Find Academic Supervisors

Sherilyn Williams-StroudView profile

Professor

• Induced Seismicity
• Subsurface Storage
• Fracture Analysis and Modeling
• +4 more

Sherilyn Williams-Stroud is the Director of the Berg-Hughes Center and holds the Dan A. Hughes '51 Chair in Geosciences at Texas A&M University. She is a Professor in the Department of Geosciences, with over 30 years of expertise in structural geology, subsurface storage, and induced seismicity. Her research focuses on fracture analysis, geomechanics, and the societal impacts of energy resource utilization, particularly in carbon capture and storage (CCUS) and renewable energy transition. Education: BA in Geology from Oberlin College (198?), MA and PhD in Structural Geology from Johns Hopkins University (199?). Research interests include induced seismicity from fluid injection, subsurface tomographic imaging, and the integration of machine learning for improved subsurface modeling. Her work addresses critical challenges in energy resource management and environmental sustainability, with a focus on CO2 sequestration and geothermal energy. Publications highlight advancements in microseismic monitoring, fracture network modeling, and geomechanical analysis of CO2 injection sites. Her contributions span academic, industrial, and governmental sectors, including roles at the USGS, Chevron, and MicroSeismic Inc. Awards: AAPG Distinguished Lecturer (2023–2024), AAPG Honorary Member (2022), USGS Star Award (1997). Professional Leadership: Member of the National Petroleum Council’s Natural Gas GHG Study Committee, National Academy of Sciences’ Geodynamics Committee, and American Rock Mechanics Association’s Discrete Fracture Network Technical Committee. Her advisory and collaborative work bridges academia and industry, with a focus on mitigating risks in subsurface energy projects while advancing sustainable practices.

• Quality Inspection and Control
• Predictive Modeling
• Smart Manufacturing Systems
• +3 more

Dr. Yu (Chelsea) Jin is an Assistant Professor in the Department of Industrial Engineering at the University at Buffalo, specializing in quality inspection, predictive modeling, and data analytics for advanced manufacturing systems. She holds a PhD in Industrial Engineering from the University of Arkansas, an ME from the University of Michigan, and dual BS degrees in Network Engineering and Finance from Jinan University. Her research focuses on integrating machine learning and physics-based models to optimize manufacturing processes, such as additive manufacturing, PCB assembly, and pharmaceutical distribution systems. She has developed frameworks like ReflowNet for reflow oven optimization and physics-informed neural networks for thermal profile prediction. Her work emphasizes both theoretical advancements and practical applications in smart manufacturing and healthcare logistics. Dr. Jin's recent publications highlight contributions to generative AI for knowledge retrieval, AGV system optimization, and multi-source transfer learning for pandemic modeling. She actively collaborates with industry partners to bridge academic research and real-world manufacturing challenges.

Vanessa MagnanimoView profile

Professor

• Discrete Element Method (DEM)
• Soil Micromechanics
• Granular Materials
• +4 more

Vanessa Magnanimo is a Full Professor at the MESA+ Institute, University of Twente, specializing in the micromechanics of granular materials and clays using advanced Discrete Element Method (DEM) simulations . Her research bridges micro- and macro-scale behavior of soils, focusing on computational modeling , small-strain stiffness , and material stabilization . She has led 107 research outputs and 2 datasets , including studies on wet granular systems , bio-cemented soils , and vegetated soil mechanics . Recent work includes 2025 publications on coarse-grained DEM and mixing indices in industrial processes. Notable activities include keynote talks at international events (2018–2020), visiting researcher appointments at institutions like 3SR Laboratory (2017) and Politecnico di Bari (2020), and editorial contributions. Her research spans geotechnical engineering , powder technology , and multi-scale modeling , with applications in soil stabilization , industrial powder handling , and eco-mechanical systems .

