machine learning, and multi-agent systems. Recent projects include developing robust control frameworks for autonomous systems, digital twin applications, and bio-inspired neural network algorithms. His research emphasizes real-world challenges in robotics, environmental monitoring, and precision agriculture, with a focus on integrating AI-driven solutions for enhanced decision-making and system reliability. Professional contributions include advisory roles in multiple journals and conference committees, reflecting his leadership in the field.
Lukas Engelmann is a Senior Lecturer at the University of Edinburgh , specifically within the Science, Technology and Innovation Studies department under the School of Social and Political Science . His research focuses on the history and sociology of biomedicine , with particular interest in epidemiological reasoning , visual cultures of disease , digital epidemiology , and decolonial approaches to medical history . The Epidemy Lab , which he founded, explores the historical development of epidemiology and its contemporary influence on data-driven public health and pandemic policy-making . Engelmann's work has been funded by prestigious grants including an ERC Starting Grant (2021-2025) for his research on the history of epidemiological reasoning, and support from the Wellcome Trust for projects examining the social dimensions of digital health . His book 'Mapping AIDS' (2018) established him as a leading scholar in medical visualization , while 'Sulphuric Utopias' (2020) with Christos Lynteris explores the technological history of maritime sanitation and its political implications. Recent publications emphasize the visual and data practices that have shaped epidemiology, including works on epidemic modeling during the COVID-19 pandemic , the history of plague mapping , and the ethical implications of digital phenotyping . He has also contributed to interdisciplinary discussions on syndemics , co-infection epistemology , and the commercialization of bacteriology in the early 20th century. His scientific contributions have earned recognition through editorial roles in journals like Big Data and Society , and collaborative projects such as 'Working with Diagrams' (2022) which investigates the epistemological role of visual tools in medical knowledge production. Scientific Awards and Funding: ERC Starting Grant (2021-2025) Wellcome Trust Institutional Support Fund British Academy/Leverhulme Small Research Grant Chancellor's Fellowship (University of Edinburgh) 'Sulphuric Utopias' listed in The Guardian's 30 Books to Understand the World (2020)
Dr. Esam Abdel-Raheem is a Professor in the Department of Electrical and Computer Engineering at the University of Windsor, Faculty of Engineering. His research focuses on digital signal processing, biomedical engineering, cognitive radio networks, and VLSI design. He holds a Ph.D. from the University of Victoria (1995) and is a Professional Engineer (P.Eng.) in Ontario and a Senior Member of IEEE. Education: B.Sc. Electrical Engineering, Ain Shams University (1984) M.Sc. Electrical Engineering, Ain Shams University (1989) Ph.D. Electrical Engineering, University of Victoria (1995) Research Interests: Dr. Abdel-Raheem’s work spans signal processing for communications, biomedical signal processing, and VLSI implementations. He has pioneered algorithms for cognitive radio networks and adaptive filtering. His recent studies leverage deep learning for medical diagnostics (e.g., lung nodule detection, Parkinson’s disease voice analysis) and cognitive radio spectrum sensing. Publications Trends: Recent work emphasizes biomedical applications (e.g., CT scan analysis, diabetic retinopathy detection) and machine learning integration in communications (e.g., federated learning for traffic crowdsourcing). His articles often bridge theoretical signal processing with practical implementations in hardware (e.g., FPGA-based filters). Awards/Grants: Not explicitly listed in the text, though his senior IEEE membership and prolific publications suggest sustained professional recognition. Lab/Teams: While not detailed, his research themes imply involvement in interdisciplinary teams focusing on biomedical engineering, telecommunications, and VLSI design.
Mikael Johansson is a Professor at Kungliga Tekniska Högskolan (KTH), specializing in Control Technology . He teaches and coordinates courses such as Distributed Optimization (FEL3311) and various advanced-level degree projects in computer science, electrical engineering, and systems engineering. His research spans Control Systems , Machine Learning , and Optimization , with a focus on asynchronous algorithms, federated learning, and applications in energy systems and construction. His work includes 15 recent publications on topics like neural networks, distributed optimization, and battery technology. Notable areas of contribution are in asynchronous learning, federated learning with privacy constraints, and quasi-Newton methods for optimization. His research bridges theoretical advancements with practical applications in urban design, healthcare, and autonomous systems.
Professor Serdar Özoğuz is a full faculty member at the Department of Electronics and Communication Engineering , Istanbul Technical University . Holding a Ph.D. from ITU (2000) and a M.Sc. from ITU (1993) , he has taught courses like Active Network Synthesis , Basics of Electrical Circuits , and Scientific Research Ethics since 2014. His research focuses on Active RC filters Nonlinear electronic circuits Analog integrated circuit design Network synthesis . His recent publications emphasize machine learning applications in RF/microwave design , quantum computing for CAD tools , and emerging memory devices . The department's Devreler ve Sistemler Laboratuvarı Çok Geniş Ölçekli Tümdevre (VLSI) Tasarımı Laboratuvarı likely support his work. Despite no explicit awards listed, his 15+ recent articles in high-impact journals underscore his technical contributions.
