جست‌وجوی استاد و پژوهشگر

• Climate and Energy Finance
• Corporate Risk Management
• International Economics/Finance
• +۳ مورد دیگر

Dr. Bernard Njindan Iyke is a Lecturer in Finance at La Trobe University, specializing in climate and energy finance, corporate risk management, and international economics/finance. He holds an ORCID identifier (0000-0002-9217-1856) and has extensive experience as a consultant for central banks and international organizations. His recent research includes leading the Australian Government-funded 'Quantum Enhanced Optimisation for Energy Efficient Data Centres' project. He actively supervises postgraduate research students focusing on Sustainable Development Goals 13 (Climate Action) and 7 (Affordable and Clean Energy). Dr. Iyke's research interests span climate finance, energy security, geopolitical risk analysis, and macroeconomic policy interactions. His work frequently explores emerging markets, particularly in Asia and Africa, with notable contributions on financial stability, currency dynamics, and pandemic economic impacts. He has presented at institutions like the University of Oxford and the Asian Development Bank Institute. His recent publications analyze topics such as financial cycle synchronization in emerging economies, energy investment under climate risks, and the interplay between monetary policy and asset prices in ASEAN countries. While no explicit awards are listed, his high citation counts (e.g., over 90 citations for his 2024 energy security paper) reflect significant academic impact. He teaches courses on commercial lending and bank strategy, integrating real-world financial technology and regulatory challenges. Dr. Iyke has secured government grants totaling millions AUD, notably the 2024 Quantum Optimisation project. He advises on policy matters related to energy transition and financial resilience, maintaining active collaboration with central banks and multilateral institutions. His research agenda emphasizes bridging theoretical economics with practical policy solutions for sustainable development.

• Robotics
• Machine Learning
• Reinforcement Learning
• +۳ مورد دیگر

Pawel Ladosz is a Lecturer in Engineering Systems for Robotics at the Department of Mechanical and Aerospace Engineering, The University of Manchester. His research focuses on applying machine learning and computer vision to mobile robots, particularly in extreme environments such as total darkness or cluttered spaces. He is actively involved in developing autonomous navigation systems, wireless signal mapping, and high-level decision-making for robotic swarms. He teaches courses including Robotic Systems Design Project and Autonomous Mobile Robots. Education: PhD in Establishing and Optimising Unmanned Airborne Relay Networks (Loughborough University, 2014–2019) MEng in Aerospace Engineering (The University of Manchester, 2010–2014) Research Interests: Ladosz’s work emphasizes reinforcement learning for robotics, vision-based autonomous systems, and exploration in challenging environments. His projects often intersect with UN Sustainable Development Goals, contributing to innovations in robotic autonomy and sensor networks. Awards: He received the 2nd Autonomous Flying Technology Competition award in 2021, recognizing his contributions to autonomous flight systems. His research has also led to the establishment of the Centre for Robotic Autonomy in Demanding and Long-Lasting Environments (CRADLE), fostering cross-disciplinary collaborations. Grants & Projects: As Principal Investigator in the Aerospace Engineering initiative (2010–2035), he explores UAV communication networks and trajectory planning. His work addresses urban environment challenges, including relay positioning and signal prediction. Labs/Teams: Ladosz contributes to CRADLE, advancing robotic autonomy in extreme scenarios. His lab focuses on integrating AI and robotics for real-world applications.

• Medical Imaging
• Breast Cancer Diagnosis
• Phase-Contrast Tomography
• +۴ مورد دیگر

Dr. Amir Tavakoli Taba is a Senior Lecturer in Medical Imaging Sciences at the University of Sydney, where he co-directs the Medical Image Optimisation and Perception Group (MIOPeG). He specializes in improving medical imaging accuracy, particularly in breast cancer diagnosis, through advancements like phase-contrast tomography and AI integration. His work bridges technological innovations (e.g., low-dose imaging) with clinical practice, emphasizing quality control and radiologist performance analysis. Education: PhD (University of Sydney) MEngSc (University of New South Wales) BSc (University of Tehran) Research Interests: Dr. Taba’s research focuses on phase-contrast computed tomography (PCT), AI-driven diagnostic tools, and clinical workflow optimization. His projects include the world’s first PCT clinical trial (scheduled for 2024 in Melbourne) and collaborations with institutions like ANSTO, Harvard Medical School, and the University of Iowa. He also investigates radiologist expertise development and the role of social networks in medical decision-making. Grants & Awards: NHMRC Synergy Grant (IMPACT: Implementation of X-ray Phase-Contrast Tomography) International recognition, including the SPIE Medical Imaging Award Advising & Labs: Current students: Mohammed ALANAZI (abdominal CT optimization), Jenna ARBID (phase-contrast imaging) Labs: MIOPeG, part of the Sydney Vital and Sydney Catalyst cancer research networks Teaching: Courses in imaging technologies, medical image perception, and clinical capstone projects for diagnostic radiography students.