• Artificial Intelligence in Manufacturing
• Production Engineering
• Circular Economy in Manufacturing
• +4 more

Dr. Amon Göppert serves as Professor and Chair of the Intelligence in Quality Sensing group at RWTH Aachen University's Laboratory for Machine Tools and Production Engineering (WZL). His work integrates artificial intelligence into manufacturing processes to enhance quality control, production efficiency, and sustainable practices. Göppert's research spans intelligent manufacturing systems with core expertise in AI-driven production engineering, circular economy applications, and advanced assembly systems. He investigates how machine learning optimizes production ramp-up, disassembly processes, and flexible manufacturing while developing sensor-based quality control solutions for industrial applications. His recent publications reveal strong trends toward AI implementation in production planning, with emphasis on worker assistance systems for disassembly, digital twin applications for real-time control, and mobile robotics in line-less assembly environments. Key focus areas include sustainable manufacturing, metrology innovation, and adaptive scheduling systems. Göppert leads multiple high-impact research initiatives: AI-driven Product Development: Machine learning for smart measurement strategies in metrology MetaVision Consortium: Industrial metaverse applications for AI-supported vision systems Generative AI for Non-Destructive Testing optimization Cluster of Excellence Internet of Production participation As Chief Engineer at WZL, he oversees technical implementation of research projects and collaborates with industry partners to translate innovations into practical manufacturing solutions, particularly in adaptive assembly systems and quality sensing technologies.

• Manufacturing Engineering
• Systems Engineering
• Simulation Modeling
• +4 more

Bruno Vallespir is a Professor at Universite de Bordeaux, affiliated with the Production Engineering research group and MEI team. His work focuses on lean manufacturing, industry 4.0 integration, and enterprise interoperability using simulation frameworks. Key research themes: Lean techniques evaluation Co-simulation for manufacturing systems Organizational interoperability Safe work activity design His recent publications address: Combining lean methods with Industry 4.0 technologies Human-machine interaction in production environments Verification of collaborative processes Performance metrics for dynamic industrial contexts Collaborations include institutions like IMS Bordeaux , INCOSE , and industrial partners such as STMicroelectronics , Thales , and Stellantis .

Giorgio ScorzelliView profile

Researcher

• Extreme Data Management
• Scientific Visualization
• Computational Topology
• +6 more

Giorgio Scorzelli is a researcher at the University of Utah, serving as Director of Software Development for the Center for Extreme Data Management, Analysis, and Visualization (CEDMAV) and the National Science Data Fabric (NSDF) . He specializes in extreme data management, scientific visualization, and computational topology, with a focus on scalable solutions for climate science, materials science, and neuroscience datasets. His work emphasizes democratizing data access through platforms like OpenVisus , enabling efficient analysis of petascale and exascale data. Key contributions include orchestrating cyberinfrastructure, optimizing parallel I/O, and developing real-time visualization systems for heterogeneous resources. Notable scientific contributions include the NSF Grant #2127548 for NSDF development . His projects integrate cloud computing, geo-distributed storage, and FAIR digital objects to lower barriers to data democratization. Giorgio's research spans multi-resolution algorithms , computational topology , and 3D geometric modeling , with applications in infrastructure security, archaeological reconstruction, and biomedical imaging. His work bridges abstract mathematical frameworks (e.g., Boolean algebras, chain complexes) with practical software solutions.