Giovanni De Micheli is a Professor of Electrical Engineering and Computer Science at EPF Lausanne, Switzerland. He also serves as Director of the Integrated Systems Centre and the Institute of Electrical Engineering at EPFL, and chairs the Scientific Committee of CSEM in Neuchatel. Previously, he held academic roles at Stanford University for 18 years, including Full Professor, Associate Professor, and Assistant Professor in the Department of Electrical Engineering. His research spans synthesis of digital circuits, hardware/software co-design, low-power design, and Networks on Chip (NoC) technology. 2003: IEEE Emanuel Piore Award 2000: Golden Jubilee Medal of the IEEE CAS Society 2000: ACM Fellow 1994: IEEE Fellow 1990: IEEE/CS Distinguished Service Award 1988: NSF Presidential Young Investigator Award His seminal contributions include pioneering C-based synthesis and Boolean matching algorithms for digital circuits, foundational work in dynamic power management using stochastic control, and the development of Network-on-Chip (NoC) technology. His publications, such as "Networks on Chips: A New SoC Paradigm" and "Dynamic Power Management for Portable Systems" , have shaped modern SoC design practices. With over 400 technical articles, 9 books, and an H-index of 56, his work remains highly influential.
Georges Gielen is Full Professor in the Department of Electrical Engineering (ESAT) at KU Leuven, Belgium, and part-time Research Director at imec. He has held multiple leadership roles including Chair of ESAT Department (2012-2013, 2020-2024) and Vice-Rector for Science, Engineering & Technology (2013-2017). His academic career spans over 30 years at KU Leuven, progressing from Assistant to Full Professor. His research focuses on analog and mixed-signal integrated circuit design automation , with expertise in CAD tools, design optimization, sensor interfaces, and neuromorphic systems. His work bridges hardware design with machine learning, particularly in hardware-efficient AI implementations and biomedical applications. He has pioneered techniques for automated analog circuit sizing, topology synthesis, and reliability-aware design in nanometer CMOS. Gielen has received numerous accolades including the IEEE CAS Mac Van Valkenburg Award (2015), IEEE CAS Charles Desoer Award (2020), and EDAA Achievement Award (2021). He holds an ERC Advanced Grant AnalogCreate and is an IEEE Fellow since 2002. As a prolific scholar, he has chaired major conferences including DATE (2006), ICCAD (2007), and ESSCIRC (2017). He has graduated over 55 PhD students through the MICAS research group at KU Leuven, currently supervising 13 doctoral candidates. His research team collaborates extensively with imec and industry partners on cutting-edge projects in carbon-aware AI accelerators, uncertainty-aware design, and neuromorphic sensor interfaces.
Krisztina Kis-Katos serves as Professor for International Economic Policy at the University of Göttingen's Department of Economics, a position she assumed in 2016. She holds prominent leadership roles including Chairwoman of the Standing Field Committee of Development Economics of the German Economic Association (Verein für Socialpolitik) and Chairwoman of the Scientific Advisory Board of the RWI Leibniz Institute for Economic Research. Her institutional affiliations extend to research fellowships at IZA and RWI, along with editorial positions at the Journal of Labour Market Research, European Journal of Political Economy, Bulletin of Indonesian Economic Studies, and Journal of Development Studies. Professor Kis-Katos earned her Economics education in Szeged and Konstanz, attended the Swiss Doctoral Program at the Study Center Gerzensee, and received her doctoral degree from the University of Freiburg in 2010. Her scholarly work spans applied development economics and political economy with particular focus on how (de-)globalization and macroeconomic processes affect social and economic outcomes including labor markets, firm performance, land use change, deforestation, and conflict. Her research portfolio reveals consistent thematic threads across recent publications: the intersection of environmental concerns with economic development (particularly deforestation and palm oil in Indonesia), the gendered impacts of trade liberalization, the socioeconomic effects of pandemics like COVID-19, and the complex relationship between governance, corruption, and economic outcomes. Methodologically, her work combines rigorous econometric approaches with innovative data sources including satellite imagery and high-frequency power usage data. Teaching prize for the best doctoral course in RTG 1723, University of Göttingen (2019) Teaching prize of the Student Union of Economics of the University of Freiburg (2014) BMZ/GIZ Public Policy Award (2013) Friedrich-August-von-Hayek-award (2011) Excellence award of the KfW Development Bank (2011) Professor Kis-Katos leads multiple significant research initiatives including the BMZ-DEval funded evaluation of Madagascar's forest restoration program, the DFG-funded Thailand-Vietnam Socioeconomic Panel, and the DFG Research Training Group on Sustainable Food Systems. Her advisory role extends to supervising doctoral candidates through these projects and previously serving as spokesperson for the Research Training Group 1723 on Globalization and Development. Her substantial grant portfolio demonstrates strong research leadership across international collaborations involving institutions in Germany, Indonesia, Thailand, Vietnam, and the United States. Her work connects closely with the Collaborative Research Centre 990 on Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems in Sumatra, Indonesia, reflecting her deep engagement with environmental-economic research questions in Southeast Asia. She also contributes to interdisciplinary teams through projects like PlanetHealth examining global land-use impacts of the COVID-19 pandemic.
