جست‌وجوی استاد و پژوهشگر

• Lab-on-a-Chip Technology
• Microfluidics
• Molecular Diagnostics
• +۳ مورد دیگر

Apl. Prof. Dr. Felix von Stetten is an Associate Professor and Senior Scientist at the Laboratory for MEMS Applications within the Department of Microsystems Engineering (IMTEK) at the University of Freiburg. He also serves as an Executive Board Member at the Hahn-Schickard Institute of Microanalysis Systems. His work bridges academia and industry, focusing on lab-on-a-chip technologies, microfluidics, and energy harvesting for biomedical applications. Education: Studied Agricultural Sciences and Biotechnology at the Technical University of Munich, earned a PhD in Microbiology there. Post-2004, he joined IMTEK’s MEMS Applications Lab, later co-founding Hahn-Schickard’s Lab-on-a-Chip division in 2008, which became an independent institute in 2016 under his leadership. Research Interests: His work centers on miniaturized diagnostic systems (e.g., Lab-on-a-Disk platforms), energy harvesting for medical implants, and microfluidic applications. Key innovations include centrifugal microfluidic systems, smartphone-integrated diagnostic tools, and glucose fuel cell technologies. Publications: Over 1200 citations highlight contributions to microfluidic unit operations, digital PCR, and field-deployable diagnostics. Recent work emphasizes automation in pathogen detection and flexible lab-on-foil platforms. Awards: Not explicitly listed in provided texts. However, his leadership roles and impactful research suggest significant recognition in microsystems engineering. Advising/Grants: Leads major projects like BrainLinks–BrainTools and contributes to initiatives such as FRIAS and PlanOS. Manages interdisciplinary teams and collaborates with industry partners like Endress+Hauser and TwistDx. Labs/Teams: Oversees the Hahn-Schickard Institute for Microanalysis Systems and collaborates with IMTEK’s Application Development group. Active in spin-off ventures such as SpinDiag GmbH.

Vera Tilsonمشاهده پروفایل

دانشیار

• Healthcare Operations Management
• Operations Management
• Supply Chain Management
• +۳ مورد دیگر

Dr. Vera Tilson is an Associate Professor at the Simon Business School, University of Rochester, specializing in Healthcare Operations Management and Operations Management. Her research focuses on healthcare operations optimization, stochastic scheduling, and supply chain management. Prior to academia, she held roles as a software engineer and project manager in telecommunications, medical instrumentation, and finance. Her teaching interests include quantitative decision-making and healthcare operations, for which she received the MBA Superior Teaching Award in 2009. Her work bridges academic research with practical applications, addressing challenges such as patient no-show management, medication waste reduction, and healthcare GPO strategies. She has published extensively in journals like Management Science, MSOM, and Operations Research. Recent research explores emergency department workflow optimization, humanitarian supply chains, and real-time capacity management in healthcare settings. Her contributions highlight interdisciplinary approaches combining operations research, data science, and healthcare analytics.

• Marine Renewable Energy
• Wind Energy Systems
• Drivetrain Design and Reliability
• +۷ مورد دیگر

Amir R. Nejad is a Professor in the Department of Marine Technology at NTNU, leading the Marine Energy Systems and Autonomics (MESA) research group. He holds roles such as Chair of the EAWE WindEurope Scientific Track Committee and co-chair of the Drivetrain Technical Committee at the European Academy of Wind Energy (EAWE). His research focuses on stochastic design, reliability-based operation, dynamic modeling, and fault detection in marine and offshore renewable systems. Nejad is an editorial board member for journals like Wind Energy Science and Ocean Engineering , and a member of ISO committees on drivetrain health monitoring. Education: PhD in Marine Technology, NTNU (2015) MSc Subsea Engineering, University of Aberdeen (2012) BSc Mechanical Engineering, Tehran University (2009) His research interests emphasize offshore wind drivetrain reliability, condition monitoring, and digital twin applications. Recent work includes studies on blade bearing fatigue estimation, SCADA-based lifetime extension of drivetrains, and wake steering techniques in floating wind farms. Key awards include multiple 'Best Lecturer' honors at NTNU and international conference recognitions. His research has been supported by grants such as the Nowitech Fellowship and DNV Education Fund. Key Projects: Marine System Dynamics and Vibration Lab (MD Lab) oversees projects on wind turbine drivetrains, floating offshore systems, and digital twin integration. Lab/Teams: MD Lab focuses on advancing marine energy systems through experimental and computational studies.

