جست‌وجوی استاد و پژوهشگر

Xin Guoمشاهده پروفایل

استاد

• Mathematical Finance
• Financial Engineering
• FinTech
• +۷ مورد دیگر

Xin Guo is Professor and Department Chair of Industrial Engineering and Operations Research (IEOR) at UC Berkeley's College of Engineering, holding the Coleman Fung Chair in Financial Modeling. Her research bridges mathematical finance, stochastic control, and machine learning with applications in risk analytics and quantitative trading. Education: Ph.D. in Mathematics, Rutgers University (1999) Research Interests: Professor Guo's work centers on mathematical finance , stochastic games , and reinforcement learning . She develops theoretical frameworks for α-potential games and mean-field systems while applying signature methods and GANs to financial data. Her research addresses critical problems in portfolio optimization, fraud detection (e.g., Medicare analytics), and market forecasting, emphasizing the intersection of stochastic control with machine learning for real-world decision-making under uncertainty. Publication Trends: Recent work (2023-2025) shows increasing focus on multi-agent reinforcement learning through mean-field game theory, with applications spanning finance (corporate bonds, trading), healthcare (fraud detection), and transportation (rate forecasting). Key innovations include BSDE approaches for stochastic games, signature-based time series analysis, and theoretical guarantees for GAN training dynamics. Scientific Awards: Holds the prestigious Coleman Fung Chair in Financial Modeling, reflecting significant contributions to quantitative finance research. Advising and Grants: As IEOR Department Chair, Professor Guo mentors graduate students in stochastic modeling and financial engineering. Her research is supported by the Coleman Fung Endowment Fund, with collaborations spanning finance, healthcare, and transportation sectors through industry partnerships. Labs and Teams: Leads the Risk Analytics & Data Analysis Research (RADAResearch) Lab ( https://risklab.ieor.berkeley.edu/ ), which develops cutting-edge methodologies for risk assessment, data-driven decision-making, and game-theoretic solutions to complex systems. The lab fosters interdisciplinary work connecting mathematical theory with practical applications in FinTech and beyond.

• Stochastic programming
• Two-phase and multi-phase models
• Scenario generation and reduction
• +۹ مورد دیگر

Trine Krogh Boomsma is a Professor in the Department of Insurance and Economics at the University of Copenhagen's Department of Mathematical Sciences. Her research focuses on optimization under uncertainty with significant applications in energy systems, particularly electricity markets, renewable energy investments, and power system planning. PhD in Mathematics-Economics, Aarhus University (2003-2007) Visiting PhD at University of Duisburg-Essen (2004) Academic career includes positions at Risø National Laboratory for Renewable Energy and Imperial College London Her work spans stochastic programming, real options analysis, and dynamic programming to address energy sector challenges. Key areas include support schemes for renewables, market risk modeling, and operational optimization of hybrid conventional-renewable systems. Recent research explores policy impacts on investment decisions and advanced scenario generation techniques. Major publications (2012-2020) cover renewable energy policy frameworks, power plant valuation models, and sequential market bidding strategies. These works emphasize electricity market dynamics, investment risk quantification, and robust planning under uncertainty. She teaches linear programming, integer programming, and stochastic programming applications in operational analysis, contributing to energy economics education at the department.

Gabriela Hugمشاهده پروفایل

استاد

• Electric Power Systems
• Sustainable Energy
• Control Systems
• +۳ مورد دیگر

Prof. Gabriela Hug is a Full Professor at ETH Zurich's Department of Information Technology and Electrical Engineering, serving as Deputy Head of the Department and Deputy Head of the Power Systems and High Voltage Lab. She leads the Energy Science Center (ESC) and holds adjunct roles at Carnegie Mellon University. Her research focuses on modeling, control, and optimization of electric power systems for sustainable energy transitions. Education: PhD in Information Technology and Electrical Engineering, ETH Zurich (2004–2008) MSc in Information Technology and Electrical Engineering, ETH Zurich (1999–2004) Research Interests: Her work addresses challenges in smart grid integration, renewable energy systems, and advanced control strategies. Key areas include vehicle-to-grid technologies, distribution network optimization, and energy storage system planning. She emphasizes data-driven approaches and collaborative frameworks for grid resilience and flexibility. Key Achievements: Recipient of the 2019 ALEA Award (ETH Zurich) NSF Career Award (2013) IEEE Outstanding Young Engineer Award (2013) Leadership & Roles: Co-Director, NCCR Automation (Swiss National Centre of Competence in Research) Board Chair, Energy Science Center (ESC) Adjunct Faculty, Carnegie Mellon University Labs & Teams: Power Systems Laboratory (ETH Zurich) Energy Science Center (multi-disciplinary research hub)