Gérard BerryView profile

Professor

• Computer Science
• Lambda Calculus
• Functional Programming
• +5 more

Gérard Berry (born December 25, 1948) is a distinguished French computer scientist currently serving as Professor at the Collège de France, holding the permanent chair Algorithmes, machines et langages (Algorithms, Machines, and Languages) since 2012. He previously held the Informatique et sciences numériques chair (2009-2010) and the Technological Innovation Liliane Bettencourt chair (2007-2008) at the same institution. Before joining Collège de France full-time, he served as Director of Research at INRIA Sophia Antipolis (2009-2012) and at École des Mines de Paris (1977-2001). His research spans over 30 years in three main fields: lambda calculus and functional programming, parallel and real-time programming languages, and design automation for synchronous digital circuits. He is particularly renowned for developing the Esterel programming language. His work bridges theoretical computer science with practical industrial applications. Berry's research has evolved to include current work in Hop and HipHop for Web programming, formal verification of compilers, and languages for computer music. His publications demonstrate consistent contributions to programming language theory, formal methods, and their applications in hardware and software systems. Gold Medal of CNRS (2014) Chevalier de l'Ordre de la Légion d'Honneur (2012) Member of French Academy of Sciences (2002) Member of Academia Europaea (1993) Monpetit Prize of Académie des sciences (1990) Berry has advised 17 PhD students and reviewed numerous theses. His industrial experience includes serving as Chief Scientist Officer of Esterel Technologies (2000-2009), where he directed the implementation of the Esterel v7 compiler. He has also held significant leadership roles including President of the Scientific Council of IRCAM and membership on the Scientific Council of the National Education. His teaching at Collège de France has covered topics ranging from the foundations of computation to the societal impact of digital technology, with courses including The Informatics of Time and Events and Proving Programs: Why? When? How? His laboratory work has focused on developing practical applications of theoretical computer science concepts.

Onur UlgenView profile

Professor

• Industrial Engineering
• Discrete-Event Simulation
• Manufacturing Systems
• +5 more

Onur Ulgen is a Professor in the Industrial and Manufacturing Systems Engineering department at the University of Michigan-Dearborn , where he has held positions since at least 2011. His work focuses on applying simulation techniques to solve complex problems in manufacturing and industrial systems. Education Ph.D., Industrial Engineering , Texas Technological University M.S., Industrial Engineering , Texas Technological University B.S., Mechanical Engineering , Robert College Research Interests Professor Ulgen specializes in Discrete-Event Simulation (DES) applications across multiple domains. His work addresses Automotive Manufacturing challenges like assembly line optimization, selectivity bank modeling, and deadlock prevention. He also investigates Steel and Metal Manufacturing systems, high-speed production lines, and Medical Logistics resource allocation. Key subfields include production scheduling, software selection for industrial simulation, and integrated systems modeling. Recent Article Trends His publications from 2015 to 2007 demonstrate a sustained focus on simulation for Automotive , Aerospace , and Healthcare industries. Topics include capacity planning, material handling optimization, and simulation-based design validation. Specific methodologies emphasize discrete-event simulation , throughput analysis , and deadlock prevention in complex systems. Grants and Projects Ford Motor Company (2011-2012): Modeling selectivity buffers for conflicting constraints in vehicle assembly SAP America, Inc. (2000): Nonlinear demand forecasting and inventory management uncertainty SME Education Foundation (1996-1997): Manufacturing engineering support

Suchi RajendranView profile

Assistant Professor

• Prescriptive Analytics
• Predictive Analytics
• Applied Operations Research
• +10 more

Suchi Rajendran is an Assistant Professor with a joint appointment in the Department of Industrial and Systems Engineering and the Department of Marketing at the University of Missouri, Trulaske College of Business. She is also the Director of Undergraduate Studies in ISE and actively leads research in prescriptive analytics, operations research, and data-driven decision-making across healthcare, transportation, and business systems. Education: PhD in Industrial Engineering, Pennsylvania State University Her research focuses on applying advanced analytics to solve complex real-world problems. Key areas include optimizing healthcare delivery systems, supply chain and logistics (notably blood supply chains and port operations), marketing data analytics, and emerging transportation systems such as air taxis and electric vehicle infrastructure. She leverages predictive and prescriptive artificial intelligence to forecast demand and recommend optimal operational strategies. Her recent work, highlighted in university news up to 2025, demonstrates a strong trend toward interdisciplinary, AI-powered solutions in logistics, sustainability, and public service. She frequently collaborates with industry partners like Case New Holland and Schneider Electric, and has secured funding from agencies such as the Alaska Department of Transportation and the National Science Foundation. Scientific Awards and Recognitions: Richard Wallace Faculty Incentive Grant Bob Bloss Faculty Enhancement Grant Winemiller Excellence Award in Data Analytics NSF CHOT Scholar (Penn State) Service Enterprise Engineering Fellow DAAD-WISE Fellowship (Germany) Lean Six Sigma Black Belt Dr. Rajendran is actively involved in mentoring students, having advised honors-winning graduate and undergraduate researchers. She leads an NSF-funded Research Experiences for Undergraduates (REU) program that brings 10 students annually to Mizzou to work on AI-enabled operations engineering. Her grants support hands-on, interdisciplinary research that prepares the next generation of engineers and data scientists. She is affiliated with cutting-edge research initiatives involving simulation modeling, digital communication platforms, and AI integration in industrial systems. Her lab and team focus on developing practical, scalable solutions for logistics, healthcare, and sustainable transportation, often through collaborative, real-world projects with public and private stakeholders.