Mohammad Dehghaniمشاهده پروفایل

استاد آموزشی

• Reinforcement Learning
• Simulation Optimization
• Healthcare Operations
• +۵ مورد دیگر

Mohammad Dehghani is an Associate Teaching Professor in the Department of Mechanical and Industrial Engineering at Northeastern University, where he also serves as Program Director of the Galante Engineering Business Program. He holds a Ph.D. in Engineering Management from Western New England University (2016), an M.S. in Industrial Engineering from Tarbiat Modares University (2011), and a B.S. in Industrial Engineering from Yazd University (2008). His research focuses on Reinforcement Learning (RL), Simulation Optimization, and Healthcare Operations, with applications in manufacturing, digital twin systems, and UAV routing. He has developed multiple courses in Industrial Engineering and Data Analytics, receiving the 2020 Fostering Engineering Innovation in Education Award and the 2025 DAIS Data Analytics Teaching Award. Education: Ph.D. in Engineering Management, Western New England University, 2016 M.S. in Industrial Engineering, Tarbiat Modares University, 2011 B.S. in Industrial Engineering, Yazd University, 2008 Dehghani’s research bridges AI and operations research, emphasizing practical applications. His work includes developing RL frameworks for manufacturing scheduling and UAV routing, as well as simulation-optimization models for healthcare and pandemic preparedness. He has collaborated on projects addressing supply chain resilience during the COVID-19 pandemic and multi-objective supplier selection processes. His publications span journals like Simulation and conferences such as Winter Simulation Conference (WSC). His honors include the 2015 Best Ph.D. Paper Award at WSC and recognition from the Institute of Industrial and Systems Engineers (IISE). He actively contributes to professional societies, including the American Society of Engineering Management and Institute of Industrial Engineers. His teaching focuses on integrating data analytics and simulation tools into engineering curricula, with courses emphasizing Python integration, simheuristics, and digital twin technology. Dehghani leads initiatives in the Galante Program to enhance engineering-business synergies, preparing students for industry roles through interdisciplinary training. His work emphasizes practical problem-solving, with grants supporting projects in healthcare logistics and sustainable construction in cold climates.

• Belt Conveyor Systems
• Bulk Solids Handling
• Energy Efficiency in Material Transportation
• +۵ مورد دیگر

