جست‌وجوی استاد و پژوهشگر

• Operations Research
• Stochastic Programming
• Energy Systems
• +۵ مورد دیگر

Patrizia Beraldi is an Associate Professor of Operations Research at the Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria. She has been with the university since 2001, holding roles from Research Fellow to her current position. With over 80 publications, her work focuses on stochastic programming, probabilistic constraints, and their applications in energy systems, healthcare, finance, and logistics. Education: PhD in System Engineering and Computer Science (2000), University of Calabria Degree in Management Engineering (cum laude, 1995), University of Calabria Her research spans solution methods for network flow problems, stochastic programming with recourse, and probabilistic constraint modeling in diverse fields like energy procurement, drone routing, and financial optimization. Recent publications emphasize stochastic bilevel models for energy tariffs and ML-enhanced optimization frameworks. Scientific Awards: Best paper award, 2015 IMA Journal of Management Mathematics Best presentation award, ICEER Conference 2017 Best poster award, ICORES 2018 She supervises numerous master's and PhD students and leads the Financial Engineering and Risk Management Laboratory at DIMEG. Her editorial roles include Associate Editor for TOP , Algorithms , and IMA Journal of Management Mathematics .

Amrit Pal Kaurمشاهده پروفایل

پژوهشگر ارشد

• Smart Grid Technology
• Electric Vehicle Charging Systems
• IoT Applications
• +۳ مورد دیگر

Dr. Amrit Pal Kaur is a Research Fellow at the University of Surrey, affiliated with the School of Computer Science and Electronic Engineering and the Advanced Technology Institute. Her research focuses on smart grid technology, electric vehicle integration, IoT applications, and renewable energy systems. She holds a PhD in Electrical and Instrumentation Engineering. Her work spans energy management, V2G systems, and sensor networks. She contributes to advancements in demand-side management and grid optimization. Research Interests: Electric vehicle charging infrastructure and V2G integration IoT-enabled smart metering solutions Optimization of energy systems using machine learning techniques Renewable energy management and tariff modeling Articles Trends: Recent publications emphasize IoT-based net metering for V2G applications and demand-side management strategies. Earlier work explored robotics (SLAM) and music classification via machine learning. Awards: No awards mentioned. Advising & Grants: No details provided on students, grants, or team projects. Labs/Teams: Active within the Advanced Technology Institute and School of Computer Science and Electronic Engineering.

• Research Commercialisation
• Entrepreneurship Education
• Sustainable Development Goals
• +۵ مورد دیگر

Professor Jerome Donovan is a leading academic in Entrepreneurship and Innovation at Swinburne University of Technology's School of Business, Law and Entrepreneurship. He serves as Research Director for the Department of Business, Technology and Entrepreneurship and holds concurrent roles as Co-Founder of mDetect Pty Ltd. and Sensfit Technologies Pty Ltd., plus Principal Advisor to Vietnam's Ministry of Science and Technology. Specializes in research commercialisation and early-stage startups Recipient of 2024 School of Business, Law and Entrepreneurship Teaching Excellence Award (Team) 2022 AFR Higher Education Awards National Finalist for Research Commercialisation His research spans corporate sustainability, land administration technologies, and sustainable supply chain management. Recent publications analyze Japanese multinational environmental practices across Southeast Asia, sustainability strategy implementation in food manufacturers, and geospatial land administration innovations. Awards emphasize his contributions to transformative research commercialisation and international educational programs. Grants highlight his work on disability employment (2024), circular economy initiatives (2024), and multi-year projects addressing SME export performance in Qatar (2016-2019). He supervises doctoral research on topics including sustainable supply chains, frugal innovation, and corporate sustainability in ASEAN contexts.