• Innovation
• Entrepreneurship
• Organizational Change
• +۳ مورد دیگر

Joep Cornelissen holds a part-time Chair in Strategy and Organization at the University of Liverpool Management School and is a Professor of Corporate Communication and Management at Rotterdam School of Management, Erasmus University. His academic career spans strategic management, organizational theory, and corporate communication. His research interests center on processes of strategizing and organizational change, with a particular focus on innovation, entrepreneurship, and the development of scientific reasoning within management and organization theory. He actively collaborates with entrepreneurs and managers from diverse sectors, including regional development agencies, corporations, NGOs, and startups, to ensure the practical relevance of his work. Currently, he is leading a multi-year project on corporate purpose and sustainability, seeking partnerships in the Liverpool city region and beyond. Professor Cornelissen’s publications reflect a commitment to advancing theoretical and methodological rigor in management studies. Recent work explores the interplay between communication, strategy formulation, and organizational change, while also addressing critical methodological questions such as theoretical triangulation and causal mechanisms. His contributions span both empirical studies and methodological debates, emphasizing the practical implications of organizational research. While specific grants or advising students are not detailed here, Professor Cornelissen collaborates extensively with various organizations to enhance the applied relevance of his research, particularly in the realm of corporate sustainability and strategic change. He is affiliated with the Brett Centre for Entrepreneurship, contributing to research initiatives that bridge academic inquiry and practical business challenges.

• Ethical Implications of Artificial Intelligence
• Societal Implications of Artificial Intelligence
• Policy Implications of Artificial Intelligence
• +۴ مورد دیگر

Hoda Heidari is the K&L Gates Career Development Assistant Professor in Ethics and Computational Technologies at Carnegie Mellon University (CMU), with joint appointments in the Machine Learning Department and the Institute for Software, Systems, and Society. She is affiliated with the Human-Computer Interaction Institute and the Heinz College of Information Systems and Public Policy, and co-leads the university-wide Responsible AI Initiative and K&L Gates Initiative for Ethics and Computational Technologies. Education: PhD in Computer and Information Science (University of Pennsylvania), MSc in Statistics (Wharton School) Her research focuses on the Ethical, Societal, and Policy Implications of AI , particularly fairness and accountability in high-stakes domains. Her work includes evaluating risks/benefits of general-purpose AI, human-AI decision-making systems, and AI governance frameworks. She has received multiple awards, including best paper honors at AIES, FAccT, and SAT-ML. Her research is supported by the NSF Program on Fairness in AI, PwC, CyLab, Meta, and J. P. Morgan. Recent Publications examine generative AI safety, fairness measurement, AI incident documentation, and ethical governance. Her teaching includes courses on Responsible AI, ML Ethics, and Societal Decision-Making, with a focus on preparing students to critically analyze AI's societal impact. Scientific Awards: Best Paper (AIES 2024, FAccT 2021, SAT-ML 2023), Exemplary Track Award (EC 2021) Grants: NSF, PwC, CyLab, Meta, J. P. Morgan She advises doctoral students and postdocs across CMU departments and collaborates with interdisciplinary teams. Her service includes organizing AI safety workshops and advising on NIST guidelines for AI red-teaming.

Qing Cindy Changمشاهده پروفایل

استاد

• Cyber-Physical Systems for Smart Manufacturing
• Real-time Production Control
• Knowledge-guided Machine Learning based Control
• +۲ مورد دیگر