Professor Craig Wheeler is a distinguished academic in the School of Engineering at the University of Newcastle, specializing in Mechanical Engineering with a focus on bulk solids handling and belt conveyor technology. As Associate Director of the Centre for Bulk Solids and Particulate Technologies and Deputy Chairman for the Australian Society for Bulk Solid Handling, he has established the university as a global leader in fundamental and applied research within this field. Wheeler's research interests primarily center on reducing the energy intensity and environmental impact of ore and mineral transportation globally. His work develops novel theoretical approaches to model and optimize belt conveyor and bulk handling systems, with significant contributions in energy-efficient transportation, dust emission control, and innovative conveying technologies like the Rail Conveyor system. His research bridges fundamental computational techniques with practical industrial applications, addressing real-world challenges in bulk material handling. His extensive publication record demonstrates trends toward increasingly sophisticated modeling techniques, combining continuum mechanics, discrete element methods, and computational fluid dynamics to solve complex problems in bulk material flow and energy consumption. Recent work shows particular emphasis on large-diameter idler rollers for energy savings, rail-running conveyor systems, and advanced dust control methodologies. 2023 Engineers Australia - Australian Society for Bulk Solids Handling 2017 Significant Contributions to Engineers Australia's Warman Design and Build Competition (Weir Minerals) 2017 Australian Council of Engineering Deans National Award for Engineering Education Excellence 2016 Innovative Technology Award (Australian Bulk Handling) 2010 Rising Star Award (Newcastle Innovation, The University of Newcastle) 2009 Pro-Vice Chancellor's Award for Research Excellence 2006 Best Research and Development Project (Australian Bulk Handling Review) 2000 A.W. Roberts Award (Australian Society for Bulk Solids Handling) Professor Wheeler has successfully led numerous Linkage Projects with major companies including Rio Tinto, Veyance Technologies, and Laing O'Rourke, securing significant cash and in-kind contributions for research projects. His industrial consulting experience, built on a 10-year engineering career with BHP, provides valuable insights that bridge fundamental research with practical applications. He actively supervises research students and contributes to professional development courses both within Australia and internationally. As a key member of the Centre for Bulk Solids and Particulate Technologies in association with TUNRA Bulk Solids, Wheeler leads research teams focused on developing eco-friendly conveying solutions. His work has resulted in new licensed technologies, internationally recognized testing methods, design guidelines, and Australian Standards that have transformed industry practices worldwide.

Mustafa Hajijمشاهده پروفایل

استادیار

• Topological Deep Learning
• Graph Neural Networks
• Computational Topology
• +۲ مورد دیگر

Mustafa Hajij is an Assistant Professor in the Data Science program at the University of San Francisco. He holds a PhD in Mathematics from Louisiana State University, an MS in Computer Science, and completed postdoctoral training at University of South Florida and Ohio State University. Previously, he served as Assistant Professor at Santa Clara University and as an AI Research Scientist at KLA Corporation. His research develops foundational frameworks for topological deep learning, including cell complex neural networks and geometric learning architectures that operate beyond graph domains. He leads the NSF-funded project 'A Unifying Deep Learning Framework Using Cell Complex Neural Networks' (DMS-2134231, $547,626). Recent publications establish new paradigms for topological representation learning, including combinatorial complexes and simplicial networks, with applications in computational biology, 3D vision, and drug discovery. He organized the ICML Topological Deep Learning Challenges and develops open-source tools like TopoX for topological learning.

George Bosilcaمشاهده پروفایل

استاد پژوهشی

• Distributed Algorithms
• Parallel Programming Paradigms
• High Performance Computing
• +۳ مورد دیگر

George Bosilca is a Research Professor at the University of Tennessee, Knoxville, affiliated with the Department of Electrical Engineering and Computer Science and the Innovative Computing Laboratory. He holds a PhD in Computer Science (University of Paris XI, 2004) and an MS in Math and Computer Science (University of Paris XI, 1999). His research focuses on distributed algorithms, parallel programming paradigms, performance modeling/optimization, and resilience in programming models. He contributes to exascale computing initiatives through projects like PaRSEC and Open MPI. Key research areas include task-based runtimes, MPI standardization for exascale systems, and fault-tolerant distributed computing. His work emphasizes scalable and portable constructs for high-performance applications. Bosilca is involved with the Innovative Computing Laboratory (ICL) and collaborates on projects like the EPEXA ecosystem and Argobots threading framework. Recent publications highlight advancements in asynchronous many-task systems, GPU-accelerated collective operations, and resilience strategies for HPC platforms. His contributions span theoretical frameworks and practical implementations, bridging algorithmic innovation with real-world HPC challenges.

