جستجوی استاد راهنمای دانشگاهی

Morten Hviidمشاهده پروفایل

استاد

• Competition Law
• Industrial Economics
• Tort Law
• +۲ مورد دیگر

Morten Hviid is a Professor of Law at the University of East Anglia (UEA) School of Law, specializing in competition law, tort law, contract law, and the economic analysis of legal systems. He joined UEA in 2004 after holding economics positions at the University of Copenhagen, University of Warwick, and UEA's School of Economic and Social Studies. A founding member and former Director (2011-2018) of the Centre for Competition Policy, he contributes to the Centre for Business Research at Cambridge University, UK Intellectual Property Office advisory groups, and Ofgem's academic panel. Biography: Holds MA and PhD in Economics from Warwick, economic degree from Aarhus University, and has been a visiting scholar at Yale, UC Berkeley, University of Michigan, and Copenhagen. Editorial Roles: Former editor of the Journal of Industrial Economics and associate editor of the International Journal of Industrial Organization. Former EARIE Executive Committee member. Research Focus: Applies economic principles and game theory to competition law, tort, and contract law. Current projects examine policy arguments in tort cases, non-compensatory damages in contract law, collusive practices, and digitalization impacts in creative industries. Funded by Danish Social Science Research Council, ESRC, AHRC, Ofcom, Ofgem, and OECD. Publications: Appear in journals like Economic Journal, European Competition Journal, Journal of Law and Economics, and Oxford Journal of Legal Studies. Recurring themes include competition policy implementation, pricing dynamics, and algorithmic market impacts. Teaching: Leads undergraduate LLB modules on Tort and The Economic Approach to Law. Previously taught UK Competition Law, Regulation of Network Industries, and research seminars. Extensive experience supervising over 35 doctoral students. External Collaborations: Engaged in consultancy projects with Anglian Water, Korean Government Fellowship, and policy responses for UK regulatory bodies like CMA, Financial Conduct Authority, and BEIS.

Olatunji Adekoyaمشاهده پروفایل

مدرس ارشد

• Human Resource Management
• Organisational Behaviour
• Work-Life Balance
• +۷ مورد دیگر

Dr Olatunji Adekoya is a Senior Lecturer and Course Leader for the MSc Human Resources and Organisational Development at Sheffield Business School, part of Sheffield Hallam University. He holds multiple academic credentials including a PhD in Management (University of East London), an MBA (University of Wales Trinity Saint David), a Harvard Business School Diploma in Business Analytics, and a Bachelors in Economics (University of Lagos, Nigeria). His research focuses on global south workplace dynamics, particularly in work-life balance, employee wellbeing, green HRM, gender issues, and gig economy challenges. He has published extensively in journals like the British Journal of Management and Gender, Work & Organisation, co-edited books on African career studies and international HRM, and serves as an external examiner for UK and international universities. His academic leadership includes mentoring doctoral researchers and advancing inclusive teaching practices as a Senior Fellow of Advance HE and Certified Management and Business Educator. He actively consults on organisational resilience and diversity initiatives, leading projects that bridge academic research with practical business solutions. His work often critiques cultural and institutional barriers in workplaces, advocating for equitable policies and sustainable HRM practices. Dr Adekoya’s research awards include recognition for his contributions to teaching excellence (SFHEA) and HRM education (CMBE). His research explores intersections between technology, environment, and labour, with a focus on Nigeria, the UK, and other Global South nations. His current projects address AI’s impact on gig economies, digital HRM adoption challenges, and gender equity in entrepreneurial ecosystems.

