Members
Dr Sergio Jofre, Director [s.jofre@mruuni.eu]
ORCID, Google Scholar, LinkedIn
With a PhD in Environmental Engineering from the Osaka University of Japan, and formal education across engineering, marine, natural and social sciences, Sergio has developed a strong interdisciplinary background over the years. With over two decades of international work in academia and industry, he has gained a rich intercultural experience in various countries across the Americas, Asia, and Europe consolidating his interests in global and complex contemporary issues. His research approach integrates principles, concepts, and methods from engineering, ecology, systems theory, design, innovation systems, technology development, and strategic management and decision-making. His current research explores the causes and effects of emerging complex HET interdependencies and behaviours in society’s digital transformation.
Professional Consultancy:
I will gladly support R&D activities at your organization or company in the areas of innovation, technology development, strategic management, complex systems and problems, eco-design, and resource circularity. For academic and research institutions, I extend a cordial invitation to establish collaboration in the broad area of digital transformation and the human, environmental, and technological intersection.
Dr Inzamam Mashood Nasir, Senior Researcher [inzamam.nasir@mruni.eu]
ORCID, Google Scholar, LinkedIn
Inzamam is a Senior Researcher at Mykolas Romeris University, Lithuania. His research focuses on medical imaging, explainable artificial intelligence, and trustworthy deep learning methods for clinical decision support. He holds a PhD from COMSATS University, Pakistan. He is actively engaged in interdisciplinary research that bridges artificial intelligence with healthcare applications, with particular emphasis on robustness, interpretability, and clinical relevance. He has collaborated with researchers across multiple institutions and countries and has contributed to both theoretical and applied research through peer-reviewed journal publications. Over time, he has developed strong cross-disciplinary expertise through international collaboration and sustained work on complex real-world problems.
Professional Consultancy:
I provide consultancy at the interface of academia and industry in medical imaging, explainable artificial intelligence, and advanced deep learning systems. My services include the design, optimization, and validation of AI models for real-world healthcare and safety-critical applications, with emphasis on robustness, interpretability, and regulatory-aware evaluation. I also support industry and academic partners in experimental benchmarking, technology transfer, and the preparation of high-quality scientific publications and competitive research proposals.
Dr Ahsan Waqar, Senior Researcher, Lecturer [ahsanwaqar@mruni.eu]
ORCID, Google Scholar, LinkedIn
Dr. Ahsan Waqar is a World’s Top 2% Scientist (Stanford University–Elsevier ranking) and holds a PhD, with a specialization in digital risk, safety, and performance frameworks for complex socio-technical systems. His academic training spans engineering and management, with a strong emphasis on digitalization, including artificial intelligence, blockchain, Internet of Things (IoT), Building Information Modeling (BIM), and natural language processing (NLP). He has authored over 110 peer-reviewed publications in leading international journals, with research contributions covering AI-enabled decision-support systems, blockchain-based digital governance, data-driven safety and risk analytics, IoT-supported monitoring platforms, and NLP-based knowledge extraction. His current research focuses on human-centric digital systems and the dynamics of human–environment–technology (HET) interactions in complex and safety-critical environments.
Professional Consultancy:
Dr. Waqar provides research consultancy for academic and industry projects, focusing on the digital transformation of construction and infrastructure systems through AI, BIM, IoT, blockchain, and Digital Twin technologies. His expertise includes risk and safety management, decision-support systems, and sustainable construction strategies. He welcomes research collaborations, funded project proposals, and industry–academia partnerships in digital construction, smart infrastructure, and human–environment–technology (HET) systems.
Dr Mir Hassan, Senior Researcher [mir.hassan@mruni.eu]
ORCID, Google Scholar, LinkedIn, Personal Webpage
Mir Hassan holds a PhD in Information and Communication Technology and has a strong research background in artificial intelligence, distributed intelligence, and federated learning, with solid foundations in computer architecture and embedded IoT systems. His core research agenda focuses on scalable and trustworthy distributed intelligence, combining federated learning and agentic AI to enable autonomous, privacy-preserving, and communication-efficient learning across heterogeneous and resource-constrained environments. His work addresses challenges such as system heterogeneity, staleness, robustness, and secure aggregation, with applications in smart industries, wireless sensing, healthcare systems, and cyber-physical systems. He has proposed several novel federated learning frameworks and has published extensively in high-quality international journals and conferences. He has contributed to the Horizon Europe SUSTAIn project, working on trustworthy AI solutions for sustainable and industrial applications. He has supervised MSc students and taught BSc and MSc level courses in artificial intelligence, machine learning, computer architecture, and distributed systems. He is also an instructor in the EIT Digital education portal, where he teaches Ethics of Trustworthy AI and Introduction to Emotion AI. He is currently working toward establishing a small research group on federated and agentic distributed intelligence, integrating research, teaching, and applied collaboration in healthcare and smart industry domains.
Professional Consultancy:
I provide research and technical consultancy in AI for medical and healthcare systems and AI-driven solutions for smart industry problems, with a focus on federated learning, distributed and agentic intelligence, edge AI, and embedded systems. My services include the design and evaluation of distributed and federated AI systems, secure and communication-efficient learning strategies, experimental benchmarking, and support for applied research projects, technology transfer, and the preparation of competitive Horizon Europe proposals and high-quality scientific publications.