Lucas Introna is a Distinguished Professor of Organisation, Technology, and Ethics at Lancaster University's Management School. He holds a BCom, BA (Hons), MBA, and PhD. His research focuses on the ethical and social implications of technology, particularly information systems, informed by phenomenology and process philosophy. He has served as Associate Dean for Research (2010-2016) and Head of the Organisation, Work and Technology Department (2007-2010). **Research Interests:** Sociomateriality and performativity Ethical implications of IT (privacy, surveillance) Political studies of technology design Plagiarism and cultural values Virtuality and embodiment **Recent Work Trends:** His publications explore algorithmic governance, digital ethics, and the interplay between technology and social structures. Notable themes include blockchain trust dynamics, refugee precarity, and the ethical dimensions of facial recognition systems. **Awards:** IFIP Outstanding Service Award **Grants & Roles:** Co-founder of the Centre for the Study of Technology and Organisation Member of multiple ethics committees and editorial boards Visited professor at University of Amsterdam **Labs/Groups:** Affiliated with the Centre for Technological Futures and the Society Management and Society group.
Dirk Koch is an Associate Professor in the Department of Computer Science at the University of Manchester. He specializes in reconfigurable computing, FPGA architecture, and hardware acceleration. His research addresses challenges in field-programmable gate arrays (FPGAs), high-level synthesis, and stream processing. He leads the Advanced Processor Technology group and contributes to the Digital Futures Institute for Data Science and AI. Education: Doctorate in Computer Engineering Affiliations: Centre for Digital Trust and Society, EPSRC Functional Oxide Reconfigurable Technologies Programme His work focuses on optimizing FPGA performance, reducing power consumption, and advancing reconfigurable hardware systems. Recent projects include bitstream manipulation frameworks, runtime stream processing pipelines, and FPGA fabric optimization techniques. He has collaborated extensively with industry partners like AMD-Xilinx. Dirk Koch has supervised 11 research projects, including work on clock region process variation analysis and FPGA virus scanning. He holds grants from EPSRC and has published 62 peer-reviewed works.
Dr. Abubakar Bello is a Senior Lecturer in Criminal Justice and Program Leader at Edge Hill University's School of Law, Policing, and Criminal Justice. Previously, he held roles at Western Sydney University, including Academic Program Advisor and Lecturer in Cyber Security and Behaviour. He holds a PhD in Cyber Criminology, an MBA in Business Law and Technology, and degrees in Computer Science. His research focuses on interdisciplinary approaches to cyber security risks, threat intelligence models, and behavioral aspects of cyber crime. Education: PhD (Cyber Criminology, Murdoch University), MBA (Business Law & Tech, Western Sydney University), MSc & BSc (Computer Science, University of Wolverhampton). Research Interests: Combating cyber crime through AI and machine learning, secure systems design, and behavioral cybersecurity. Key areas include ransomware defenses, social engineering, and cybersecurity frameworks for diverse populations. Grants & Projects: Awarded funding for initiatives such as 'Social Engineered Payment Diversion Fraud' (NSW Cyber Security Network), 'Brain-Inspired Algorithm for Network Anomaly Detection' (DST Group), and 'Cyber Security Awareness Framework' (ECR Grant). Awards: 'Award for Teaching and Learning Contributing to Public Good.' Active in professional networks like the International Centre on Racism and Centre for Applied Criminal Justice Research. Labs & Collaboration: Engages in cyber investigations, forensics, and community outreach through initiatives like Western Cyber Aid. Serves as a consultant for corporate espionage cases and a speaker on ransomware and AI in law enforcement.