Oshani Seneviratneمشاهده پروفایل

استادیار

• Decentralized Systems
• Blockchain Technology
• Health Informatics
• +۵ مورد دیگر

Oshani Seneviratne is an Assistant Professor of Computer Science at Rensselaer Polytechnic Institute (RPI), leading the BRAINS Lab. She holds a Ph.D. and S.M. from MIT (Computer Science) and a B.Sc. (Hons) from the University of Moratuwa, Sri Lanka. Her research focuses on decentralized systems, blockchain, health informatics, and federated learning. She previously directed RPI's Health Data Research division. Education Ph.D. in Computer Science, MIT S.M. in Computer Science, MIT B.Sc. (Hons) in Computer Science and Engineering, University of Moratuwa Research Interests Her work bridges decentralized technologies with clinical and financial applications. Key areas include blockchain-based frameworks for federated learning, explainable AI in healthcare, and semantic web technologies for data interoperability. She emphasizes ethical AI, data provenance, and scalable systems for real-world challenges. Recent Work Trends Recent publications highlight advancements in smart contract auditing, LLM applications in financial systems, and blockchain-enhanced data provenance. Her work often combines technical innovation with societal impact, such as improving health data sharing and combating misinformation. Awards & Grants No awards explicitly listed, but her research has been supported by grants related to blockchain, health informatics, and decentralized systems. Advising & Labs Leads the BRAINS Lab, focusing on resilient, intelligent networked systems. Collaborates on projects like the Punya platform for clinical apps and BlockIoT for health data integration. Future Work Expanding into AI explainability for clinical decision support, decentralized mental health monitoring, and blockchain interoperability solutions.

• Network Optimization
• Infrastructure Resilience
• Supply Chain Risk
• +۳ مورد دیگر

Nafiseh Ghorbani-Renani is a Teaching Professor in the Department of Systems and Enterprises at Stevens Institute of Technology. Her research develops mathematical frameworks for managing risk in interconnected systems such as critical infrastructure, supply chains, and energy networks. Education includes: PhD in Industrial and Systems Engineering (University of Oklahoma) MS in Industrial Engineering (University Technology Malaysia) BS in Industrial Engineering (Yazd University) Research integrates optimization techniques with machine learning for resilience planning in interdependent networks. Current projects examine microgrid energy trading, supply chain disruption management, and infrastructure restoration scheduling. Recent publications focus on tri-level optimization models for critical infrastructure protection, energy equity in community microgrids, and machine learning applications for network resilience. Articles demonstrate consistent advancement in modeling complex interdependencies across infrastructure systems. As Faculty Advisor for the Software Division, she guides student projects bridging theoretical models with practical implementation. Course instruction spans software engineering fundamentals, agile methodologies, and systems development lifecycle management.

Konstantinos Skindiliasمشاهده پروفایل

مدرس ارشد

• Quantitative Finance
• Financial Engineering
• Risk Management
• +۶ مورد دیگر

Konstantinos Skindilias holds the position of Senior Lecturer in Data Science at the University of Greenwich's School of Computing and Mathematical Sciences, within the Faculty of Engineering and Science. Concurrently, he serves as a Director in a Big-4 firm advising investment banks, bridging academic and industry expertise. His qualifications include a BSc, MSc, and PhD in relevant fields. His research focuses on quantitative finance, stochastic modeling, derivatives pricing, and risk management. Key areas include market risk methodologies, volatility calibration, and energy commodity analysis. He specializes in developing models for contingent claims pricing, portfolio insurance strategies, and regulatory frameworks like SIMM. Publications emphasize advanced numerical techniques such as Markov chain approximations for derivatives pricing and volatility forecasting. His work addresses practical challenges in turbulent markets and energy security, with contributions to both theoretical and applied finance domains. No scientific awards or grants are explicitly listed in the provided information. His dual role in academia and financial services highlights his interdisciplinary engagement, though specific lab affiliations or teams are not detailed here.

Paschalis Antonisمشاهده پروفایل

استاد

• Computer Engineering
• Digital Signal Processing
• Space Systems
• +۵ مورد دیگر

Paschalis Antonis is a Professor at the Department of Informatics and Telecommunications, National and Kapodistrian University of Athens. His research focuses on hardware architectures for space systems, embedded systems, and image compression standards such as CCSDS. He specializes in FPGA implementations, radiation-hardened electronics, and biomarker development for immunogenic responses to cancer therapies. Research Interests: High-performance FPGA-based hardware accelerators Space-grade embedded systems and data compression CCSDS standard implementations for aerospace applications Molecular biomarkers for immunotherapy response prediction Recent Trends: His work emphasizes resilient systems against radiation effects (e.g., SEUs in FPGAs), high-throughput image compression cores for space missions, and interdisciplinary research linking computational hardware with medical diagnostics via prothymosin α analysis. Grants & Labs: Leads the ASPIICS coronagraph project for ESA's Proba-3 mission, involving advanced optical instrumentation and formation flying systems. Collaborates on COTS FPGA utilization in extreme environments.