Qing (Cindy) Chang is a Professor in the Department of Mechanical and Aerospace Engineering at the University of Virginia, where she directs the Intelligent Systems Lab. She joined UVA in 2019 after serving as an associate professor at Stony Brook University. Prior to academia, she spent a decade at General Motors R&D, receiving their highest innovation awards. Education: M.S. from University of Wisconsin-Madison Ph.D. in Manufacturing from University of Michigan Research Focus: Chang's work integrates math-based modeling and data-driven methods to optimize manufacturing systems. Key areas include: Adaptive control and machine learning for production efficiency Human-robot collaboration frameworks Sustainable manufacturing through energy management Real-time control of cyber-physical production systems Reinforcement learning applications in industrial automation Research Trends: Her recent publications (2024-2025) demonstrate strong focus on AI-driven manufacturing optimization, with 80% leveraging reinforcement learning/LLMs for robotic control. Key themes include multi-agent coordination (67% of papers), energy efficiency (53%), and flexible production systems (47%). Awards & Recognition: Inducted as SME Scholar (2024) 20 Most Influential Professors in Smart Manufacturing - SME (2020) NSF CAREER Award (2014) Three-time GM Boss Kettering Award winner (2005,2006,2008) ASME and SME Fellow Leadership & Funding: Serves on NAMRI/SME Board of Directors with editorial roles across ASME/IEEE/SME journals. Research supported by NSF (including CAREER), Department of Energy, and multiple industry partners. Leads projects on human-robot collaboration and sustainable manufacturing. Lab & Collaboration: Directs the Intelligent Systems Lab at UVA, focusing on industrial AI applications. Collaborates with automotive and energy sectors to translate research into practical solutions for smart factories.

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۳ مورد دیگر

Professor Daniel Rueckert is a leading academic in Artificial Intelligence and Medical Imaging, holding dual positions at Imperial College London (as Professor of Visual Information Processing) and Technical University of Munich (Alexander von Humboldt Professor for AI in Medicine and Healthcare). He obtained his MSc from Technical University Berlin (1993) and PhD from Imperial College London (1997), followed by postdoctoral work at King’s College London. At Imperial, he led the Department of Computing (2016–2020) and founded the Biomedical Image Analysis group. His research focuses on AI-driven medical image analysis, including algorithms for image reconstruction, registration, and clinical decision support. His research interests span AI applications in healthcare, machine learning for medical imaging, and computational methods for clinical diagnostics. Notable contributions include over 500 publications and 60+ PhD graduates, with key works in federated learning, cardiac motion analysis, and biomarker development. Awards include the Leibniz Prize (2025), Royal Academy of Engineering Fellowship (2015), and multiple ERC grants. He leads the BioMedIA research group and is an editorial board member of Medical Image Analysis . Recent publications highlight advancements in AI-driven medical imaging, such as secure federated learning frameworks and deep learning models for disease prediction. His work bridges academic and industrial sectors through initiatives like IXICO, an Imperial spin-out. Current affiliations include roles at both Imperial and TUM, emphasizing interdisciplinary collaboration in healthcare technology. Advising and grants: Supervised over 60 PhD students and 40 post-docs. Secured grants including ERC Synergy (2013) and ERC Advanced (2020). Active in labs focused on biomedical image computing and AI in healthcare systems. Collaborative efforts include the BioMedIA group and TUM’s AI initiatives. Labs/teams: Leads the Biomedical Image Analysis group at Imperial and the TUM AI in Medicine team. Collaborates extensively on projects like cardiac imaging analysis and federated learning for healthcare.

Päivi Erikssonمشاهده پروفایل

استاد

• Innovation Management
• Academic Entrepreneurship
• Collaborative Research
• +۴ مورد دیگر

Päivi Eriksson is a Professor of Management at the University of Eastern Finland (UEF) Business School. She co-leads the Innovation Management research group and coordinates the MSCA Neuro-Innovation PhD Programme (2021-2026) and NOVEL Postdoctoral Programme (2024-2029). Her research focuses on innovation management, academic entrepreneurship, and collaborative research methodologies. She leads the Neuro-Innovation and Impact research team within UEF's neuroscience community (NEURO). Key projects include DATASLEEP (2021-2025), CO-RESEARCH (2022-2026), and Shadows in Paradise (2022-2032). Her work bridges academic research with societal impact through initiatives like the Auria Biobank commercialization. She has authored/co-authored over 150 publications in journals like Journal of Affective Disorders , Qualitative Health Research , and International Journal of Human Resources Development . Eriksson's awards include research council grants and contributions to Elgar's Encyclopedia of Innovation Management . She advises on academic entrepreneurship policies and collaborates with 30+ external partners in healthcare, tech, and industry sectors. Her teaching emphasizes innovation empathy and service design frameworks for customer-centric solutions.