Cornelia Fernerمشاهده پروفایل

مدرس

• Machine Learning
• Natural Language Processing
• Data Science
• +۳ مورد دیگر

Cornelia Ferner serves as a Lecturer in the Department of Information Technologies and Digitalisation at Salzburg University of Applied Sciences, based at Campus Urstein. Her office is located in room Urstein-430, and she can be reached via email at cornelia.ferner@fh-salzburg.ac.at or by telephone at +43-50-2211-1329. Education: Bachelor of Science (BSc) Her research expertise lies at the intersection of artificial intelligence and real-world applications, with primary focus areas including machine learning (particularly deep learning and generative models), natural language processing (topic modeling, sentiment analysis), and data science methodologies. She applies these techniques to energy systems analysis, social media mining for refugee movement tracking, and process optimization in business contexts, demonstrating strong interdisciplinary capabilities across technical and societal domains. Analysis of her publication trends (2017-2022) reveals consistent methodological innovation in neural networks and probabilistic modeling, applied to energy data (smart grids, tariff structures) and social dynamics (event detection, refugee movements). Her work bridges theoretical AI advancements with practical European industry challenges, particularly in digital transformation of energy markets and social media analytics. No scientific awards were mentioned in available sources. Information regarding graduate student supervision or specific research funding was not documented in current materials, though her multi-case studies indicate collaborative industry engagement. Her publications suggest involvement in cross-institutional energy sector projects and social impact research initiatives. Details about laboratory facilities or dedicated research teams were not available in provided documentation.

Gopinath Munisamyمشاهده پروفایل

استاد

• International Trade
• Agricultural Policy
• Productivity
• +۴ مورد دیگر

Gopinath Munisamy is a Professor at the University of Georgia within the College of Agricultural & Environmental Sciences and the Agricultural & Applied Economics department. He holds a Distinguished Professor title in Agricultural Marketing and is affiliated with the Center for Agribusiness and Economic Development (CAED) . Ph.D., Agricultural & Applied Economics, University of Minnesota, 1995 M.Sc., Agricultural Economics, Indian Agricultural Research Institute, 1990 B.Sc., Agricultural Sciences, Tamil Nadu Agricultural University, 1988 His research spans International Trade , Agricultural Policy , Productivity , Economic Development , and Consumer Demand , with a focus on integrating Machine Learning and AI into agricultural economics. Recent publications examine trade policy uncertainty , climate resilience , and global trade patterns . Key awards include leadership roles in the Global Forum on Agriculture (OECD), Gamma Sigma Delta Honor Society , and the Herald Jensen Award for his Ph.D. thesis at the University of Minnesota. His work bridges political economy and agricultural trade , particularly in South Asia and Chile .

Maureen Irishمشاهده پروفایل

عضو هیئت علمی

• International Trade Law
• WTO Law
• Climate Change Law
• +۳ مورد دیگر

Maureen Irish is a Professor Emerita at the University of Windsor Faculty of Law, specializing in international economic law with expertise in trade agreements, dispute resolution, and regulatory frameworks. She holds a DCL and LLM from McGill University, an LLB from University of Toronto, and a BA from University of Toronto. Her research examines trade and development relationships, WTO governance, climate change impacts on trade, Canada-US legal frameworks, and customs tariff law. Recent publications analyze special treatment in WTO systems, trade facilitation agreements, and NAFTA regulatory cooperation cases. Professional activities include service on NAFTA and Canada-US Free Trade Agreement dispute settlement panels addressing trade classification and subsidy disputes. Cases include rulings on softwood lumber, corrosion-resistant steel, and concrete panel disputes. Current research investigates arms trade regulation under WTO law and multimodal transportation frameworks.

• Urban Analytics
• Smart Charging Systems
• Electric Vehicle Infrastructure
• +۵ مورد دیگر