• Embedded Systems
• System-on-Chip (SoC) Design
• Computer Architecture
• +۵ مورد دیگر

Professor Klaus McDonald-Maier is a full Professor in the School of Computer Science and Electronic Engineering (CSEE) at the University of Essex , where he leads the Embedded and Intelligent Systems (EIS) Research Laboratory and heads the Intelligent Embedded Systems and Environments Research Group . He is also Director of Impact , Visiting Professor at the University of Kent, and Visiting Research Affiliate at NASA Jet Propulsion Laboratory, California Institute of Technology. Education PhD in High-Performance Parallel Neural Network Architectures, Friedrich-Schiller-University Jena (Germany, 1999) Electronic Engineering studies, University of Ulm (Germany) Electronic Engineering studies, Cardiff University (Wales) Electronic Engineering studies, École Supérieur de Chimie Physique Électronique de Lyon (CPE-Lyon) (France) Research Interests Professor McDonald-Maier’s research integrates embedded systems , System-on-Chip (SoC) architectures , and AI-driven robotics . He pioneers visual place recognition techniques that remain robust under severe appearance and viewpoint changes, develops cybersecurity frameworks based on ICMetrics for autonomous vehicles and IoT, and designs approximate real-time computing solutions for energy-constrained multicore and FPGA platforms. His work on radiation-tolerant systems supports space and nuclear applications, while his bio-inspired algorithms enable lightweight, neuromorphic perception on resource-limited robots. Publication Trends Between 2022 and 2025 his output converges on FPGA-accelerated AI , secure edge intelligence , visual navigation for autonomous systems , and healthcare analytics . He repeatedly couples rigorous algorithmic innovation with practical hardware deployment, yielding energy-efficient, real-time systems validated in domains ranging from autonomous driving to post-stroke rehabilitation. Scientific Awards & Recognition Best Paper Award – IEEE Transactions on Sustainable Computing (2024) Best Paper Award – IEEE/ACM DATE (2024) Best Paper Award – IEEE Systems Journal (2022) Best Paper Award – IEEE Sensors Journal (2021) Best Paper Award – IEEE Access (2020) Research Grants & Industrial Collaboration He has secured major funding from EPSRC , EU Horizon 2020 , Innovate UK , and industry partners. Current projects span trustworthy autonomy, radiation-hardened edge AI, and AI-enhanced rehabilitation technologies. He is Chief Scientist of UltraSoC Technologies Ltd and CEO of Metrarc Ltd , commercialising University research in semiconductor debug and cybersecurity respectively. Laboratory & Team Leadership As Director of the Embedded and Intelligent Systems Laboratory (EIS Lab) , he oversees a multidisciplinary team of researchers and PhD students, providing state-of-the-art FPGA, robotics, and embedded-systems facilities. The lab collaborates closely with NASA JPL, UK Atomic Energy Authority, and leading semiconductor firms to translate fundamental research into high-impact industrial solutions.

Tony Janمشاهده پروفایل

استاد

• Artificial Intelligence
• Cybersecurity
• Machine Learning
• +۷ مورد دیگر

Professor Tony Jan leads the Centre for Artificial Intelligence Research and Optimisation (AIRO) at Torrens University Australia's Design and Creative Technology school. He holds a PhD in Computing Science from the University of Technology Sydney (2004) and a Bachelor of Engineering from the University of Western Australia (1999). His research focuses on federated machine learning for IoT security, ensembled machine learning for real-time applications, cognitive machines for human-centric computing, and smart sensor networks for healthcare and security. He has secured ARC grants and industry partnerships with NVIDIA, IBM, and Microsoft. Awards include the 2024 SEI Global Academic Excellence Award and the 2023 Torrens University Excellence Award. Research collaborations span global partners, with contributions to UN Sustainable Development Goals in education and industry. His work bridges academia and industry, expanding AI program enrollments by 2,000+ students and enhancing student satisfaction by 15%. He advises PhD students on topics like IIoT cybersecurity and smart cities, and has produced over 97 publications since 1999. Education: PhD (UTS, 2004), BEng (UWA, 1999) Research Themes: AI for Industry 5.0, Cybersecurity, Smart Cities, Healthcare Technology Key Partnerships: NVIDIA, CIMIC, Palo Alto Networks Recent Projects: Federated learning for health IoT, drone vision intelligence, ransomware detection His work emphasizes ethical AI adoption in design and healthcare, with publications exploring AI ethics, generative AI applications, and sustainable technology integration.