Mark HeinrichView profile

Associate Professor

• Parallel Computer Architecture
• Heterogeneous Architectures
• Active Memory and I/O Systems
• +4 more

Mark Heinrich is an Associate Professor in the Department of Computer Science at the University of Central Florida (UCF), where he also serves as Undergraduate Coordinator for CS and IT, and Senior Design Coordinator. He previously held roles at Cornell University and has industry experience co-founding companies like Phanfare and Flashbase. His research focuses on parallel computer architecture, heterogeneous systems, cache coherence protocols, and multiprocessor simulation. Heinrich holds a Ph.D. in Electrical Engineering from Stanford University (1998) under John Hennessy, and a B.S. in Electrical Engineering and Computer Science from Duke University (1991). Research Interests His work spans parallel architectures, active memory systems, scalable cache coherence protocols, and hardware/software co-design. Recent efforts include innovations in persistent memory technologies and multiprocessor simulation methodologies. Teaching In Spring 2020, he taught CS Senior Design I and II courses (COP 4934/4935), with office hours focused on senior design and undergraduate coordination. Professional Background Associate Professor at UCF since 2003 Past roles: Director of UCF's School of Computer Science (2005), Associate Director of EECS (2005-2007) Co-founder of the Cornell Computer Systems Laboratory Contributed to the FLASH multiprocessor architecture and its simulation tools Labs & Projects He has been involved in projects like Active Memory Clusters and architectural support for multiprocessor systems. His work often bridges theoretical computer architecture with practical hardware implementations.

Ayan MukhopadhyayView profile

Researcher

• Multi-Agent Systems
• Cyber-Physical Systems
• Smart Cities
• +5 more

Dr. Ayan Mukhopadhyay serves as a Senior Research Scientist in the Department of Electrical Engineering and Computer Science at Vanderbilt University's School of Engineering. Previously, he was a Post-Doctoral Research Fellow at Stanford Intelligent Systems Lab where he received the 2019 CARS post-doctoral fellowship. His academic journey includes a Ph.D. from Vanderbilt University's Computational Economics Research Lab with a doctoral thesis nominated for the Victor Lesser Distinguished Dissertation Award 2020. His research spans critical domains in smart infrastructure systems with particular focus on: Developing robust decision-making frameworks for cyber-physical systems under uncertainty Creating multi-agent solutions for emergency response optimization Designing machine learning approaches for urban mobility and energy management Building proactive incident detection pipelines using heterogeneous data sources Analysis of his recent publications reveals strong thematic continuity in applying artificial intelligence to real-world infrastructure challenges, particularly in transportation systems, emergency response, and energy management. His work consistently bridges theoretical AI advances with practical implementation in smart city contexts, demonstrating expertise in both algorithmic innovation and systems integration. Award highlights include: CARS Post-Doctoral Fellowship (2019) Best Paper Award at ICLR's AI for Social Good Workshop Victor Lesser Distinguished Dissertation Award Nomination (2020) Dr. Mukhopadhyay leads significant research initiatives through ScopeLab, focusing on creating deployable solutions for public transit, emergency response, and energy systems. His work on vehicle-to-building charging, traffic incident localization, and equitable transit network design demonstrates commitment to solving high-impact urban challenges through rigorous computational methods. Current projects involve developing simulation environments for non-stationary environments (NS-Gym) and explainable planning frameworks integrating formal logic with large language models.