Dr. Pieter Bons serves as a Senior Lecturer at the Faculty of Technology, Hogeschool van Amsterdam, where he teaches Applied Mathematics and Data Science. His academic work spans urban analytics, smart charging systems, and geospatial modeling, with significant contributions to electric vehicle infrastructure and climate adaptation research. His research focuses on applying data science to urban challenges, particularly in smart charging for electric vehicles and neighborhood typology classification . Bons specializes in extracting actionable insights from complex urban datasets while addressing critical issues like data bias, quality, and privacy. His work bridges theoretical data science with practical urban applications, notably through projects like the Rijkswaterstaat charging infrastructure study and nationwide neighborhood typology mapping. Recent publications reveal a clear trajectory from fundamental physics (2010-2017) to applied urban analytics (2020-present), with current work emphasizing energy grid optimization through smart charging AI-driven climate adaptation tools geospatial analysis for urban planning His fingerprint analysis highlights strong connections to Smart Charging (95%), Public Charging Stations (36%), and Electric Vehicles (54%). Award highlights: HvA onderzoeksprijs 2021 for collaborative urban research Nominatie KennisDC Parel 2023 for innovation in zero-emission infrastructure Bons actively enhances data literacy across the faculty through educational initiatives like Data Studio, integrating students into real-world research cases. His activities include stakeholder presentations for Rijkswaterstaat, knowledge clips on neighborhood typologies, and academic talks on walkability and zero-emission corridors. He contributes to datasets like the Wijktypologie Buurtniveau 2023, supporting national climate adaptation efforts. His work occurs at the intersection of urban planning, energy systems, and AI, with current projects focusing on balancing urban energy grids through flexible EV charging and developing nationwide neighborhood classification systems for climate resilience.

Katrien Antonioمشاهده پروفایل

استاد

• Insurance Analytics
• Data Science
• Predictive Modeling in Insurance
• +۳ مورد دیگر

Katrien Antonio is a **full professor** in actuarial science and insurance analytics at **KU Leuven** and holds a **part-time professorship** in actuarial data science at the University of Amsterdam. She leads the **Insurance Research Group** and chairs the **Department of Accountancy, Finance and Insurance** within the **Faculty of Economics and Business (FEB)**. Her roles include directing the LRISK research center and overseeing education commissions at KU Leuven’s Leuven and Kortrijk campuses. **Research Interests**: Insurance analytics, data science, predictive modeling in insurance, actuarial science, and sustainable finance. Key projects include designing inclusive insurance products, compliant actuarial models, and risk analytics for societal impact. **Publications**: Her recent work focuses on environmental impacts on mortality, neural networks for insurance pricing, fraud detection, and IoT-driven maintenance risk assessment. She has published in top journals like *Journal of the Royal Statistical Society*, *North American Actuarial Journal*, and *European Journal of Operational Research*. **Education**: PhD in Mathematics (KU Leuven, 2007), with prior degrees in Mathematics from the same institution. Extensive teaching experience across higher education, emphasizing data-driven insights and innovative materials. **Grants & Projects**: Leads initiatives such as the “Actuaries and STatisticians” project (2022–2025) and “VALERIA” (2021–2024), focusing on emerging risks and sustainable finance. **Labs & Teams**: Directs the LRISK center, fostering interdisciplinary collaboration in risk analysis. Active in academic networks, including IMAC and the Faculty Board of Economics and Business.

Michel Anlikerمشاهده پروفایل

مدرس

• Customs Law
• International Trade Law
• Trade Compliance
• +۷ مورد دیگر

Michel Anliker is a legal expert and lecturer specializing in customs law, international trade compliance, and VAT regulations. He serves as Head of Customs, Import and Export Compliance at the Schindler Group and teaches in the CAS FH in Customs Law program. His expertise bridges corporate compliance and academic instruction, focusing on Swiss, EU, and Asia-Pacific trade frameworks. Research Interests: Customs and international trade law Free trade agreements (FTAs) and economic integration Tariff classification and customs valuation VAT and tax compliance in cross-border transactions Trade facilitation and regulatory challenges Pharmaceutical and art trade compliance His recent publications reflect a strong focus on trade policy developments, particularly between Switzerland and Asian nations, including China, the Philippines, and ASEAN countries. He frequently analyzes legal procedures, compliance risks, and legislative reforms in customs and foreign trade. Scientific Contributions: Author and co-author of numerous articles in professional journals such as ZOLL REVUE, China Compass, and EXPERT FOCUS Contributor to the book Singapore and Switzerland: Secrets to Small State Success (2016) Regular commentator on EU and Swiss customs law developments Michel Anliker advises on corporate trade compliance and contributes to postgraduate legal education. While not affiliated with a traditional university faculty, he plays a significant role in professional legal training and industry guidance. He has collaborated extensively with experts such as Simeon Probst and Corinne Scagnet on compliance topics. He is active in professional networks and continues to publish on current trade law issues.