• Obstetrics
• Gynaecology
• Maternal Health
• +۵ مورد دیگر

Clinical Associate Professor Therese McGee is affiliated with the Westmead Clinical School, part of the Sydney Medical School at the University of Sydney. Her work focuses on maternal and neonatal health, particularly in obstetrics and gynaecology, with a strong emphasis on clinical research and guideline implementation. She investigates diverse topics such as perinatal outcomes, pandemic impacts on healthcare, and optimizing healthcare delivery models. Her research often addresses challenges in multiethnic populations and evaluates interventions to improve patient care and reduce healthcare costs. Her research interests include perinatal care, gestational diabetes, hypertensive disorders in pregnancy, and the validation of hospital data to ensure accurate reporting of maternal medical conditions. She also explores fetal surveillance techniques, neonatal jaundice management, and the efficacy of midwifery-led care models. Her work frequently employs mixed-methods and cohort study designs, reflecting a commitment to evidence-based practice. Therese has contributed to studies on uterine rupture, anaemia in pregnancy, and the use of rapid diagnostic tests for preventing neonatal infections. Her articles highlight a focus on healthcare quality, patient-centered care, and improving clinical guidelines through rigorous analysis. The scope of her research spans both clinical and public health dimensions, addressing issues such as antibiotic exposure reduction and maternal morbidity in Australian contexts. Grants: Efficacy and safety of vaccination in at-risk pregnant women and impact on infant immune responses (2017) Are we there yet? Optimising timing of planned birth to improve newborn outcomes and reduce health service costs (2017) Therese is involved in collaborative projects through Sydney Health Partners, focusing on applied research with real-world healthcare implications. Her studies often involve interdisciplinary teams, reflecting her role in bridging clinical practice and academic research. While no formal student advisees are listed, her publications suggest active participation in mentoring research cohorts.

Zhongbei Tianمشاهده پروفایل

استادیار

• Transport Energy System Decarbonisation
• Transport Energy System Modelling and Analysis
• Railway Traction Power Supply Systems
• +۳ مورد دیگر

Dr Zhongbei Tian is an Assistant Professor in Transport Energy Systems at the University of Birmingham's School of Engineering, within the Department of Electronic, Electrical and Systems Engineering. His research focuses on decarbonising transport energy systems, including railway, road, and ship energy systems, with emphasis on energy-efficient train control and sustainable integration of energy systems. He has led projects funded by EPSRC, Royal Society, Horizon 2020, Network Rail, RSSB, and Innovate UK. His work has been implemented globally, including in the UK (Network Rail, Edinburgh Tram), Spain (Madrid Metro), Singapore (SMRT), and China (Beijing and Guangzhou Metro). Awards: 2016 ERESS Award for Best Energy Efficiency Project for Railways. His research spans energy system optimisation and sustainable integration, with over 60 high-impact publications. He collaborates internationally, addressing challenges in decarbonisation across diverse transport sectors. Advising and grants include leadership on major funded initiatives, reflecting his role in advancing transport energy innovation. He leads research groups focused on decarbonisation strategies and energy-efficient systems.

Nagham Saeedمشاهده پروفایل

دانشیار

• Electrical and Electronic Engineering
• Industrial Internet of Things (IIoT)
• Artificial Intelligence in Engineering
• +۹ مورد دیگر