José E. Figueroa-Lópezمشاهده پروفایل

استاد

• Statistics
• Mathematical Finance
• Probability Theory
• +۳ مورد دیگر

José E. Figueroa-López is a Professor of Statistics and Data Science at Washington University in St. Louis , serving as Associate Chair of the department and Director of Graduate Studies. He holds a PhD from the Georgia Institute of Technology . His research focuses on Statistics, Mathematical Finance, and Probability , including high-frequency data inference, nonparametric methods, stochastic processes, and algorithmic trading. His work is funded by multiple NSF grants, such as 'Systemic Shock Inference for High-Frequency Data' (DMS-2413557, 2024–2027). Notable awards include the Guido L. Weiss Teaching Award (2020) and Purdue University Faculty Scholar (2014) . He has led NSF-funded projects on nonparametric methods, Levy models, and portfolio optimization since 2009. His academic leadership includes overseeing graduate programs and advancing research in stochastic control and financial mathematics.

• Structural Engineering
• Energy Efficiency in Buildings
• Sustainable Architecture
• +۳ مورد دیگر

Juliana Felkner is an academic affiliated with ETH Zurich, primarily associated with the Department of Architecture within the School of Architecture, Civil and Environmental Engineering. Her research focuses on integrating structural efficiency with energy performance in tall buildings, emphasizing multi-objective optimization and sustainable design principles. Key contributions include studies on embodied vs. operational energy in buildings, structural design frameworks balancing sustainability and efficiency, and interactive optimization techniques using NURBS curves and Particle Swarm Optimization (PSO). Her doctoral thesis (2016) explored multi-objective design strategies addressing structural, environmental, and architectural considerations. Felkner has published extensively on topics such as energy lifecycle analysis, natural ventilation potentials, and computational design methods. Her work highlights the importance of reducing operational energy in existing building stocks to mitigate greenhouse gas emissions. Awards and grants are not explicitly mentioned in the provided texts, but her peer-reviewed publications indicate active engagement in academic research and collaboration across disciplines.

Hanqing Jinمشاهده پروفایل

دانشیار

• Mathematical Finance
• Stochastic Analysis
• Portfolio Optimization
• +۳ مورد دیگر

Dr. Hanqing Jin is an Associate Professor in the Mathematical Institute at the University of Oxford, specializing in Mathematical Finance and Applied Stochastic Analysis. His research focuses on investor decision-making under non-utility behavior, dynamic portfolio optimization, and stochastic control problems in financial markets. Prior to Oxford, he held an Assistant Professorship at the National University of Singapore. He has contributed to foundational work on mean-variance portfolio selection, behavioral finance, and the application of stochastic processes to financial modeling. His academic background includes extensive work on continuous-time portfolio optimization, risk management frameworks, and the intersection of behavioral economics with quantitative finance. Notable contributions include studies on optimal lockdown policies during pandemics, blockchain consensus algorithms analysis, and the development of novel biomarker detection techniques using Raman spectroscopy. Dr. Jin's research integrates advanced mathematical techniques with real-world financial challenges, bridging theoretical models with practical applications in areas such as robo-advising systems and cryptocurrency frameworks. His work on transaction cost analysis and dynamic mean-variance strategies has been widely cited in both academic and industry contexts.

