Simon Caillard is a teacher-researcher at CESI Campus Lingolsheim , specializing in operational research and artificial intelligence applications for healthcare systems. His work focuses on resource planning, scheduling optimization, and sustainable logistics solutions. Develops algorithms for healthcare simulation center management Researches shared mobility systems and renewable energy integration Supervises doctoral theses in dynamic scheduling and green logistics Recent publications demonstrate expertise in constraint optimization, variable neighborhood search, and ant colony algorithms applied to health training environments. Contact: Email: scaillard@cesi.fr Phone: +33 6 42 12 41 87 Address: Pars des Tanneries, 2 Allée des Foulons, 67380 Lingolsheim
Edilson Arruda is an Associate Professor in the Department of Decision Analytics and Risk at the University of Southampton's Southampton Business School. His academic career spans Electrical Engineering with specialization in Operational Research and Optimal Control, focusing on interdisciplinary applications at the intersection of artificial intelligence, operations research, and management science. His educational background includes a BSc in Electrical Engineering from the Federal University of Mato Grosso (Brazil), followed by MSc and DSc in Electrical Engineering (Operational Research/Optimal Control) from the University of Campinas. Prior academic appointments include Lecturing/Senior Lecturing positions at the Pontifical Catholic University of Rio Grande do Sul and the Federal University of Rio de Janeiro, plus postdoctoral work at the National Laboratory for Scientific Computation (Brazil) and Cardiff University. Arruda's research centers on optimization under uncertainty using Markov decision processes and stochastic modeling, with significant applications in healthcare resource management, logistics, and supply chain analytics. His work addresses critical challenges such as hospital bed allocation, surgical scheduling for military healthcare, epidemic control, and offshore infrastructure management. He leads the FORecasting Turbulence in Hospitals (FORTH) project and has contributed to mass casualty response modeling for blast events. His publications reveal a strong trend toward healthcare applications of stochastic optimization, particularly in resource-constrained environments. Approximately 60% of his recent work focuses on healthcare modeling, while 30% addresses logistics and supply chain challenges, and 10% explores fundamental methodological advances in Markov decision processes and optimization theory. As an educator, Arruda teaches advanced modules including Markov Decision Processes, Probabilistic Methods in Operational Research, and Foundations of Business Analytics. He actively supervises PhD students across disciplines including Management, Mathematical Sciences, and Human Development. He maintains significant external engagement as Chair at Kerala University of Digital Sciences (2022) and as a speaker on patient pathway modeling (2023). His research is conducted through multiple centers including the Institute for Life Sciences, CORMSIS (Centre for Operational Research, Management Science and Information Systems), and the Centre for Healthcare Analytics.
Volodymyr Kindratenko is a Research Associate Professor at the University of Illinois at Urbana-Champaign and Assistant Director for the Center for Artificial Intelligence Innovation (CAII) at the National Center for Supercomputing Applications (NCSA) . He also holds an Adjunct Associate Professor appointment in the Department of Electrical and Computer Engineering . His academic background includes a D.Sc. in Analytical Chemistry (University of Antwerp, 1997) and an M.Sc. in Mathematics and Informatics (Volodymyr Vynnychenko Central Ukrainian State University, 1993). Dr. Kindratenko's research focuses on High-performance computing (HPC) with computational accelerators Special-purpose computing architectures AI and machine learning systems for scientific applications Cloud computing integration with HPC Transformer-based models for medical imaging Federated learning on heterogeneous resources His work has been funded by NSF, NASA, ONR, DOE, and industry partners. The 15 most recent publications span AI-driven cosmological data analysis, cloud-HPC integration, and GPU-accelerated quantum simulations. Keywords include Machine Learning , High-performance computing , Quantum Chromodynamics , and Cloud Computing , with subfields like Transformers for medical imaging , Federated learning , and GPU clusters . Scientific awards include SRC Award for Excellence in Reconfigurable Computing (2007) Instructure Academic Excellence Award (2025) Outstanding Service Award at the 9th ACS/IEEE Conference (2011) George Anner Excellence in Teaching Award (2022) He serves as department editor of IEEE Computing in Science and Engineering and associate editor of International Journal of Reconfigurable Computing , and mentors students in the SC Student Cluster Competition (2016-2021). Dr. Kindratenko is a Senior Member of IEEE and ACM .
