جست‌وجوی استاد و پژوهشگر

Maria-Luciana Blahaمشاهده پروفایل

استادیار

• Intelligent Automation
• Business Management
• Technology Adoption
• +۴ مورد دیگر

Maria-Luciana Blaha is an Assistant Professor in Business Management and Intelligent Automation at Heriot-Watt University, affiliated with the School of Social Sciences and Edinburgh Business School. She leads the Intelligent Automation Systems (IAS) Lab and coordinates the Graduate Apprenticeships in Business Management Year 1 program. With a PhD from the University of Aberdeen and extensive professional experience across sectors, her research focuses on AI, RPA, chatbots, and their impact on organizational behavior. She was awarded the 2023 Early Career Researcher of the Year by the School of Social Sciences. Education : PhD in Business Management, University of Aberdeen (Elphinstone Scholarship, British Federation of Women Graduates Bursary) Research Interests : Blaha investigates Intelligent Automation systems, posthumanism, organizational behavior, and ethical AI adoption. Her work bridges science/technology studies, business management, and computing science. Current projects include automation in Ghana/UK manufacturing, ethical AI frameworks for healthcare, and generative AI in HR. Grants & Projects (2025-): TransiT: Decarbonisation via Digital Twinning (EPSRC) Lighthouse Project: SME Manufacturing Audit (Innovate UK) Local Authority AI Readiness Review (Interface Scotland) 2024 Projects : Thermo Fisher/National Robotarium AKTP (Innovate UK) Extend Robotics Feasibility Study (Interface Scotland) Media & Outreach : Blaha contributes to Scottish AI Alliance initiatives, speaks globally on AI/automation, and engages in public lectures like the 'Age of AI' series. Her media features include Financial Times and pandemic-era fact-checking insights. Labs & Teams : Leads the IAS Lab, collaborates with National Robotarium, and oversees AKT projects with industry partners.

• Software Engineering
• Model-Based Software Engineering
• Automated Reasoning
• +۵ مورد دیگر

Sebastián Uchitel is a Professor at the Department of Computing, Imperial College London, UK. His research focuses on foundational aspects of Software Engineering, particularly in modeling and analysis for automated reasoning, verification of probabilistic systems, controller synthesis, and adaptive systems. He has led major research projects, including the ERC-funded IDEAS StG project on Partial Behaviour Modelling and the European FP6 SENSORIA project. Research Interests: Model-Based Software Engineering, Controller Synthesis, Probabilistic Systems, Adaptive Systems, Requirements Engineering External Roles: General Chair, International Conference on Software Engineering (2017); Associate Editor, Elsevier Science of Computer Programming; Steering Committee, International Conference on Software Engineering His recent work explores intersections between Software Engineering and AI, including assured adaptive systems and logic-based learning. A Senior Member of IEEE and Distinguished Scientist of ACM , he has received awards like the Houssay Prize (2015) and Philip Leverhulme Prize (2005). Collaborators include institutions in Argentina, Canada, and the UK. Selected Publications: 150+ peer-reviewed works spanning controller synthesis, requirements engineering, and formal methods Students: Supervised 12 PhD students since 2003 Grants: Principal Investigator for 3 major grants (2005-2016) totaling over $3.7M USD, including: 2013-2016: Technology Platform in Software Engineering (ANPCYT, $1.6M) 2009-2014: ERC IDEAS StG on Partial Behaviour Modelling (€1.4M) 2005-2008: FP6 SENSORIA Project (€0.7M)

Smitha Gopinathمشاهده پروفایل

مدرس

• Sustainable engineering systems
• Carbon capture, utilisation and storage (CCUS)
• Renewable energy systems
• +۵ مورد دیگر