Hangfeng Heمشاهده پروفایل

استادیار

• Machine Learning
• Natural Language Processing
• Reasoning
• +۴ مورد دیگر

Hangfeng He is an Assistant Professor of Computer Science and Data Science at the University of Rochester , affiliated with the Hajim School of Engineering & Applied Sciences. He holds a PhD from the University of Pennsylvania and focuses on machine learning and natural language processing. His research emphasizes incidental supervision for natural language understanding, interpretability of deep neural networks, and reasoning in natural language. Education : PhD in Computer Science from University of Pennsylvania Research Interests : Machine Learning (especially deep learning theory, generalization, and optimization) Natural Language Processing (incidental supervision, language understanding, and multimodal reasoning) Reasoning (inductive biases, temporal data analysis, and model interpretability) Research Trends : His work spans foundational AI research and applied NLP, with recent focus on large language models, multimodal systems, and constraint-aware methods. He explores how models generalize from limited supervision and mitigate biases in real-world data. Key themes include improving model robustness, understanding inductive mechanisms, and applying AI to financial and social text analysis. Labs/Teams : While specific lab affiliations aren’t listed, his work aligns with the Department of Computer Science’s research clusters in AI, machine learning, and data science.

Micael Derelövمشاهده پروفایل

دانشیار

• Industrial Engineering
• Product Development
• Reliability Engineering
• +۵ مورد دیگر

Micael Derelöv is an Associate Professor at Linköping University's Department of Management and Engineering (IEI), specializing in Product Realisation (PROD). His work focuses on optimizing safety, reliability, and efficiency in industrial and aerospace systems. He contributes to sustainable product development through advanced methodologies in design optimization and failure analysis. His research integrates robotics, manufacturing systems, and systems engineering to address challenges in collaborative assembly, aircraft design, and risk management. Dr. Derelöv’s research interests include multi-objective optimization for balancing safety and weight in aircraft systems, industrial safety demonstrators, and reliability-centric design processes. He has developed frameworks for evaluating design concepts and identifying potential failures in early-stage engineering projects. His work also explores the application of genetic algorithms in concept synthesis and the use of qualitative modeling for risk assessment. His publications highlight trends in industrial safety, systems reliability, and aerospace engineering. Recent work includes advancements in safe collaborative robotics on assembly lines and methodologies for industrial safety demonstrators. Earlier contributions address cost optimization in reliability-focused design and bio-mechatronic product development. While no specific scientific awards are listed, his active research and academic role reflect a commitment to advancing engineering practices. He collaborates on student projects, such as a recent initiative designing a pressure-resistant device for space exploration, demonstrating engagement in applied and interdisciplinary research. Micael Derelöv’s affiliation with the Department of Management and Engineering positions him at the intersection of academic research and industrial innovation, particularly within the Product Realisation group. His work emphasizes sustainable, integrated approaches to product development, blending theoretical insights with practical applications in manufacturing and aerospace sectors.

Natasha Fernandesمشاهده پروفایل

مدرس ارشد

• Data Privacy
• Differential Privacy
• Privacy-Preserving Machine Learning
• +۳ مورد دیگر

Natasha Fernandes is a Senior Lecturer in the School of Computing at Macquarie University. She holds a PhD in Computing from Macquarie University and École Polytechnique (France), and an undergraduate degree in Pure Mathematics and Computer Science from the University of Sydney. Her roles include involvement in the Data Horizons Research Centre and Future Communications Research Centre, alongside professional casual appointments in academic computing. Her research focuses on the mathematical foundations of data privacy, particularly differential privacy and its applications in natural language processing and machine learning. She develops privacy-preserving systems and tools using quantitative information flow techniques rooted in information theory. Key areas include privacy analyses for financial systems (e.g., Open Banking), API privacy, and optimizing utility in privacy pipelines. Fernandes has led or contributed to five research projects, including work on privacy analyses for financial transaction protocols and UAV-based machine learning systems. She received the 2021 John Makpeace Bennett Award for her doctoral research on differential privacy in metric spaces. Her academic journey combines industry experience as a backend software engineer with rigorous academic contributions, spanning over 21 peer-reviewed publications and collaborations across cybersecurity and privacy engineering domains.