• Artificial Intelligence
• Machine Learning
• Activity Recognition
• +۱۲ مورد دیگر

Gita Reese Sukthankar is a Professor in the Department of Computer Science at the University of Central Florida (UCF) , where she directs the Intelligent Agents Lab . Her research focuses on activity and plan recognition , with applications in multi-agent systems, robotics, and human-robot interaction. She earned her Ph.D. from the Robotics Institute at Carnegie Mellon University and joined UCF in fall 2007. Research Interests: Her work spans activity recognition , intent inference , multi-agent coordination , and human-robot teams . She has applied these techniques to domains such as adversarial games (e.g., military simulations, Unreal Tournament), assistive technologies, and cooperative robotics. Her research integrates AI, machine learning, and probabilistic models to understand and predict complex team behaviors. Publication Trends: Her publications emphasize spatio-temporal modeling , probabilistic graphical models (e.g., HMMs, CRFs) , and multi-agent plan recognition . She frequently publishes in top venues like AAMAS, AAAI, and ICRA, with a focus on robust recognition of team behaviors, transfer learning, and real-world AI applications. Scientific Awards: NSF CAREER Award (2009) AFOSR Young Investigator (2009) ONR Summer Faculty Fellow (2008) UCF Faculty Excellence for Doctoral Mentoring (2012) CECS Dean's Research Professorship (2013) AAAI Senior Member (2021) ACM and IEEE Senior Member Advising and Grants: She mentors graduate students in AI and robotics and has led research funded by DARPA, AFOSR, and ONR. Her lab develops systems for intelligent agents that can understand and collaborate with humans. She has served on numerous program committees and editorial boards, including ACM Transactions on Autonomous and Adaptive Systems . She teaches courses such as Intelligent Systems , Robotics , and Machine Learning , and has been recognized for both research and teaching excellence. Labs and Teams: She leads the Intelligent Agents Lab at UCF, which focuses on data-driven social informatics and AI for human-agent teams. Her group collaborates with researchers in robotics, computer vision, and cognitive science to build adaptive, intelligent systems.

Andreas J. Kasslerمشاهده پروفایل

استاد

• Software Defined Networking
• Programmable Dataplanes
• Network Virtualization
• +۷ مورد دیگر

Andreas J. Kassler is a Full Professor of Computer Science at Karlstad University, Sweden, where he has been since 2005. He co-chairs the Distributed Systems and Communication (DISCO) group and focuses on networking, cloud computing, and wireless networks. His research includes software-defined networking, future internet architectures, and network optimization. He has authored/co-authored over 130 peer-reviewed publications, holds 6 patents, and serves on editorial boards of journals like Journal of Internet Engineering . Education : Ph.D. in Computer Science, Universität Ulm (2002) Docent (Habilitation), Karlstad University (2007) M.Sc. in Mathematics/Computer Science, Universität Augsburg (1995) Research Interests : Software Defined Networking (SDN) Programmable Dataplanes Wireless Mesh Networks Time-Sensitive Networking (TSN) Edge Computing Machine Learning for Network Optimization Recent Directions : His work spans TSN scheduling, hybrid P4 solutions for 5G, and explainable AI in energy communities. He explores network resilience, latency optimization, and multi-objective control in microgrids. Service Contributions : Track co-chair for VTC 2015 General chair for Wired/Wireless Internet Communications (WWIC) 2013 Editor-in-Chief of IARIA Journal on Advances in Internet Technology Labs/Teams : Leads DISCO group at Karlstad University. Collaborates with global teams on projects like mmWave backhaul networks and SDN-enabled industrial control systems.