Matthias BeckerView profile

Professor

• Human-Computer Interaction
• Simulation and Modeling
• Distributed Systems
• +6 more

Matthias Becker is a Professor at the Institute for Practical Computer Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover, where he has been a core member of the Human-Computer Interaction group since 2019. He serves as Internship Coordinator for Computer Science and Computer Engineering and holds key roles in the Computer Science Examination Board and Selection Committee, actively shaping academic governance and student development. His academic journey began with PhD studies at the University of Bremen (1996-2000) supported by a DFG grant, followed by a postdoctoral permanent position at Leibniz University Hannover (2000-2019), an Associated Assistant Professor role at École des Mines de Nantes (2000), and a Habilitation in Computer Science in 2013. This foundation enabled his transition to a full professorship in 2019. Becker's research spans Human-Computer Interaction, Simulation and Modeling, and Bio-inspired Computing, with applications in agriculture, renewable energy, and manufacturing. His work integrates distributed systems, optimization algorithms, and wireless sensor networks to solve complex real-world problems, such as greenhouse monitoring, wind farm logistics, and tire noise reduction. Recent publications reveal a strategic focus on practical validation of simulation models and cross-domain applications of nature-inspired algorithms. His 15 most recent publications (2018-2024) demonstrate consistent innovation in applying simulation techniques to offshore wind farm installation, agricultural pest management, and sports science. These works emphasize real-world validation, collaborative problem-solving, and the development of domain-specific optimization frameworks that bridge theoretical algorithms and industrial implementation. As Internship Coordinator, Becker facilitates critical industry-academia connections for students, while his examination board responsibilities ensure rigorous academic standards. His leadership in the Human-Computer Interaction group drives research on interactive systems for agriculture, energy, and health, with particular emphasis on user-centered design in complex operational environments like wind farm logistics and greenhouse automation.

Halit UsterView profile

Professor

• Operations Research
• Network Optimization
• Logistics
• +7 more

Halit Uster is Professor of Operations Research & Engineering Management at SMU’s Lyle School of Engineering and Professor of Civil & Environmental Engineering (by courtesy). A 2025 IISE Fellow, he also serves as Fellow of SMU’s Hunt Institute for Engineering and Humanity, where he leads large-scale optimization research with strong societal impact. Education Ph.D. in Management Science/Systems – McMaster University, Canada M.A. in Business Administration (Production/Operations Management) – Hacettepe University, Turkey B.S. in Mechanical Engineering – Middle East Technical University, Turkey Research Interests Uster develops optimization models and efficient algorithms for the design and analysis of networked systems. His work spans: Electric-vehicle charging and wireless power-transfer networks Emergency logistics and disaster-preparedness planning Bio-energy and biomass supply-chain networks Closed-loop supply chains with recycling and remanufacturing Relay and multi-commodity transportation networks to mitigate driver shortages Wireless sensor networks for environmental monitoring Publication Trends Over the past decade Uster has published extensively in Transportation Science , IISE Transactions , Transportation Research Part E , and Annals of Operations Research . His recent articles collectively advance decomposition-based exact algorithms (notably Lagrangean and Benders schemes), bilevel and robust optimization, and stochastic modeling of supply and demand uncertainty, all applied to socially critical infrastructure systems. Scientific Awards & Honors IISE Fellow (2025) Caterpillar Teaching Excellence Award, Texas A&M University (2011) Eshbach Society Distinguished Visiting Scholar, Northwestern University (2009) Faculty Appreciation Awards, INFORMS Student Chapters (2004, 2009) Multiple research features in IE Magazine (2008, 2010, 2017) Daniel H. Wagner Prize Finalist (2008) Moving Spirit Award, INFORMS (2007) Outstanding Faculty Member – University of Alabama (1999-2000) NSERC Postgraduate Scholarship (1997-1999) Grants & Doctoral Advising Uster has secured over $2 million in funding from NSF, USDA and industry, including four NSF grants since 2015 focused on disaster-preparedness logistics, EV-charging infrastructure, and biomass supply chains. He has graduated 17 PhD students who now hold positions in academia (IIM Udaipur, ITESM Mexico, St. Mary’s University) and industry (ExxonMobil, Norfolk Southern, FedEx, Sabre, NetJets, JD.com, BNSF Railway, etc.). Professional Service & Editorial Roles He is Department Editor of IISE Transactions on Supply Chains and Logistics (2024–present) and Associate Editor of Transportation Science (2018–present), previously serving on the editorial boards of IISE Transactions on Scheduling and Logistics and Sustainability Analytics and Modelling . He has chaired or co-chaired numerous INFORMS committees and conferences, including the upcoming TSL 2026 meeting at MIT.