Suresh Chand is a Professor and the Louis A. Weil Jr. Chair of Management at the Daniels School of Business, Purdue University . He serves as Department Head of Supply Chain and Operations Management. Ph.D., Industrial Administration, Carnegie Mellon (1979) M.S., Industrial Engineering, University of Texas (1976) M. Tech. & B. Tech., Mechanical Engineering, IIT Kanpur (1974, 1972) His research focuses on production process optimization across manufacturing and healthcare sectors. Key areas include: Capacity and production planning for volume flexibility Supply chain modeling to align supply with demand Reduction of patient flow time in healthcare systems Learning/forgetting effects in scheduling and setups Statistical process control and inventory management Professor Chand has published over 50 articles in Operations Research , Management Science , and similar journals. His work spans theoretical advancements in lot sizing, scheduling algorithms, and practical applications in healthcare and global supply chains. He has served as Associate Editor for Management Science (1986-2008), Area Editor for Production and Operations Management (1992-2003), and Senior Editor for Manufacturing and Service Operations Management (1999-2004). He was General Chair for the POM 2005 international conference. Professor Chand teaches core and elective courses in Operations Management to MBA, undergraduate, and doctoral students. He has taught at Purdue's Hannover campus and led Summer Study Abroad programs at TVS Motors in India.
Edoardo Fadda is a Fixed-term tenure-track Assistant Professor at the Department of Mathematical Sciences (DISMA), Politecnico di Torino . He serves as a member of the College of Mathematical Engineering and College of Electronic, Telecommunications and Physics Engineering . Specializes in Operations Research and Mathematical Programming Active in stochastic optimization , reinforcement learning , and control applications Teaching roles include Optimization Methods for Control Applications and Stochastic Programming courses His research spans supply chain optimization , logistics , and AI-integrated decision systems , focusing on uncertainty modeling and multi-stage stochastic programming. He leads the Development of Decision Support Systems and the SUPERSONIC project for ecological logistics, alongside commercial consulting for RIDIX SPA through Fondimpresa contracts. Notable collaborations include Paolo Brandimarte and Francesca Maggioni . Edoardo supervises PhD candidates Alessia De Crescenzo (39th cycle) and Lorenzo Mazza (40th cycle). His publications emphasize stochastic customer behavior , perishable product policies , and kernel-based system identification , with applications in aerospace, smart cities, and industrial manufacturing.
Florian Christian Holzinger is a Researcher at the University of Applied Sciences Upper Austria, Campus Hagenberg, specializing in predictive maintenance and industrial optimization. He is affiliated with the Center of Excellence for Smart Production and the HEAL Produktion und Operations Management department. His research focuses on Predictive Maintenance (83%) , Machine Learning , and Multi-criteria Optimization with applications in radial fan systems and manufacturing. Key research areas include sensor-based health prediction, concept drift detection, and data acquisition systems for industrial applications. His publication trends show consistent output in computer-aided systems theory with emphasis on EUROCAST conference proceedings. Recent work (2023-2025) explores constraint-based regression methods, composable evolutionary computation, and workflow optimization in manufacturing. Dr. Holzinger has participated in multiple research projects including DigiVent (2017-2020) for predictive maintenance of industrial radial fans and FlashCheck (2017-2020) for arc detection in DC networks using compressed sensing.