Wolffgangمشاهده پروفایل

استاد

• Artificial Intelligence
• Deep Learning
• Natural Language Processing
• +۷ مورد دیگر

Professor Wolffgang is an academic at the University of Münster, affiliated with the Institute of Customs and International Trade Law. He coordinates international conferences on protectionism and tariff reforms, and has made significant contributions to artificial intelligence applications in medical diagnostics and economic modeling. His research spans two primary domains: Medical Informatics: Applying AI/ML to prostate cancer diagnosis and EHR data extraction Economic Simulation: Developing multi-agent systems and modeling frameworks Recent publications demonstrate his work in: Interpretable AI for histology image analysis Automated data extraction from medical records Model-driven web application development Professor Wolffgang actively participates in international academic discourse, most recently moderating panels on customs reform during global economic shifts.

• International Economics
• Foreign Direct Investment
• Intellectual Property Economics
• +۳ مورد دیگر

Andreas Bielig serves as Professor at Warsaw School of Economics (SGH) in the Department of German Economic Research, holding PhD and DSc degrees. His academic office is located at Batorego 8, 02-591 Warsaw (Mokotów), building S, room 2.29. Affiliated exclusively with SGH's institutional structure, he maintains active research status without indication of part-time appointment or administrative roles. Professor Bielig's research centers on International Economics with specialized focus on German-Polish economic relations, foreign direct investment dynamics, and digital currency systems. His work examines geopolitical impacts on social market economies (notably Ukraine war consequences), intellectual property's role in economic development, and longitudinal analysis of German FDI patterns across 1989-2022. Methodologically, he employs empirical comparative analysis with strong emphasis on policy-relevant outcomes for Central European integration. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) Geopolitical recalibration of global investment flows toward Indo-Pacific regions, (2) Structural transformation in digital currency competition challenging traditional market architectures, and (3) Adaptive responses of social market economies to compound crises. His scholarship consistently bridges theoretical frameworks with Polish-German policy coordination needs, demonstrating particular expertise in FDI impact measurement and digital economy governance. While the provided materials document extensive publication activity, no scientific awards, student advisement records, or research grant details are disclosed. Similarly, laboratory affiliations, research teams, or future project pipelines remain unspecified in available sources.

Yi Fangمشاهده پروفایل

استاد

• Information Retrieval
• Natural Language Processing
• Machine Learning
• +۳ مورد دیگر

Yi Fang is a Professor in the Department of Computer Science and Engineering at Santa Clara University's School of Engineering, holding a Ph.D. in Computer Science from Purdue University under advisor Professor Luo Si. Her academic leadership spans over 15 years with significant contributions to information retrieval and machine learning systems. Education: Ph.D. in Computer Science, Purdue University Research Focus: Professor Fang pioneers scalable, principled approaches in information retrieval , natural language processing , and machine learning , with recent emphasis on fairness in AI and privacy preservation . Her work bridges theoretical rigor with real-world applications in search engines, recommendation systems, and ethical AI deployment, particularly addressing bias in large language models and search systems. Publication Evolution: Her research trajectory shows a clear shift from foundational work in probabilistic models (2010-2015) toward deep learning integration (2016-2020), culminating in her current focus on ethical AI (2021-2025). Recent publications demonstrate increasing concentration on fairness metrics, bias mitigation in ranking systems, and privacy-preserving techniques for LLMs, reflecting urgent societal needs in AI governance. Awards & Recognition: Teacher of the Year, School of Engineering (2017) Researcher of the Year, School of Engineering (2017) Brutocao Family Foundation Award for Curriculum Innovation (2024) Outstanding Service Awards from ACM CIKM and IEEE ICME (2013) Purdue University Outstanding Dissertation Award nomination Mentorship & Leadership: Professor Fang actively mentors PhD and MS students through SCU's Computer Science program, prioritizing candidates with AI coursework. She directs the university-wide Responsible AI initiative and holds influential roles including ACM ICTIR General Co-Chair (2019), Program Co-Chair (2021), and SIGIR Senior Program Committee member (2020-2025), shaping research directions in information retrieval globally. Interdisciplinary Impact: As Director of Santa Clara's Responsible AI program, she leads cross-departmental collaborations ensuring AI advancements remain safe, equitable, transparent , and societally beneficial , with recent projects targeting bias in electricity tariff systems, misinformation detection for Chinese Americans, and fairness audits for news sources.