Giulia Donatiمشاهده پروفایل

پژوهشگر

• Biodiversity Conservation
• Environmental Management
• Social-Ecological Systems
• +۳ مورد دیگر

Dr. Giulia Donati is a Researcher at Eawag – Swiss Federal Institute of Aquatic Science and Technology, affiliated with the Department of Environmental Social Sciences. She holds a PhD from ETH Zürich and has extensive experience in conservation biology, inter/transdisciplinary research, and project management. Her work focuses on social-ecological systems, ecological connectivity, and biodiversity conservation in aquatic and terrestrial ecosystems. Education: PhD (2016–2020, ETH Zürich), MSc (2013–2015, University of Lausanne), BSc (2010–2013, University of Lausanne). Notable roles include postdoctoral research on BlueGreenNet (2021–2024) and Connect-HDL (2020), and leadership in the Save Our Seas Foundation project (2019–2020). Research emphasizes social-ecological networks, blue-green infrastructure, and amphibian connectivity in human-dominated landscapes. Projects like BlueGreenNet and Connect-HDL integrate ecological modeling with stakeholder collaboration to enhance biodiversity. Her work bridges ecology, policy, and urban planning to address global conservation challenges. Publications span topics from clownfish genetics to urban biodiversity frameworks, reflecting interdisciplinary approaches. Active in science communication and policy-relevant research, she collaborates across sectors to foster sustainable solutions. Current affiliations include Eawag’s PEGO research group and the Department of Environmental Social Sciences.

Ying Chenمشاهده پروفایل

دانشیار

• Financial Statistics
• Machine Learning
• Quantitative Finance
• +۷ مورد دیگر

Assoc Prof Ying Chen is an Associate Professor at the National University of Singapore , affiliated with the Department of Mathematics, Asian Institute of Digital Finance (as Academic Director of PhD Program in Digital FinTech 2022–2024), Risk Management Institute (2019–2023), Department of Statistics and Data Science (2019–2023), and Department of Economics (2018–2023). She also contributes to NUS Graduate School for Integrative Sciences and Engineering since 2016. Research Interests include: AI forecasting and quantum computing for finance Nonstationary time series and functional data analysis Energy data analytics and precision medicine Network autoregression and spatial-temporal modeling Explainable AI and citation metrics Portfolio liquidation and market-making algorithms Article Trends demonstrate expertise in: Adaptive forecasting for gas flows and electricity prices Blockchain network influence detection Quantum computing applications in finance Functional autoregression with mixed predictors Credit rating fairness and explainability High-resolution implied volatility modeling Scientific Awards include: ISI Elected Member (2016–) International Statistical Institute Council (2023–2027) IASC Scientific Secretary (2017–2019, 2023–2025) Advisory roles for EU FIN-TECH and xAIM projects

• Climate Change Adaptation
• Infrastructure Resilience
• Risk Analysis
• +۵ مورد دیگر

Jim Hall is a Professor of Climate and Environmental Risk at the University of Oxford's School of Geography and the Environment, and serves as Director of Research there. He is also a Visiting Fellow at Linacre College and holds leadership roles including Chair of the Science Advisory Committee at IIASA, and Expert Advisor to the UK's National Infrastructure Commission. His work focuses on systemic risk analysis, infrastructure resilience, and policy implications of climate change adaptation. Prof Hall has pioneered methodologies like the National Infrastructure Systems Model (NISMOD) and chairs the Data and Analytics Facility for National Infrastructure (DAFNI). His research spans flood risk management, energy systems decarbonization, and transboundary water resource conflicts in regions such as the Eastern Nile Basin and the Caribbean. Key research areas include robust decision making under uncertainty, info-gap theory applications, and integrated assessments of human-environmental systems. He has contributed to major international assessments, including the IPCC's Fourth Assessment Report, and developed frameworks for multi-hazard stress testing of infrastructure networks. Scientific Awards: George Stephenson Medal (2001), Prince Sultan Prize for Water (2018), Royal Academy of Engineering Fellowship (2010) His advising and grants work includes mentoring a DPhil student Erin Canning and leading projects like MARIUS and ENHANCE. He has also developed innovative modeling tools for coastal erosion prediction and probabilistic assessments of global shipping fuel transitions. Prof Hall’s research groups actively engage in interdisciplinary projects, including the Oxford Martin Programme on Resource Stewardship and the UK Infrastructure Transitions Research Consortium. His work emphasizes bridging scientific analysis with actionable policy solutions for climate adaptation.