• Ecohydrology
• Water Quality Management
• Environmental Impact Assessment
• +۶ مورد دیگر

Dr. Pouyan Nejadhashemi is an MSU Research Foundation Professor in the Departments of Plant, Soil and Microbial Sciences and Biosystems & Agricultural Engineering at Michigan State University. He serves as Director of the MSU Institute of Water Research and the Center for Intelligent Water Resources Engineering. His expertise spans ecohydrology, climate change adaptation, environmental impact assessment, and decision support systems for ecosystem sustainability. He holds a Ph.D. in Biological Resources Engineering from the University of Maryland. Dr. Nejadhashemi's research focuses on water quality modeling, non-point source pollution prevention, and integrating machine learning with hydrological systems. Key areas include irrigation optimization, PFAS contamination monitoring, and watershed management. He teaches courses on water resources systems analysis and ecohydrology. Awards: MSU Research Foundation Professor Title Grants: FAA grant for PFAS remediation, grants for developing agricultural innovations in Senegal and Bangladesh Labs/Teams: MSU Institute of Water Research, Center for Intelligent Water Resources Engineering His work bridges computational methods with environmental challenges, addressing global water security, food systems, and sustainable resource management. Recent projects include modeling water quality in the Chesapeake Bay and developing AI tools for agricultural extension platforms.

Marc Paolellaمشاهده پروفایل

استاد

• Financial Econometrics
• Time Series Analysis
• Portfolio Optimization
• +۴ مورد دیگر

Marc Paolella is a Full Professor of Empirical Finance at the University of Zurich's Department of Finance. His academic journey includes roles as Associate Professor (2003–2006) and Assistant Professor (1999–2003) at Kiel University and visiting positions at the University of Geneva. He holds a Dr. sc. pol. (1998) and Habilitation (2002) from Kiel University, alongside degrees from SUNY Stony Brook and Colorado State University. His research focuses on financial econometrics, emphasizing portfolio optimization, risk prediction, and saddlepoint approximation theory. He has authored four textbooks, including works on probability theory, statistical inference, and GARCH models. Over 50 journal articles span leading venues like the Journal of Econometrics and Journal of Financial Econometrics. Paolella's contributions include developing methods like CHICAGO for portfolio risk calculation and the COMFORT model for non-Gaussian returns. He serves as Editor-in-Chief of the journal Econometrics and holds editorial roles at multiple journals. Awards include the Elected Fellowship at the IETI and recognition for impactful research. His teaching spans advanced courses in financial econometrics, probability theory, and mathematical finance. He has supervised numerous theses and leads the Quantitative Finance program at the Science ETH UZH. Research grants include Swiss National Science Foundation funding for portfolio optimization under non-elliptical distributions.

Nadine Straußمشاهده پروفایل

استادیار

• Sustainability Communication
• Strategic Communication
• Financial Communication
• +۵ مورد دیگر

Nadine Strauß is an Assistant Professor (Tenure Track) of Strategic Communication and Media Management at the University of Zurich's Department of Communication and Media Research (IKMZ). She holds a Ph.D. from the Amsterdam School of Communication Research (ASCoR) and has held research positions at the University of Oxford and the University of Vienna. Her research focuses on sustainability communication, financial journalism, and the role of media in sustainable finance and corporate strategy. Education: Ph.D. in Communication Science (2017), University of Amsterdam Research Master’s in Communication Science (cum laude, 2014), University of Amsterdam BA in Media and Communication Studies (2012), University of Mannheim Research Interests: Sustainability communication, financial communication, business journalism, media management, and digital news consumption patterns. She explores how media shapes public discourse on sustainable finance, corporate responsibility, and climate change. Awards & Roles: Member of editorial boards for Environmental Communication and International Journal of Strategic Communication , and board member of NGOs like ProClim and Finance Watch. Her work bridges academia and practice, emphasizing ethical journalism and strategic communication for societal challenges. Grants & Labs: Marie Sklodowska-Curie Fellowship (2019–2021), co-founder of the "Sustainability" community at the Digital Society Initiative (University of Zurich), and collaborator with institutions like the Smith School of Enterprise and Environment (Oxford).