Dr. Nagham Saeed is an Associate Professor in Electrical and Electronic Engineering at the School of Computing and Engineering, University of West London, where she has been actively engaged in teaching and research since 2007. She holds a PhD in Intelligent MANET Optimisation from Brunel University and leads the Industrial Internet of Things (IIoT) research group. Her academic service includes editorial and technical committee roles for IEEE and MDPI, and she is a Chartered Engineer (CEng), Senior Member of IEEE, Member of IET, and Senior Fellow of the Higher Education Academy (HEA). PhD in Intelligent MANET Optimisation System, Brunel University (2011) Her research focuses on intelligent systems for smart cities, applying artificial intelligence to telecommunications, energy modeling, and industrial applications. She explores AI-driven optimization in next-generation networks, smart grid integration, battery management systems, and sustainable ICT. Her work also extends to engineering education, particularly feedforward teaching methods and student engagement. The recent publications reveal a strong trend in applying AI and machine learning to solve real-world challenges in energy systems, IoT, transportation, and environmental sustainability, often with a focus on smart cities and renewable integration. Dr. Saeed has been recognized with several awards, including: 2021 University of West London Student Union Best Supervisor/Tutor Award 2022 IEEE Region 8 Outstanding Women in Engineering Section Volunteer Award She mentors early-career engineers and academics and actively promotes electrical and electronic engineering among young girls. She has served as the 2023 IEEE Women in Engineering UK & Ireland Chair and is currently the Vice Chair (Chair-Elect) for the IEEE UK & Ireland Section (2024–2025). Her leadership spans technical innovation, academic service, and diversity advocacy in engineering. She teaches across a range of programs, including MSc Industrial Internet of Things, BEng and MSc Electrical and Electronic Engineering, and supervises PhD research in related fields.

Standa Živnýمشاهده پروفایل

استاد

• Theoretical Computer Science
• Discrete Mathematics
• Algorithms
• +۱۰ مورد دیگر

Standa Živný is a Professor of Computer Science at the University of Oxford and a Fellow and Tutor at Merton College. He has been a faculty member at Oxford since 2013 and was promoted to full professor in 2021. His research spans theoretical computer science and discrete mathematics, with a focus on algorithms, computational complexity, and constraint satisfaction problems (CSPs) in various forms, including optimisation, counting, and approximation. His research interests include the power and limitations of convex relaxations, sparsification, submodularity, and the algebraic and logical foundations of tractability in combinatorial problems. He has made significant contributions to understanding when and why certain problems can or cannot be efficiently solved using linear programming and other algorithmic paradigms. The recent trends in his publications show a deep engagement with approximation algorithms, hardness results, sparsification techniques, and the complexity of counting and promise problems. His work often lies at the intersection of algebra, logic, and optimisation, demonstrating the power of interdisciplinary approaches in theoretical computer science. ERC Consolidator Grant (NAASP, 2022–2027) ERC Starting Grant (PowAlgDO, 2017–2022) Royal Society University Research Fellowship (2013–2021) He actively supervises a large cohort of postdoctoral researchers and students, including PhD candidates, master’s, and undergraduate students. His leadership extends to academic service, where he serves as Editor-in-Chief of the SIAM Journal on Discrete Mathematics and holds editorial and committee positions in major journals and funding bodies. He has organised numerous workshops and research programmes at institutions such as Dagstuhl, the Isaac Newton Institute, and AIM. He is involved in major research initiatives, including a Simons Programme on symmetry in computation and an American Institute of Mathematics SQuARE on relaxations for promise CSPs.

• Sustainable Development
• Low-Carbon Technologies
• Energy and Building Technology
• +۱۳ مورد دیگر

Dr. Behrang Vand Alimohammadisagvand is a Lecturer at the School of Computing, Engineering and the Built Environment, Edinburgh Napier University. His research focuses on sustainable energy systems, building performance, and smart energy management, with strong international collaboration across Iran, China, Finland, and the UK. B.Sc. and M.Sc. in Mechanical and Energy Engineering Ph.D. in Energy and Building Technology His research interests include sustainable development, low-carbon technologies, energy policy, thermal comfort in buildings, and energy management systems at multiple scales. He actively investigates model predictive control (MPC), demand response, energy sharing in communities, and low-temperature heating networks. His work bridges theoretical modeling and practical implementation in real-world buildings. Dr. Vand's recent publications highlight trends in integrated energy management , smart grid optimization , and decarbonization of building heating systems . His articles emphasize mathematical modeling, simulation, and control strategies to improve energy efficiency and reduce carbon emissions in the built environment. He supervises doctoral students working on smart IoT systems and low-temperature heat networks. His research is supported by funders such as the Academy of Finland and Energy Technology Partnership. Active supervisor for PhD project on smart IoT systems with real-time deep learning (since 2022) Director of Studies for PhD on heating Scottish public buildings with low-temperature networks (2018–2024) He is affiliated with the Institute for Sustainable Construction and contributes to the research theme Culture and Communities . His work aligns with global efforts toward net-zero emissions and sustainable urban development.