• Data Science
• Concept-Drift Management
• Database Systems
• +۱۲ مورد دیگر

Tania Cerquitelli is a Full Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where she leads research in data science, concept-drift management, and inclusive AI technologies. She is a member of SmartData@PoliTO, the GEDI Observatory for Gender Equality, and serves in leadership roles related to social affairs and community policies at the university level. She also acts as a scientific advisor for the partnership with Accenture. Her research interests span Data Science , Concept-Drift Management , Database Systems , Conversational Data Science , and Industry 4.0 . She applies AI and machine learning to industrial, societal, and ethical challenges, particularly in promoting inclusive communication and gender equality in research. The most recent publications highlight her work in explainable AI, concept drift detection, multimodal diagnostics, and AI for social good. Her research integrates machine learning, natural language processing, and computer vision to address real-world problems in manufacturing, healthcare, agriculture, and education. She is an Associate Editor for several prestigious journals including Expert Systems with Applications , Computer Networks , Future Generation Computer Systems , and Knowledge and Information Systems . She has served on the program committees of major conferences such as ECML PKDD, EDBT/ICDT, and ACM KDD, and has been a reviewer and selection committee member for ETH Zurich and EMPA. She actively supervises PhD students and teaches a wide range of courses including Data Science and Database Technologies, Business Intelligence for Big Data, and Gender and Diversity in Research. She is involved in multiple national and international research projects such as E-MIMIC, WEBFARE, and EnABLES, focusing on inclusive AI, smart data, and industrial applications. Her lab affiliations include the DBDM - Database and Data Mining Group (DAUIN) and the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory , where she contributes to advancing data science methodologies and their societal impact.

Hsiao-Dong Chiangمشاهده پروفایل

استاد

• Nonlinear System Theory
• Power System Stability and Control
• Optimal Power Flow
• +۱۲ مورد دیگر

Hsiao-Dong Chiang is a Professor in the School of Electrical and Computer Engineering at Cornell University. He holds a Ph.D. in Electrical Engineering from the University of California, Berkeley, and has made significant contributions to nonlinear system theory and power system stability. His research spans theoretical development and practical applications in electric power systems, nonlinear optimization, and machine learning. B.S., Electrical Engineering, National Taiwan University, 1979 M.S., Electrical Engineering, National Taiwan University, 1981 Ph.D., Electrical Engineering, University of California, Berkeley, 1986 Chiang's research interests focus on nonlinear system theory , power system stability and control , nonlinear optimization , and their applications to modern power grids with high penetration of inverter-based resources. He is renowned for developing the BCU method and TRUST-TECH methodology , which have enabled fast direct stability assessment and global optimization in complex systems. His work bridges fundamental theory with industrial deployment through his companies, Bigwood Systems, Inc. and Global Optimal Technology, Inc. His recent publications (2024–2025) reflect a strong trend toward integrating machine learning and deep neural networks with power system analysis , particularly in state estimation, optimal power flow, and voltage control. There is a clear emphasis on handling uncertainty, non-convexity, and multi-scale dynamics in active distribution networks and integrated energy systems . His work increasingly focuses on resilience , real-time control , and user-centered methodologies for modern grid operations. Chiang has received numerous scientific honors, including: IEEE Fellow (1997) United States Presidential Young Investigator Award (1989) Multiple DOE Grid Optimization Challenge Awards (2020–2023) Best Paper Awards from IEEE Transactions and Conferences Outstanding Education Award, Cornell University (1990) He has successfully managed over 100 research projects and holds 28 U.S. and international patents. As the founder of Bigwood Systems, Inc., he has commercialized advanced software for utility companies across the U.S. and Japan. His team has published over 480 refereed papers and received more than 17,500 citations. He advises a large research group and leads innovations in computational methods for energy systems. His lab is actively involved in developing next-generation tools for grid security, optimization, and machine learning integration.

Stefan Goldمشاهده پروفایل

استاد

• Sustainability Management
• Social Dimension of Sustainability
• Modern Slavery
• +۶ مورد دیگر

Prof. Stefan Gold is a Professor of Sustainability Management at TUM Campus Straubing, leading the Chair of Sustainability Management. His research focuses on the social dimensions of sustainability, including modern slavery, diversity, and inclusive operations. He previously held roles at the University of Kassel (2017–2025) and the University of Nottingham (2014–2016). His work integrates interdisciplinary approaches to address systemic challenges in supply chains and humanitarian aid. Notable awards include recognition in the research.com rankings and the Financial Times Responsible Business Education Award. Education: PhD in Cultural Economics (University of Kassel, 2011), Postdoc at University of Neuchâtel (2011–2014), Studies in Cultural Economics at University of Passau (1997–2003). His research emphasizes actionable solutions for social sustainability, such as combating modern slavery through policy integration and advancing circular economy frameworks. Recent projects include agent-based modeling of labor standards diffusion and multi-method interventions targeting exploitation hotspots. Key publications span topics like supply chain ethics, humanitarian logistics, and DEI in operations. His work bridges academic rigor with real-world impact, influencing policy and corporate practices.