Yuhong Liuمشاهده پروفایل

دانشیار

• Trustworthy Generative AI
• Blockchain Security
• IoT Anomaly Detection
• +۳ مورد دیگر

Yuhong Liu is an Associate Professor in the Department of Computer Science and Engineering at Santa Clara University's School of Engineering. She holds a B.S. and M.S. from Beijing University of Posts and Telecommunications (2004, 2007) and a Ph.D. from the University of Rhode Island (2012). Her research focuses on trust, security, and privacy in emerging technologies including Generative AI, IoT, blockchain, and social media. She leads the Trustworthy Computing Lab, which develops solutions for IoT security, misinformation detection, and energy-efficient systems. Her research spans: Generative AI : Trustworthy synthetic data generation and multi-agent collaboration Blockchain : Multi-signature schemes and decentralized consensus IoT Security : Anomaly detection and lightweight cryptography Social Media : Misinformation mitigation and privacy preservation Recent publications emphasize blockchain-enabled security, IoT anomaly detection, and AI fairness, reflecting a trend toward practical, cross-domain solutions for cyber-physical systems. Her work frequently integrates machine learning with cryptographic techniques to address real-world vulnerabilities. Awards & Honors: IEEE Rising Star Service Award (2023) APSIPA Distinguished Lecturer (2021-2022) Researcher of the Year, Santa Clara University (2019) Best Paper Awards at IEEE SocialCom 2010 & UMEDIA 2016 She advises 7+ graduate students on IoT security, blockchain, and social media analytics. She co-leads the NSF-funded EuReCa Global Center for clean energy research and has organized panels on AI ethics and disinformation. Her lab collaborates with industry partners to deploy secure edge computing solutions.

• Optimization
• Supply Chain Management
• Sustainability
• +۵ مورد دیگر

Metin Türkay is a Professor and Head of the Department of Industrial Engineering at Koç University, School of Industrial Engineering and Operations Management. His research bridges mathematical optimization with applications in supply chain systems, sustainability, and computational biology. PhD, Carnegie Mellon University (1996) MSc, Middle East Technical University (1991) BS, Middle East Technical University (1989) His research focuses on optimization theory and its implementation in multi-objective supply chain problems, sustainable operations , and computational biology . Recent studies explore circadian rhythm regulation through small molecule discovery alongside supply chain carbon footprint assessment. Key article trends reveal a dual focus on optimization algorithms (including MILP, multi-objective programming) and interdisciplinary applications spanning diabetes research, drug design, and sustainable energy networks. IBM Faculty Award (2009) IBM SUR Award (2007) TÜBİTAK Incentive Award (2006) Türkay leads projects integrating mathematical programming with machine learning for problems in octane optimization, tumor classification, and logistics planning. His work demonstrates optimization's transformative potential across industrial and biomedical domains.

Brian Thomasمشاهده پروفایل

مدرس ارشد

• Tariff Classification
• Tariff Policy
• Customs Administration
• +۲ مورد دیگر

Brian Thomas is a Senior Lecturer at the Centre for Customs and Excise Studies. With 36 years of experience as a former customs officer at the Australian Customs Service, he specializes in tariff classification, policy development, customs systems, and staff training. He has designed and delivered national and international training programs for customs officials, government personnel, and industry stakeholders. Education: BA Cert IV in Assessment & Workplace Training Research Interests: Brian's work focuses on the practical and theoretical aspects of customs and excise, including tariff legislation, administrative frameworks, and the development of training methodologies for global customs operations. His expertise bridges policy implementation and workforce capacity building in customs administration.