Dr Smitha Gopinath is a Lecturer in the School of Chemical, Materials and Biological Engineering at the University of Sheffield , where she leads research in sustainable engineering systems within the Sustainable Design Laboratory (SDL) . Education & Career Path PhD in Chemical Engineering, Imperial College London Post-doctoral researcher, Applied Mathematics and Plasma Physics Group, Los Alamos National Laboratory Research Focus Dr Gopinath’s interdisciplinary work centres on the design, calibration and operation of sustainable engineering systems . She develops high-fidelity models and large-scale optimisation algorithms tailored to energy and materials challenges. Core interests include: Thermo-mechanical energy conversion devices (heat pumps, organic Rankine cycles) Carbon-capture utilisation and storage (CCUS) via novel solvents and separation systems Power-grid expansion and operation for renewable integration and decarbonisation Methodologically, she integrates Integrated Molecular and Process Synthesis (IMPS) with Optimisation Accelerated by domain Knowledge (OAK) to co-design molecules, materials and flowsheets that meet stringent energy and environmental targets. Publication Landscape Across 2015–2025 her publications reveal a clear trajectory from fundamental thermodynamic measurements and molecular design toward rigorous optimisation of large-scale energy systems. Early work concentrated on CO₂ solubility and carbonation kinetics of steel slag, providing essential data for carbon-sequestration schemes. Subsequent papers introduced advanced optimisation frameworks—outer-approximation algorithms, exact reformulations and feasibility-based methods—applied to solvent-based CO₂ capture, organic Rankine cycle working-fluid selection and AC optimal power flow (ACOPF). Recent contributions benchmark global optimality certificates for ACOPF problems, underscoring her drive to bridge chemical process systems engineering with electrical power systems optimisation. Teaching & Mentoring Dr Gopinath teaches undergraduate modules: CPE440 (Particle Technology) CPE170 (Particle Technology) She actively invites prospective PhD students to join the Sustainable Design Laboratory, offering supervision on projects spanning sustainable process design, renewable energy systems and algorithmic optimisation. Laboratory & Collaborative Networks She directs the Sustainable Design Laboratory (SDL), a multidisciplinary team leveraging systems engineering, multi-scale modelling, process simulation and optimisation to re-imagine a sustainable chemical and energy industry. The SDL collaborates with international partners, including Los Alamos National Laboratory and leading researchers in applied mathematics and power systems engineering.

Tanya Bondaroukمشاهده پروفایل

استاد

• Human Resource Management
• Electronic HRM
• Technology Impact on Workplaces
• +۳ مورد دیگر

Prof. Tanya Bondarouk is a distinguished academic affiliated with the Digital Society Institute and Faculty of Behavioural, Management and Social Sciences at the University of Twente. Her research focuses on Human Resource Management (HRM), electronic HRM systems, and the impact of disruptive technologies on work environments. She holds leadership roles including Board Member of the National Network of Female Professors (Landelijk Netwerk Vrouwelijke Hoogleraren). Her academic contributions span over 250 publications, including influential works on AI in HRM, open innovation, and gig economy challenges. Notable awards include the Best HRM Scientist in The Netherlands (2018) and the Inspiration Award (2019). Research interests: Technology-human interaction in workplaces, HRM strategies for innovation, and digital transformation in organizations. Recent articles analyze AI-driven recruitment, generational differences in tech engagement, and algorithmic management dilemmas. Prof. Bondarouk actively engages in academic networks, organizing conferences like the 38th EGOS Colloquium (2022), and provides expert commentary on digital labor platforms and employer branding strategies. Her work bridges theoretical HRM frameworks with real-world organizational challenges.

Martijn R.K. Mesمشاهده پروفایل

استاد

• Transportation and Logistics Management
• Artificial Intelligence for Logistics
• Synchromodal Transport
• +۱۱ مورد دیگر

Martijn Mes is a full professor of Transportation and Logistics Management and chair of the Industrial Engineering & Business Information Systems section at the University of Twente, Netherlands. He leads research and education initiatives that integrate AI, simulation and optimisation into logistics and supply-chain innovation. Education: Ph.D. in Operations Research, University of Twente – 2008 M.Sc. in Applied Mathematics, University of Twente – 2002 Post-doctoral researcher, Princeton University, Dept. of Operations Research & Financial Engineering Research focus: Mes develops quantitative models and AI techniques for strategic, tactical and operational logistics challenges. His work spans three application pillars: Emergency & humanitarian logistics – rapid relief distribution with trucks and UAVs Urban logistics – city distribution, self-organising systems and last-mile innovations Sustainable logistics – synchromodal transport, green ports and electric/autonomous fleets Methodologically he combines approximate dynamic programming, reinforcement learning, multi-agent simulation, discrete-event simulation and stochastic optimisation to create decision-support tools for industry and government. Publications trend: Recent articles (2025-2022) exhibit a strong emphasis on integrating reinforcement learning and stochastic optimisation into dynamic vehicle routing, drone-assisted delivery and post-disaster inventory allocation, signalling a shift towards data-driven, real-time logistic systems. Grants & projects: Mes has coordinated and participated in numerous national and European projects on sustainable logistics, urban distribution, port optimisation and healthcare logistics, frequently collaborating with industry partners and public bodies. Teaching & supervision: He coordinates and lectures in the BSc and MSc programmes Industrial Engineering & Management, offering courses on simulation, queueing theory, dynamic programming, Markov chains, transportation management and technology management. He has authored a widely used Plant Simulation tutorial and supervises PhD candidates working on AI-driven logistics, autonomous vehicles and digital twins.