Wei Wang is a Senior Lecturer in Automation Engineering at the School of Engineering Science , University of Skövde . His research focuses on advanced manufacturing technologies, digital twin frameworks, and sustainable production systems. Roles: Programme Coordinator for Computational Methods in Engineering – Master's Programme Projects: QWELD (2021–2025), Energy Storage & Power Electronics (2021–2023), Intelligent Simulation-Based Planning (2019–2023) Research Interests Dr. Wang specializes in human-robot collaboration , digital twin applications , and machine learning for industrial processes . His work bridges automation, sustainability, and cybersecurity in manufacturing systems. Scientific Trends Recent publications highlight multi-objective optimization in machining processes, deformation prediction using voxel-based models, and cybersecurity integration in cyber-physical production systems. Collaborative studies emphasize laser welding and green technology adoption . Education Leadership Coordinates Computational Methods in Engineering – Master's Programme and teaches courses at both bachelor's and master's levels, including Industrial Computing Technology and Simulation-Based Optimization .
Mosharaf Chowdhury is an Associate Professor at the University of Michigan's College of Engineering, Department of Electrical Engineering and Computer Science. He leads the SymbioticLab (https://symbioticlab.org/), focusing on AI/ML systems optimization and energy-efficient computing. Current roles: Associate Professor, Director of SymbioticLab Key projects: Infiniswap (memory disaggregation), Salus (GPU sharing), FedScale (federated learning), Zeus (GPU energy optimization) Original co-creator of Apache Spark Research Interests center on large-scale systems for AI/ML and big data, with emphasis on: Energy consumption optimization Memory disaggregation via CXL GPU resource management Data privacy in distributed systems Federated learning scalability Scientific Awards include multiple paper awards from top systems venues (NSDI, OSDI, ATC, MICRO) and fellowships. Teaching includes courses like EECS 489 (Computer Networks) and EECS 598 (Systems for AI/ML).
Jim McCann is an Associate Professor at the Robotics Institute of Carnegie Mellon University. He holds a PhD from Carnegie Mellon University (2010), advised by Nancy Pollard, and has held positions at Adobe Research and Disney Research Pittsburgh. His academic journey includes postdoctoral work and industry experience in game development before joining CMU's faculty in 2017. His research focuses on creativity support tools spanning real-time systems, textiles fabrication, machine knitting, and interactive design. Key themes include: Developing compilers and interfaces for machine knitting (e.g., 3D shape knitting, knitout semantics) Building accessible fabrication tools for textiles and soft objects Creating parameterized design spaces enhanced with machine learning Advancing physics-based animation and simulation tuning His publications demonstrate strong interdisciplinarity, with recent work emphasizing textiles computing (knitting compilers, fabric 3D printing), human-AI collaboration (design adjectives), and novel interfaces (infinity mirrors, RFID systems). Earlier contributions established foundations in gradient-domain editing, fluid control, and motion synthesis. He leads the Carnegie Mellon Textiles Lab and has advised 9+ graduate students on topics ranging from knit microstructures to robot design. His teaching includes courses on Algorithmic Textiles Design, Real-Time Graphics, and Game Programming.
Thomas Kosch serves as Professor at the Institute of Computer Science within the Faculty of Mathematics and Natural Sciences at Humboldt University of Berlin. His research group Human-Computer Interaction for Scientific Software develops innovative interfaces for scientific applications, with laboratory facilities at Rudower Chaussee 25, 12489 Berlin-Adlershof and administrative correspondence via Unter den Linden 6, 10099 Berlin. His research spans Human-Computer Interaction, Virtual/Augmented Reality, Artificial Intelligence, and Neurophysiological Computing. Key interests include cognitive augmentation through EEG/EMG systems, motor learning with electrical muscle stimulation, large language model integration in UX workflows, and privacy implications of tracking technologies. His work bridges theoretical HCI frameworks with empirical validation through controlled experiments involving physiological measurements and immersive environments. Analysis of his 15 most recent publications (all 2025) reveals three dominant trends: (1) Critical examination of LLM limitations through prompt-hacking and deceptive design studies, (2) Neurophysiological validation of cognitive phenomena using multimodal sensing (EEG/eye-tracking), and (3) Application-driven XR solutions for veterinary care, navigation, and motor assessment. These works consistently employ rigorous user studies with quantitative behavioral metrics. No scientific awards are documented in the provided materials, though his publication volume in top-tier venues (e.g., CHI, UIST) indicates significant field contributions. Professor Kosch actively supervises doctoral candidates, with at least one PhD defense (Michael Piechotta, Dipl.-Bio-Inf.) scheduled for September 2025. His research group likely secures competitive grants supporting equipment-intensive projects involving EEG systems, VR setups, and physiological sensors, though specific funding sources aren't detailed. The Human-Computer Interaction for Scientific Software group operates as an interdisciplinary hub combining computer science, cognitive psychology, and domain-specific applications. Current projects involve developing open-source tools like MorphoHaptics for medical imaging, MIRAGE for fall hazard detection, and Senscon for physiological sensing integration in VR controllers.