Evangelos Boulougourisمشاهده پروفایل

استاد

• Naval Architecture
• Marine Engineering
• Ocean Engineering
• +۱۹ مورد دیگر

Professor Evangelos Boulougouris is Head of the Department of Naval Architecture, Ocean and Marine Engineering at the University of Strathclyde, where he also serves as Chair of the Maritime Safety Research Centre. He is a chartered professional engineer with over 28 years of internationally recognized research in maritime safety, design for safety, and holistic ship design. His work spans damage stability, autonomous vessels, alternative fuels, and ship survivability, with strong impact on international regulations through roles in IMO, ITTC, SNAME, and RINA. Research Interests: His primary research focuses on safety of marine operations, including damage and intact stability in waves, collision avoidance, ship evacuation, crashworthiness, and the integration of alternative fuels like ammonia and hydrogen. He leads cutting-edge work in multi-objective ship design optimization, risk modeling, and decarbonization strategies for advanced marine vehicles. The recent 15 publications highlight a strong trend toward digitalization and sustainability in shipping, combining machine learning for propeller optimization, CFD simulations for catamaran performance, real-time decision support in emergencies, and hybrid propulsion systems for zero-emission vessels. His work increasingly emphasizes climate resilience, port risk under extreme weather, and energy management in CTVs, aligning with global SDGs. Scientific Awards: 2020 Denny Medal SNAME ABS Captain Joseph H. Linnard Prize (2023) Safety 2020 Best Paper Award (2022) Honorable Mention for Vice Admiral E. L. Cochrane Award (2022) EU CHAMPIONS of Transport Research (HOLISHIP, TRA 2014) Greek Technical Innovation Award, Lloyd’s List (2009) 1st Prize, International SAFER SHIP Competition (1999) Advising and Grants: He actively supervises PhD students and has led numerous EU and UK-funded projects such as SEASTARS, SAFARI, EcoShipYard, and Digital Shipwright. As Principal Investigator and Co-I, he secures substantial research funding, coordinates knowledge exchange (KE) initiatives, and leads training programs across Europe. Labs and Teams: He leads the Maritime Safety Research Centre at Strathclyde, fostering interdisciplinary collaboration on ship safety, stability, and sustainable design. His team works closely with industry partners RCG and DNV, and engages in international networks through STAB, ITTC, and IMO committees.

Lisa Baiمشاهده پروفایل

پژوهشگر ارشد

• Resource recovery from waste and wastewater
• Bioenergy production
• Biodegradable plastics (PHA)
• +۷ مورد دیگر

Dr. Lisa Bai is a Research Fellow at the Australian Centre for Water and Environmental Biotechnology (ACWEB) within the School of Chemical Engineering at the University of Queensland. She also maintains affiliations with the ARC Training Centre for Bioplastics and Biocomposites. Her research focuses on sustainable waste and wastewater management with expertise in resource recovery technologies and bioenergy production from organic waste streams. Dr. Bai earned her PhD from the University of Queensland and has a background in Bioengineering and Environmental Engineering. Prior to her academic career, she spent four years working at an environmental consultancy in North Queensland, where she specialized in aquaculture water bioremediation using macroalgae technologies and waste stream utilization for biomass production. Her research program spans four interconnected themes: 1) Data-Based Waste Identification and Characterisation for both core and non-core organic wastes; 2) Tailored Organic Waste and Wastewater Treatment Technology focusing on anaerobic digestion and nutrient recovery; 3) Biotechnology Assisted Process Optimisation for co-digestion modeling; and 4) Biotechnology Based Process Enhancement investigating microbial ecology mechanisms. Her work bridges molecular biology with engineering applications for practical waste management solutions. Analysis of her publication record reveals a consistent research trajectory in anaerobic digestion technologies and resource recovery, with recent work (2023-2025) focusing on enhancing digestion of challenging waste streams like paunch waste from meat processing. Her research demonstrates progression from fundamental laboratory studies to pilot-scale implementation with industry partners. Dr. Bai is actively involved in research funding, currently leading the 'Pilot-scale Validation of Anaerobic Co-digestion at Large Municipal STP' project (2024-2025) funded by Urban Utilities. Previously, she contributed to the 'Waste-to-Energy' project (2020-2024) under the Fight Food Waste CRC program. She serves as an Associate Advisor for PhD students working on biotechnologies for PHA production. Her research team collaborates closely with industry partners including Central SEQ Distributor-Retailer Authority and Red-Meat-Processing facilities to translate laboratory findings into commercial applications for sustainable waste management, demonstrating strong industry engagement and practical implementation focus.