• AI & Neuroscience
• Biomedical Engineering
• Neurotechnology
• +۷ مورد دیگر

Aldo Faisal is a Professor of AI & Neuroscience at Imperial College London's Department of Bioengineering and Faculty of Engineering. He is also the Founding Director of the UKRI Centre for Doctoral Training in AI for Healthcare (£20M), leading the Faisal Lab. His roles include associate investigator at the MRC London Institute of Medical Sciences and affiliation with the Gatsby Computational Neuroscience Unit (UCL). His research bridges AI, neuroscience, and healthcare, focusing on neurotechnology, human behavior analysis, and clinical applications. Education: Studied Computer Science and Physics in Germany, followed by Biology at the University of Cambridge (Emmanuel College). Earned a PhD in Neuroscience under Simon Laughlin, and postdoctoral work with Daniel Wolpert on sensorimotor control. Prior professional experience includes roles at McKinsey & Co. and Credit Suisse. Research Interests: Combines cross-disciplinary approaches to study brain-behavior relationships, developing technologies for neurological disorders and amputees. Key labs include the Brain & Behaviour Lab (neurotechnology) and Behaviour Analytics Lab (behavioral data science). Techniques include machine learning, robotics, and neuroimaging (EEG/fNIRS). Publications: Over 100+ peer-reviewed articles, spanning AI in healthcare, motor learning, and neurotechnology. Recent work emphasizes safety of AI in critical care, wearable biomarkers for neuromuscular diseases, and human-AI collaboration. Awards: UKRI Turing AI Fellowship, Toyota Mobility Prize ($50k), Rosetree Interdisciplinary Award (£300k), and fellowships from German National Merit Foundation and Böhringer-Ingelheim Foundation. Elected to Global Futures Council (WEF, 2016). Grants & Labs: Leads £20M CDT in AI for Healthcare, £2M Turing Fellowship project, and manages labs at Imperial and University of Bayreuth (Germany). Collaborates with institutions like CRUK Convergence Science Centre and Data Science Institute.

• Dementia
• Depression
• Delirium
• +۴ مورد دیگر

Professor Wendy Moyle is a leading academic in dementia care and assistive technologies, affiliated with Griffith University in the School of Nursing and Midwifery . With a PhD from Queensland University of Technology and over 27 completed PhD supervisions, she has received numerous accolades including the 2023 VC Research Excellence Award in Research Supervision and recognition as one of the World's 50 Renowned Women in Robotics (2020). Her work focuses on evidence-based interventions for dementia patients, emphasizing social robotics, pain management, and behavioral symptom mitigation. Bachelor of Nursing, Flinders University (1989) Master of Health Science, Queensland University of Technology PhD, Queensland University of Technology (1997) Her research spans Dementia , Social Robots , and Geriatric Nursing , with a strong emphasis on improving quality of life through technological innovations. Recent publications highlight the role of humanoid robots like Telenoid and PARO in enhancing engagement and managing chronic pain in dementia patients. She has secured significant grants from NHMRC, Wellcome Trust, and international institutions to advance her work. VC Research Excellence Award in Research Supervision (2023) World's 50 Renowned Women in Robotics (Analytics Insight, 2020) International Nurse Researcher Hall of Fame (Sigma, 2019) International Women’s Day 2016 Global Innovation Award As a prolific supervisor, she has guided 27 PhD students to completion, many achieving no/minor revision outcomes. Her collaborative projects span Australia, China, and Taiwan, involving multidisciplinary teams for dementia research. She actively contributes to healthcare policy and education frameworks, particularly in residential aged care and informal caregiver support.