M.Sc. Fabian Lehmann is a scientific collaborator at the Humboldt University of Berlin , affiliated with the Faculty of Mathematics and Natural Sciences and the Institute of Computer Science . His research focuses on knowledge management in bioinformatics and scientific workflows, particularly in areas like resource management, workflow scheduling, and energy-efficient computing. His recent work includes: Carbon-aware execution strategies for scientific workflows (2025) Runtime prediction techniques for heterogeneous infrastructures (2024-2022) Performance prediction and resource recommendation systems (2025-2022) Community-driven workflow standardization initiatives (2024-2022) Applications in environmental data analysis and earth observation (2023-2021) Contact: fabian.lehmann@informatik.hu-berlin.de Phone: 030 2093-41285 Address: Unter den Linden 6, 10099 Berlin
Filippo Maria Ottaviani is a Research Fellow and Teaching Assistant at Polytechnic University of Turin's Department of Management and Production Engineering (DIGEP) and Doctoral School (SCDOTT). His academic roles include visiting researcher positions at Ghent University and Universitat Politècnica de València, along with contract professorships at Università degli Studi di Genova and Università Cattolica del Sacro Cuore. Research Focus: Ottaviani specializes in integrating project management methodologies with systems engineering, particularly through: Agile software development frameworks Predictive and prescriptive analytics for project management System dynamics modeling of complex engineering systems AI applications in construction and manufacturing His work spans ERC sectors including AI, operations research, and industrial design, supporting UN SDGs for sustainable industry and economic growth. Publication analysis reveals consistent focus on: Data-driven project management techniques Risk and contingency modeling Public infrastructure financing BIM and AI integration in construction Sustainable urban development solutions Awards & Recognition: PMI Thesis and Dissertation Grant (2022) Founding partner of Project Management League (2021-present) Effective member of Project Management Institute (2019-present) Academic Service: Serves as peer reviewer for 11 journals including International Journal of Project Management and Journal of Construction Engineering. Regularly contributes as conference auditor for APMS and EURAM conferences.