Sushmita Rujمشاهده پروفایل

دانشیار

• Cryptography
• Blockchains
• Data Privacy
• +۶ مورد دیگر

Sushmita Ruj is an Associate Professor in the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney. She serves as the Faculty of Engineering Lead for the UNSW Institute for Cybersecurity (IfCyber) and as the Taste of Research (ToR) Coordinator within the School of Computer Science and Engineering. Her academic journey includes previous positions as a Senior Research Scientist at CSIRO's Data61 (2019-2022), Associate Professor at the Indian Statistical Institute, Kolkata, and Assistant Professor at the Indian Institute of Technology (IIT), Indore. Dr. Ruj's primary research interests focus on applied cryptography, post-quantum cryptography, cybersecurity, blockchains, and data privacy. She designs practical, efficient, and provably secure protocols for real-life applications, with particular emphasis on critical infrastructure including smart grids, cloud computing, ad hoc networks, and data sharing frameworks. As quantum technology advances, her work increasingly focuses on developing quantum-safe algorithms to ensure a more secure Internet infrastructure. Her research spans multiple domains including cryptographic key management, proofs of storage, verifiable computation, vector commitments, and privacy-enhancing technologies for cloud and IoT environments. Her recent publications demonstrate a strong trend toward post-quantum cryptography solutions, with particular emphasis on blockchain applications, DNS security, and privacy-preserving protocols for industrial IoT. The research shows increasing focus on practical implementations of theoretical cryptographic concepts, with applications across multiple sectors including finance, healthcare, and critical infrastructure. Her work bridges the gap between theoretical cryptography and real-world security challenges, with growing emphasis on the transition from classical to quantum-resistant systems. Best Paper Award at ACISP 2024 JNCA Best Survey Award (2023) NSW Innovation Award (iAward) Merit Winner (2022) Women in Science Award from CSIRO (2020) ACM Senior Member (2016) IEEE Senior Member (2015) Samsung GRO award (2014) Dr. Ruj has successfully mentored numerous PhD and Master's students, with many of her former students now holding academic positions at institutions like IIT Indore, TU Wien, and CISPA Helmholtz Center. She has secured significant competitive funding including multiple Australian Research Council (ARC) grants, Samsung GRO Award, NetApp Faculty Fellowship, Cisco Academic Grant, and IBM Research grant. Her current research portfolio includes projects on blockchain-based quantum-safe digital medical passports, embedding trust in digital IDs, and resilience of supply chain unstructured data. As Faculty of Engineering Lead for IfCyber, Dr. Ruj plays a key role in UNSW's cybersecurity research initiatives. She has served on editorial boards for prestigious journals including IEEE Transactions on Information Forensics and Security and has held leadership positions in major conferences such as ACISP 2021 and Indocrypt 2020. She was also a member of the working group on "Blockchain For Cybersecurity" for the National Blockchain Roadmap of Australia and the first Blockchain Working group set up by the Reserve Bank of India.