• Optimal Control
• Aerospace Engineering
• Robotics
• +۳ مورد دیگر

Ran Dai is a Professor in the Department of Aeronautics and Astronautics at Purdue University's College of Engineering. His research focuses on optimal control theory, trajectory optimization, and robotics applications, with an emphasis on aerospace systems and energy-efficient solutions. He leads the Autonomous Optimization Lab (AOL) and has contributed extensively to advancements in learning-based control, mixed-integer programming, and deployable space systems. His work spans applications such as spacecraft guidance, unmanned vehicle path planning, and energy management for solar-powered systems. Notable contributions include algorithms for fuel-optimal powered descent, real-time trajectory optimization, and origami-inspired deployable mechanisms. He holds a Ph.D. in Aerospace Engineering and has published over 100 peer-reviewed articles. Research interests include: Optimal control and trajectory optimization Reinforcement learning for decision-making Autonomous systems and robotics Energy-efficient aerospace engineering Recent work emphasizes meta-reinforcement learning frameworks and adaptive optimization engines for complex systems.

• Operations Research
• Optimization
• Dynamic Programming
• +۶ مورد دیگر

Peng Sun is the J.B. Fuqua Professor of Decision Sciences at Duke University's Fuqua School of Business. His research focuses on mathematical models for resource allocation under uncertainty, dynamic mechanism design, and incentive structures in operations, finance, healthcare, and sustainability contexts. He holds editorial roles at top journals including Management Science and Operations Research . Dr. Sun earned his Ph.D. in Operations Research from MIT in 2003. His teaching includes MBA core courses on decision models and strategic dynamics, as well as PhD courses on dynamic programming. His work bridges theory and application across sectors like healthcare policy, renewable energy, and pandemic control. Key research areas include: Dynamic contracts and incentive design Optimization under uncertainty Healthcare resource allocation Sustainability policy modeling Recent research explores topics like optimal drug approval mechanisms, epidemic control strategies through information design, and dynamic pricing in service systems. His work frequently appears in leading journals and addresses real-world challenges in public policy and business operations.

• Supply Chain Risk Management
• Blockchain Technology
• Sustainability & Environmental Initiatives
• +۶ مورد دیگر

Srinivas (Sri) Talluri is the John Hoagland - Richard Metzler Professor in Purchasing and Supply Management at the Department of Supply Chain Management, Michigan State University (Broad College of Business). He holds the title of DSI Fellow and served as the faculty director of the Axia Institute, focusing on advancing supply chain research and education. His work emphasizes supply chain resilience, risk management, and sustainability through innovative applications of blockchain, generative AI, and quantum computing. Dr. Talluri's research spans demand-supply uncertainty modeling, sustainable supply chain design, and strategic sourcing. Notable contributions include frameworks for blockchain integration in logistics, eco-efficient vaccine distribution during pandemics, and data-driven optimization for remanufacturing systems. His work frequently addresses macroeconomic disruptions, geopolitical risks, and environmental compliance under carbon tax schemes. His scholarly recognition includes the Fulbright-Hanken Distinguished Chair (2016-2017) and top 100 Operations Management scholar rankings. His research has been published in leading journals such as International Journal of Production Research and IEEE Transactions on Engineering Management . Key Professional Contributions: Over 140 peer-reviewed articles, leadership in supply chain education, and industry collaborations addressing global supply chain challenges. Labs/Initiatives: Active in the Axia Institute, focusing on supply chain innovation and policy.