• Artificial Intelligence
• Cognitive Neuroscience
• Robotics
• +۳ مورد دیگر

Prof. W.F.G. Haselager is a Professor of Artificial Intelligence at Radboud University Nijmegen, affiliated with the Donders Institute for Brain, Cognition and Behaviour and the Donders Centre for Cognition. He holds dual expertise in philosophy, psychology, and AI, focusing on societal implications of emerging technologies. His research integrates empirical methods (e.g., robotics, computational modeling) with philosophical inquiry into agency, responsibility, and human self-understanding. Education: MSc degrees in Philosophy and Psychology, PhD (1995) from Vrije Universiteit Amsterdam. Teaching responsibilities include bachelor/master programs in AI and Cognitive Neuroscience. Active in public engagement through lectures/workshops on AI ethics, neurotechnology, and free will. Key research themes include neuroethics, AI equity, and brain-computer interfacing. Current projects include the ELSA Lab (AI for Health Equity) and 'Healthy Data' initiatives addressing algorithmic bias and medical AI oversight. He advises Zander Labs on neurotechnology ethics and co-leads multi-institutional grants exploring conversational AI and neurodiverse education. Media appearances include Dutch TV/NOS coverage of brain implants and podcasts on AI sentience. Ancillary activities include the 'Pim Haselager Lectures' series and advisory roles in neurotechnology ethics.

• agent and multi-agent systems
• online auctions
• machine learning
• +۶ مورد دیگر

Patricia Anthony serves as Associate Professor at Lincoln University's School of Landscape Architecture in New Zealand, where she holds an ORCID identifier 0000-0002-4991-3340. Her academic appointments include Faculty Postgraduate Chair for the Faculty of Environment, Society and Design (2021-2024) and current affiliation with the Centre for Geospatial and Computing Technologies (2025-present). Previously, she served as Head of Department (2016-2017), Department Postgraduate Coordinator (2014-2016), and SHIFT Coordinator (2017-2020). Her educational background comprises a Ph.D. from the University of Southampton, United Kingdom; an M.Sc. from Birkbeck, University of London, United Kingdom; and a BSc (High Honors) from the State University of New York, United States. She is proficient in Malay language, with reading, writing, and speaking capabilities. Dr. Anthony's research centers on agent and multi-agent systems, utilizing artificial intelligence techniques including machine learning, evolutionary computation, and text processing as decision-making strategies for agents. She is recognized as a leading researcher applying intelligent agents across diverse domains such as online auctions, agriculture, education, and social media analysis. Her specialized work in sentiment analysis and emotion identification enables agents to detect emotional states in textual communications, with recent applications in earthquake tweet analysis. Her publication record demonstrates consistent scholarly output with over 130 publications, showing particular strength in applying multi-agent systems to practical challenges. Recent work reveals three major research streams: trust and reputation management in IoT environments (accounting for approximately 30% of recent publications), agricultural technology applications including mastitis detection and water resource management (approximately 40%), and social media analysis focusing on elderly technology adoption and cyber aggression classification (approximately 30%). Adjunct Professor, Hubei University of Technology, Wuhan, China Program Committee/Senior Program Committee member for Pacific Rim International Conferences on Artificial Intelligence (PRICAI) 2016, 2018, 2019 Co-chair for International Carnahan Conference on Security Technology (ICCST) 2014, 2016, 2018, 2020 Member of Institute of Electrical and Electronics Engineers (IEEE) Reviewer for Engineering Applications of Artificial Intelligence, Malaysian Journal of Computer Science, and Adaptive Behaviour Dr. Anthony has supervised numerous postgraduate students across multiple research areas related to multi-agent systems, with completed projects spanning cyber aggression classification, agricultural technology, IoT security, and elderly technology adoption. She serves as an examiner for advanced computing courses including Advanced Database (COMP643), Advanced Programming (COMP642), and Studio Project (COMP639), demonstrating her integration within the university's computing curriculum despite her Landscape Architecture appointment. Her research aligns with Sustainable Development Goal 11 (Sustainable Cities and Communities), reflecting her commitment to applying computational techniques to address real-world challenges in urban and community contexts. She actively collaborates across disciplines through the Centre for Geospatial and Computing Technologies, bridging computational methods with landscape architecture applications.