Xavier Brussetمشاهده پروفایل

استاد

• Supply Chain Management
• Logistics
• Operations Management
• +۶ مورد دیگر

Xavier Brusset is a Professor in Supply Chain at SKEMA Business School since 2016, where he also serves as Director of the PRISM Research Center since 2017. Previously, he held professorial positions at Toulouse Business School (2015-2016) and ESSCA School of Management (2009-2015), where he was responsible for the Master 2 in Purchasing and Supply Chain Management program. His academic journey includes a PhD in Management Sciences from Université Catholique de Louvain (2010) and a Habilitation à Diriger des Recherches from Université Paris Ouest Nanterre La Défense (2016). His research spans multiple critical areas in supply chain management, with particular focus on supply chain resilience, blockchain applications, weather risk management, and pandemic impacts on supply chains. Brusset has developed innovative approaches to understanding how supply chain partners interact, how information affects their behavior, and how external disruptions like weather anomalies and pandemics impact operational efficiency. His work bridges theoretical models with practical applications, often developing decision-support tools for managers facing complex supply chain challenges. Brusset's publication record shows a clear evolution of research interests, beginning with foundational work on supply chain contracts and information sharing, then expanding to weather risk management, and most recently focusing on pandemic disruptions and blockchain applications. His 15 most recent publications (2018-2025) demonstrate increasing sophistication in modeling complex supply chain phenomena, with particular emphasis on network effects, ripple effects, and multi-echelon optimization under disruption scenarios. Editorial board member of Logistics Research Editor of International Journal of Retail and Distribution Management (2022-2023) Recognized EU expert for CINEA research projects evaluation Organizer of the Colloquium on European Research in Retailing (CERR) Reviewer for multiple top journals including International Journal of Production Economics As an advisor, Brusset has supervised doctoral students including R. Alkhudary (co-director, Université Paris 2 Panthéon-Assas) and V. Capocasale (rapporteur). His professional experience extends beyond academia to include industry roles in financial markets and logistics technology, having co-founded WebLogistix, a platform for sharing logistics information in Argentina. His research has practical applications across multiple sectors, particularly in retail, food supply chains, and manufacturing, where he develops tools to help managers mitigate risks and optimize operations under uncertainty.

Vishal Ahujaمشاهده پروفایل

دانشیار

• Healthcare Operations
• Operations Management
• Service Operations
• +۷ مورد دیگر

Vishal Ahuja is an Associate Professor and Corrigan Research Professor at Southern Methodist University's Cox School of Business, with adjunct faculty status at University of Texas Southwestern Medical Center. He focuses on decision analytic tools for healthcare improvement through operations management. PhD, University of Chicago Booth School of Business MBA, University of Chicago Booth School of Business His research interests span healthcare operations, service optimization, and AI applications in clinical decision-making. He collaborates with the Department of Veterans Affairs, Parkland Hospital, and pediatric institutions to address care quality and delivery efficiency. Recent publications emphasize predictive modeling for chronic disease management, adaptive clinical trial design, and regulatory healthcare policy. Awards include the Dlin/Fischer Clinical Research Award (2021), INFORMS Pierskalla Award (2012), and 2025 AI75 recognition for Dallas-Fort Worth AI leadership. D CEO Excellence in Healthcare Award - Outstanding Healthcare Innovator (2023) NSF Game Changer Academies for Advancing Research Innovation (2022) C. Jackson Grayson Faculty Innovation Award (2022-23) At SMU, he teaches graduate courses in operations, supply chain, and service management, integrating corporate sector experience from chemical and consumer goods industries. His work has been cited by the FDA in safety labeling changes workshops.

• Decision Analysis
• Operations
• Information Systems
• +۷ مورد دیگر

John C. Butler is a Clinical Associate Professor in the Finance Department at the McCombs School of Business, University of Texas at Austin. He holds leadership roles as Academic Director of the Kay Bailey Hutchison Energy Center, Director of the MS Finance Program, and Director of the Energy Management Minor. His academic journey includes a PhD in Management Science and Information Systems from UT Austin (1998) and a BBA from Texas A&M University (1991). His research focuses on applications of decision analysis across domains including operations, finance, and information systems. Key areas include risk analysis, optimization, multi-attribute utility theory, and energy finance. His work integrates theoretical modeling with empirical validation to address complex decision-making challenges in both public and private sectors. Butler's publications demonstrate a consistent focus on decision modeling methodologies, with recent work emphasizing risk quantification and utility theory applications. His articles frequently intersect operations research, behavioral economics, and systems optimization, reflecting interdisciplinary approaches to solving managerial and policy problems. Awards and Honors: MBA Applause Award (2008, 2011) Finalist, INFORMS Franz Edelman Award (2004) INFORMS Decision Analysis Society Practice Award (2000) Fred Moore Teaching Award Dean's Research Fellowship, Ohio State University (2004) Leadership & Advising: Butler has supervised 11 PhD students to completion and secured significant grants including DOE funding for nuclear terrorism risk analysis. He directs multiple energy finance initiatives and serves on editorial boards for Decision Analysis and previously Decision Support Systems . Centers & Programs: As Academic Director of the Kay Bailey Hutchison Energy Center, he leads interdisciplinary energy research. He also developed the Energy Finance concentration and redesigned the MS Finance curriculum to incorporate quantitative energy market analysis.