Ivana Nikoloska is an Assistant Professor at the Department of Electrical Engineering, Eindhoven University of Technology (TU/e). She is affiliated with the Center for Quantum Materials and Technology Eindhoven and BIASlab (Bayesian Intelligence and Stochastic Agents Lab). Her academic career includes prior roles as a Research Associate at King’s College London and a Visiting Researcher at Aalborg University. PhD: Monash University, Australia (2023) MSc & Dipl.-Ing.: University of Ss. Cyril and Methodius, North Macedonia Research Interests span foundational and applied machine learning, quantum computing, and information/communication engineering. Her work focuses on integrating Bayesian inference, variational methods, and quantum technologies for tasks like signal processing, channel estimation, and power control optimization. Quantum Machine Learning Bayesian Simulation-Based Inference Meta-learning for Wireless Systems Hybrid Quantum-Classical Architectures Stochastic Signal Processing Quantum Sensing & Metrology Notable Trends in Publications include quantum recurrent neural networks with adaptive gating, Bayesian frameworks for quantum sensing, and meta-learning applications in communication systems. She explores variational inference for planning and robust algorithms for channel estimation under non-ideal conditions.
Dr. Le-Nam Tran is a researcher at the UCD School of Electrical & Electronic Engineering , University College Dublin. His work focuses on optimizing the last hop of 5G/6G wireless networks through mathematical programming, with emphasis on energy efficiency, interference management, and security against eavesdropping. Develops low-cost, low-complexity transmission techniques Projects supported by Science Foundation Ireland Career Development Award Author of over 80 peer-reviewed publications Research Keywords: Wireless Communications Network Security Signal Processing Energy-Efficient Systems Beamforming Optimization Interference Mitigation
Dr. Anurug Chakma is a Research Fellow at the Migration Hub within the School of Regulation and Global Governance (RegNet) at The Australian National University (ANU). Previously, he served as a casual sessional academic at ANU's School of Politics and International Relations and held teaching positions at the University of Dhaka, including Lecturer and Assistant Professor in Peace and Conflict Studies. He has also contributed to research and consultancy roles at organizations such as the Bangladesh Legal Aid and Services Trust (BLAST), UNDP-CHTDF, University College London (UCL), and the United States Institute of Peace (USIP). Dr. Chakma's educational background includes: PhD in Politics and International Relations (2023), Australian National University Master's in Economics, Political Science, Law, and Criminal Science (2016), University of Antwerp Master's and Bachelor's in Peace and Conflict Studies (2012-2011), University of Dhaka His research interests span terrorism, civil conflict, peace agreements, human rights, diaspora communities, and computational social science. He focuses on topics such as the implementation of peace accords, diaspora roles in humanitarian efforts, and the impact of political ideology on conflict resolution. Dr. Chakma's recent research explores the role of diasporas in humanitarian assistance, climate change policies for health equity, nation-building in Bangladesh, and the influence of social media on violence. His work bridges theoretical frameworks with real-world case studies, emphasizing policy-relevant outcomes. While no formal students are listed, Dr. Chakma's research is supported by two projects: the ongoing "Biannual Perceptions Survey - International Development Policy" and the completed "Exploring multi-stakeholder perspectives on diaspora humanitarianism". These projects reflect his commitment to interdisciplinary research addressing global challenges. He is affiliated with the ANU South Asian Research Institute (SARI) and holds memberships in the Australia Political Science Association (APSA) and the Australian Society for Quantitative Political Science (ASQPS).
Adrien Depeursinge is a Professor at HES-SO Valais-Wallis - Haute Ecole de Gestion, affiliated with the School of Economics and Services and the Management Information Systems department. His research focuses on radiomics, personalized medicine via image-based analysis, and clinical workflow optimization. He leads the development of the QuantImage platform, a physician-centered web-based tool for radiomics research, and contributes to radiomics standardization efforts through initiatives like the Image Biomarker Standardization Initiative (IBSI). His work emphasizes machine learning applications in healthcare, including tumor segmentation, biomarker extraction, and improving diagnostic accuracy through computational models. Key research themes include: 1) Radiomics – developing quantitative imaging features for cancer diagnosis/prognosis; 2) Medical Imaging Analysis – advancing texture-based models, multi-modal fusion, and automated lesion detection; 3) Physician-AI Collaboration – designing user-centric tools for clinical integration. His contributions span neuro-oncology (brain metastases), head-and-neck cancer, and multiple sclerosis imaging. Publications emphasize methodological advancements (e.g., kernel optimization in CNNs, steerable detectors) and clinical validation (e.g., reproducibility of radiomics features across imaging protocols). He collaborates with institutions like the University Hospital of Lausanne (CHUV) and international teams on projects like the HECKTOR challenge for PET/CT tumor segmentation. His work bridges technical innovation with clinical impact, aiming to translate radiomics into actionable clinical tools. QuantImage v2, his flagship tool, enables no-code development of machine learning models using clinical imaging data. Research also includes phantom-based validation of radiomics features and addressing challenges in feature stability across imaging modalities. Current projects explore improving contour quality for radiomics studies and optimizing AI explainability in medical decision-making.