Prateek Bansalمشاهده پروفایل

استادیار

• Transportation Engineering
• Data Science
• Artificial Intelligence
• +۶ مورد دیگر

Dr. Prateek Bansal is a Presidential Young Assistant Professor at the National University of Singapore (NUS), leading the Behavioural Cognitive Science (BeCoS) lab. His research focuses on developing AI-driven methodologies to analyze mobility behavior and urban systems. He holds a PhD from Cornell University and has held fellowships at Imperial College London and visiting roles at multiple institutions. His expertise spans transportation engineering, econometrics, and causal inference. Dr. Bansal is an elected board member of the International Association of Travel Behaviour Research and serves on editorial boards of top journals like Transportation Research Part B . He has received prestigious awards including the Presidential Young Professorship (2021) and Leverhulme Trust Fellowship (2020). His lab investigates individual-level decision-making models and system-level urban planning frameworks. Education: PhD, Transportation Engineering (Cornell University, 2016-2019); MS, Transportation Engineering (UT Austin, 2013-2015); BTech, Civil Engineering (IIT Delhi, 2008-2013). Research interests include neurophysiological data modeling, activity-based urban systems, and causal inference for infrastructure planning. Notable contributions include studies on electric vehicle adoption, ride-sourcing demand estimation, and ethical decisions in autonomous systems. His work integrates machine learning with traditional transportation models to address contemporary challenges like urban congestion and sustainable mobility. Professional activities include organizing conferences, delivering keynotes (e.g., 2023 Summer School of Behavior Modeling), and advising on policy issues such as carsharing and road safety. The BeCoS lab collaborates globally, leveraging interdisciplinary approaches to advance transportation science.

Kartic Subrمشاهده پروفایل

مدرس ارشد

• Computer Graphics
• Monte Carlo Rendering
• Physics-based Simulation
• +۱۳ مورد دیگر

Kartic Subr is a Senior Lecturer (equivalent to Associate Professor) in the School of Informatics at the University of Edinburgh, where he conducts research at the intersection of computer graphics, machine learning, and robotics. He is affiliated with the Institute of Perception, Action and Behaviour and leads an active research group in physics-aware simulation and AI for scientific discovery. His research interests span Computer Graphics , Monte Carlo Rendering , Physics-based Simulation , Machine Learning , Robotics , and Computational Biology . He has made significant contributions to rendering theory, light transport analysis, BRDF modeling, and simulation of fluids and fractures. Recently, his group has applied deep learning to protein design, achieving notable success in international competitions. The recent publications reflect a strong trend toward interdisciplinary research, combining computer graphics with AI and biology. Key themes include explainable AI for physics-aware interfaces (e.g., CueTip), neural rendering (NeRF), protein design with CNNs, and reward learning in robotics. His group regularly publishes in top venues such as SIGGRAPH, NeurIPS, and IEEE RA-L. Royal Society University Research Fellowship (2014–2024) Lead, GCRF Impact Accelerator (2019) Lead, EPSRC First Grant (2017) Royal Society Challenge Grant (2016) Royal Society Newton International Fellow (2010) Marie-Curie Visitor (2006) Best Paper Honorable Mention, I3D 2012 Best Paper, I3D 2011 Kartic Subr actively supervises PhD students and postdocs, including Leonardo Castorina, Zhiyuan Zhang, and Kevin Denamganaï. Former students have gone on to positions at DeepMind, University of Edinburgh, and industry. He has secured multiple grants, including from the Royal Society and EPSRC. His research group collaborates across disciplines, particularly with biological sciences on protein design. He leads projects on approximate physics for robotics, protein design via deep learning, and interactive rendering systems. The group has developed frameworks like TIMED for de novo protein design and tools for explainable physics-aware assistants.

Yichuan Wangمشاهده پروفایل

مدرس ارشد

• Digital Marketing
• Healthcare Information Systems
• Big Data Analytics
• +۴ مورد دیگر

Dr. Yichuan Wang is a Senior Lecturer in Digital Marketing at the Sheffield University Management School (SUMS). Previously, he held positions at Newcastle University Business School and Auburn University (USA). His interdisciplinary research focuses on digital marketing, healthcare information systems, and big data analytics, with over 100 publications and 6,000 citations. He co-founded the International Conference on Digital Health and Medical Analytics (since 2018) and leads industry projects enhancing healthcare quality via analytics. His teaching innovations include serious games for business ethics education, supported by an NSF grant ($200k), and he was a Fellow of the Higher Education Academy (2018). Education: PhD in Marketing from Auburn University. Research Interests: Social media & digital marketing strategies Big data analytics and AI applications Digital health and business value Sharing economy dynamics Business transformation through digitalization Awards: Nominated for Teaching Excellence Awards (2018) Fellow of the Higher Education Academy (2018) Teaching & Industry Engagement: Incorporates real-world case studies and simulation games into modules like MGT3006. Collaborates with healthcare institutions to improve care through information systems. Part of the Behavioural Research for Inclusivity, Sustainability and Technological Transformation (BRISTT) research group. Lab/Teams: Active in the BRISTT group, focusing on behavioral insights for sustainable technological adoption.