• Renewable Energy
• Solar Thermal Energy
• Energy Storage
• +۹ مورد دیگر

Dr Leok Lee is a Lecturer in the School of Electrical and Mechanical Engineering at the University of Adelaide . He is also an active member of the Centre for Energy Technology , contributing to cutting-edge research in renewable energy systems. Research Interests: Renewable energy systems, with a focus on solar thermal energy and energy storage. System integration and optimisation of complex transient energy systems. Computational fluid dynamics (CFD) and experimental design for energy applications. Decarbonisation of heavy industry through clean energy technologies. His research spans from fundamental studies in heat transfer and fluid mechanics to applied engineering solutions for decarbonising industrial processes. He has led and contributed to projects funded by ARENA and HILT CRC, targeting the integration of concentrated solar thermal energy into industrial applications such as the Bayer Alumina process. Supervision & Mentorship: Dr Lee is eligible to supervise Masters and PhD students and actively mentors undergraduate, Masters, and PhD candidates. He encourages prospective students to contact him via email to discuss research opportunities. Contact: Email: leok.lee@adelaide.edu.au Location: Room 3, Engineering South, North Terrace Campus

Katherine Fishمشاهده پروفایل

پژوهشگر ارشد

• Applied environmental microbiology
• Biofilm formation and mobilisation/stability
• Biofilm management
• +۶ مورد دیگر

Dr. Katherine Fish is a Research Fellow in Water Systems Microbiology at the School of Mechanical, Aerospace and Civil Engineering, University of Sheffield. She holds a PhD in Civil and Structural Engineering (2013) and an MSc in Biological Science (2009) from the same institution. PhD: The impact of hydraulic regime upon biofilms in drinking water distribution systems , University of Sheffield. MSc: First-Class Honours in Biological Science, Department of Animal and Plant Sciences, University of Sheffield. Her research focuses on applied environmental microbiology, particularly the microbial ecology of natural and engineered environments. Key areas include: Biofilm formation, mobilisation, and stability in drinking water systems Interdisciplinary approaches to biofilm management and water quality Microbial community responses to disinfection practices Impacts of hydraulic regimes and chemical treatments on biofilms Public health implications of biofilm dynamics She collaborates with industry partners such as AkzoNobel, Dŵr Cymru Welsh Water, and South Staffs Water on projects like Managing Aquatic Biofilms via Surface Manipulation (funded by NBIC, BBSRC) and Biomonitoring . Her work also contributes to EPSRC-funded initiatives including TWENTY65, Sheffield Water Centre, PODDS, Pipe Dreams, and Pennine Water Group. Her publications span topics like Pseudomonas aeruginosa interactions in biofilms, disinfection residual behaviour, microplastic contamination in aquatic systems, and climate change impacts on water infrastructure. These studies integrate biological, chemical, and physical analyses to enhance water system management. Contact: k.fish@sheffield.ac.uk | ORCID | LinkedIn

• Functional Analysis
• Artificial Intelligence
• Foundations of Computational Mathematics
• +۷ مورد دیگر

Anders C. Hansen is Professor of Mathematics at the University of Cambridge (Faculty of Mathematics, Department of Applied Mathematics and Theoretical Physics) and Professor II at the University of Oslo. He leads the Applied Functional and Harmonic Analysis group and holds a Royal Society University Research Fellowship. His research bridges pure mathematics and cutting-edge applications in AI, computational harmonic analysis, inverse problems, and compressed sensing. Education: PhD from the University of Cambridge, MA from UC Berkeley, and BA from the Norwegian University of Science and Technology. Research Interests: Hansen's work centers on foundational challenges in computational mathematics, including the Solvability Complexity Index hierarchy for classifying computational problems, instability phenomena in deep learning, and theoretical advances in compressed sensing. His group develops rigorous frameworks for high-dimensional data analysis, medical imaging, and AI safety, often exposing paradoxes in algorithmic reliability. Publication Trends: Recent articles focus on the limits of deep learning (e.g., Smale's 18th problem, instability in image reconstruction), mathematical foundations of AI (trustworthiness, feature selection, LLMs), and advanced compressed sensing (asymptotic incoherence, spectral computations). His work consistently intersects functional analysis with computational feasibility. Awards: PROSE Award Finalist (2022) Whitehead Prize (2019) IMA Prize in Mathematics and Applications (2018) Leverhulme Prize (2017) Royal Society University Research Fellow (2012) Advising & Leadership: Hansen has supervised 17 PhD students and 8 postdocs. He leads the Applied Functional and Harmonic Analysis group, coordinating interdisciplinary projects in mathematical data science. His editorial roles include SIAM Journal on Imaging Sciences and Proceedings of the Royal Society A .