Angelina AnaniView profile

Associate Professor

• Mining Systems Optimization
• Mine Planning and Production Scheduling
• Sustainable Mining Systems
• +12 more

Dr. Angelina Anani is an Associate Professor in the Department of Mining & Geological Engineering at the University of Arizona, College of Engineering. She is also a member of the Graduate Faculty and actively contributes to research and teaching in mining systems optimization, mine planning, and sustainable mining practices. Education: PhD in Mining Engineering, Missouri University of Science and Technology, Rolla, Missouri, United States BS in Mining Engineering (Summa cum laude), Missouri University of Science and Technology, Rolla, Missouri, United States Research Interests: Dr. Anani's research spans a broad spectrum of mining engineering challenges, focusing on modeling and optimization of mining systems , mine planning and production scheduling , and sustainable mining system design . She investigates mine equipment reliability , tunneling and underground works , and energy and water efficiency . A significant portion of her recent work integrates machine learning and data-driven approaches into mine safety and planning, including 3D/4D/VR applications and digital twin systems . Her interdisciplinary approach also includes ethnographic research in mining communities and supply chain management in the mining sector. Publications Trends: Her recent publications reflect a strong shift toward intelligent systems in mining, with increasing focus on machine learning for safety, process mining for maintenance, and digital twin deployment. She combines traditional optimization techniques like discrete event simulation with modern AI to solve complex mining challenges, particularly in underground and transition mines. Scientific Awards: Freeport-McMoRan, Inc. Career Development Grant Society for Mining, Metallurgy and Exploration, Fall 2022 Faculty Core Advising and Grants: Dr. Anani supervises graduate research through MNE 900 (Research), MNE 910 (Thesis), and MNE 920 (Dissertation) courses. She has secured external funding such as the Freeport-McMoRan Career Development Grant, supporting her innovative work in mine optimization and safety. While current students are not listed, her active supervision load indicates ongoing mentorship of master’s and PhD candidates. Labs and Teams: She is actively involved with the San Xavier Underground Mine Laboratory, where she contributes to monitoring systems and digital twin development. Her collaborative work with researchers from Chile and Ghana highlights her international engagement. She is also affiliated with professional societies including the Society of Mining, Metallurgy and Exploration (SME), Society of Mining Professors, and Women in Mining (WIM), contributing to both technical and diversity initiatives in the field.

• Construction Engineering
• Simulation Science
• Information Technology in Construction
• +3 more

Simaan Abourizk, PhD, PEng, is the Dean of the Faculty of Engineering at the University of Alberta and holds the rank of Professor in Construction Engineering and Management. He also served as the NSERC/Alberta Construction Industry Research Chair (1997–2011) and Canada Research Chair in Operations Simulation (2001–2008). His roles include Executive Board membership at the Construction Research Institute of Canada. Education: Doctor of Philosophy in Construction Engineering and Management from Purdue University (1990), Master of Science and Bachelor of Civil Engineering (Honors) from Georgia Institute of Technology (1985 and 1984). Research focuses on advancing simulation technologies for construction and natural resource industries, including: Development of the Simphony simulation environment and COSYE framework Integration of AI, visualization, and scheduling tools (e.g., SmartEst, MTRACK) Optimization of tunneling, modular assembly, and industrial fabrication processes Key awards include the E. Whitman Wright Award (2002), E.W.R. Steacie Memorial Fellowship (2001), and Walter Shanly Award (2001). Current projects emphasize synthetic environments, safety analytics, and data-driven decision support systems in construction. He leads initiatives on risk simulation, resource allocation, and industrial automation.