Emma Norlingمشاهده پروفایل

استاد

• Agent-Based Modelling
• Social Simulation
• Cognitive Modelling
• +۳ مورد دیگر

Professor Emma Norling is a Professor of Engineering Education and Director of Education in the School of Computer Science at the University of Sheffield. She holds a BEng (Hons) from the University of Melbourne and a PhD in Computer Science from the University of Sheffield. Her career includes postdoctoral work at Manchester Metropolitan University's Centre for Policy Modelling and a lecturing role at its School of Mathematics, Computing and Digital Technology. Her research focuses on agent-based systems, particularly cognitive and social simulations, with an emphasis on integrating social intelligence into computational models. She leads the Teaching Specialists group and oversees accreditation and professional institution relations. Key roles include directing educational strategy and promoting pedagogical innovation in engineering and computing education. Her publications highlight contributions to agent-based modelling methodologies, emergency response systems, and social simulation frameworks. Notable works include studies on food web evolution, morphogenetic network growth for emergency teams, and the application of BDI agents in human behavior modelling. She actively engages with interdisciplinary approaches, bridging computer science with education and social sciences. Professional service includes leading educational accreditation efforts and fostering collaboration between academia and industry. She is a sought-after expert in computational models of human behavior and their implications for educational technology and societal systems.

Justin Brienzaمشاهده پروفایل

مدرس ارشد

• Applied and developmental psychology
• Cognitive and computational psychology
• Psychology

Dr. Justin Brienza is a Senior Lecturer at the School of Business, University of Queensland , where he teaches Organisational Behaviour , Manager Skills/Contemporary Business Communication , and Wise Leadership . Previously, he taught at the Lazaridis School of Business and Economics at Wilfrid Laurier University, Canada. Education: Honors Bachelor of Science in Cognitive Science & Artificial Intelligence and Psychology at University of Toronto Masters and PhD in Industrial/Organizational Psychology at University of Waterloo His research focuses on wisdom and wise reasoning in complex social problems, reducing bias, and developing balanced decision-making. Topics span interpersonal cooperation , organizational dynamics , and AI ethics , with applications in leadership , conflict resolution , and social equity . His recent publications analyze self-control perception, gender pay gaps, and Indigenous conflict management frameworks. Justin Brienza has received the Kellogg School of Management's Dispute Resolution Center Scholar Award . His work appears in Nature Human Behaviour , Journal of Personality and Social Psychology , and Cambridge Handbook of Wisdom . He serves as a peer reviewer for journals like Journal of Personality and Social Psychology and Journal of Cross-Cultural Psychology , and his research has been featured in TIME , NewsWeek , and Science Magazine .

• Robotics
• Autonomous Systems
• Machine Learning
• +۳ مورد دیگر

Björn Åstrand serves as a Senior Lecturer at Halmstad University's School of Information Technology, specializing in mechatronics and autonomous systems with the additional qualification of Associate Professor (Docent). His research develops perception and cognition systems for mobile robots, focusing on agricultural robotics, automatic guided vehicles, and self-driving vehicles. He applies signal processing and machine learning to semantic mapping, human tracking, agent behaviour modelling, intention estimation, object detection/classification, and autonomous vehicle safety systems. Dr. Åstrand teaches Electrical Circuits and Electronics, Design of Mechatronical Systems, Intelligent Vehicles, Robotics, Sensors, Signals and Systems, and Signals and Sensors courses. He acts as course responsible and examiner for Bachelor of Science engineering theses while supervising undergraduate, postgraduate, and PhD students. No scientific awards were documented in the source materials. His academic supervision spans undergraduate theses, postgraduate research, and PhD candidate mentorship, with primary responsibility for engineering program thesis examination.