Vicente Gonzalez-Moret serves as Professor and Tier 1 Canada Research Chair in Digital Lean Construction within the Faculty of Engineering's Civil and Environmental Engineering Department at the University of Alberta. Appointed in October 2022, he rapidly secured over CAN$3.9 million in research funding during his first nine months and established the Infrastructure Human Tech Lab (IHT-Lab), pioneering commercialization-focused student research. Previously, he spent over 12 years at the University of Auckland where he founded the CAD$1.0 million Smart Digital Lab and currently holds an Honorary Academic position. His educational background includes: PhD in Construction Engineering and Management (Pontificia Universidad Catolica de Chile, 2008) ME in Construction Engineering and Management (Pontificia Universidad Catolica de Chile, 2004) BE (Hons) in Construction Engineering (Universidad de Valparaiso, Chile, 1999) Gonzalez-Moret's research pioneers the Lean Construction 4.0 concept at the intersection of Construction Engineering and Management with Computer Science. His work extensively applies extended reality technologies, digital twinning, AI, BIM, and serious games to construction engineering, safety, and evacuation problems. With over CAN$64 million secured in research and teaching grants - including the largest corporate sponsorship in University of Auckland history - his research demonstrates exceptional industry impact and technological innovation. His 15 most recent publications reveal a strong focus on digital transformation in construction, with recurring themes in lean-digital integration, socio-technical systems, and practical implementation frameworks. Key areas include digital twin applications for offsite construction, ethical AI deployment, blockchain governance, and immersive VR for production planning - all advancing his foundational Lean Construction 4.0 paradigm. Scientific recognition includes: Tier 1 Canada Research Chair (2022) Editorship of the seminal 'Lean Construction 4.0' book (Routledge, 2022) Associate Editor roles (Advanced Engineering Informatics, Lean Construction Journal) Leadership in international organizations (Former General Secretary, International Group for Lean Construction) As an educator, he has supervised completion of 88 BE(Hons) projects, 7 Master's theses, 15 PhD theses, and 2 postdoctoral fellows. Currently supervising 8 PhD and 1 MSc students, he founded Alberta's first ASCE student chapter. His grant portfolio includes major industry partnerships and leadership in the Infrastructure Human Tech Lab, which develops commercially viable student research. Additional leadership roles span Lean Design and Construction Canada (Founding Board) and indigenous advocacy (Bent Arrow Board).
Haluk Topcuoglu is a Full Professor in the Department of Computer Engineering at Marmara University's Faculty of Engineering. He holds a PhD from Syracuse University (1999) and has been at Marmara University since 1999, progressing through roles as Assistant, Associate, and Full Professor. His research focuses on multicore architectures, parallel algorithms, fault tolerance, dynamic optimization, and hybrid evolutionary algorithms. He has led multiple funded projects, including TUBITAK initiatives on reliability optimization and sensor placement. Education: PhD in Computer Science (Syracuse University, 1999), MSc and BSc in Computer Engineering (Boğaziçi University, 1993 and 1991). Research Interests: Task scheduling for multicore systems, reliability-aware computing, dynamic optimization, and applications of evolutionary algorithms in cloud/fog computing. His work emphasizes balancing performance, energy efficiency, and fault tolerance in parallel systems. Awards include the 2008 IBM Faculty Award, 2010 IEEE ISDA Best Paper Award, and Marmara University's 2012 Publication Impact Award. He has supervised 4 PhD and 19 MSc theses, with ongoing research in machine learning-assisted metaheuristics and dynamic monitor selection. Editorial roles include Cluster Computing Journal (SCI-Expanded) and Journal of Aeronautics and Space Technologies. He teaches courses on evolutionary computing, multicore computing, and parallel processing. Current projects include cross-layer reliability frameworks and scheduling algorithms for fog computing, reflecting his focus on industry-relevant computational challenges.
Nicolette Krebitz is an Acting Professor for Feature Film Directing at the Academy of Media Arts Cologne (KHM), located in Cologne, Germany. She holds a position in the School of Film and Television, specifically within the Department of Feature Film. Her current role involves teaching and mentoring students in advanced film production and post-production techniques. She leads the Feature Film Exercise 2 "CAGE" seminar, focusing on post-production planning, editing, and feasibility analysis for student film projects. This course coordinates both image and sound post-production schedules for participants in the Winter Semester 2024/2025 program. Her teaching emphasizes collaborative workflows between directors and camera personnel in film production. Krebitz’s office is located at Heumarkt 14, Floor H14 Room 2.21. She can be reached via email at nicolette.krebitz@khm.de. She utilizes facilities such as the KHM’s Film Studios, Editing Suites, and Seminar Rooms (e.g., Room 1.06) for instructional purposes. No scientific awards or grants are explicitly mentioned in the provided texts. Her professional focus revolves around experiential learning in film production, with an emphasis on practical post-production methodologies.
