Production Line Optimization Professors and Supervisors | ApplySharif

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Yu XiaView profile

Researcher

Stockholm UniversitySweden

Yu Xia is a Post Doc at the Department of Chemistry, Stockholm University, Sweden. He is affiliated with the Tom Willhammar Research Group, focusing on advanced electron microscopy and diffraction techniques for structural characterization of materials. PhD (2019–2023) from a joint program between the University of Birmingham (UK) and the Southern University of Science and Technology (China). Research emphasizes fabrication of metallic nanoparticles with non-equilibrium structures and shapes using gas-phase condensation and thermal shock methods. Specializes in scanning transmission electron microscopy (STEM), in-situ heating experiments, and electron energy loss spectroscopy (EELS) for nanoparticle analysis. Current work prioritizes 4DSTEM imaging for electron beam-sensitive materials and Python-based post-processing of electron microscopy datasets. Yu Xia's research spans Materials Science , Nanotechnology , and Electrocatalysis , with applications in photocatalytic hydrogen evolution , graphene composites , and advanced electron microscopy techniques . His work often integrates computational image processing with structural characterization to optimize material properties. Publications highlight innovations in heterostructure engineering , metallic alloy catalysts , and electron beam-sensitive material imaging . No scientific awards are explicitly mentioned in the provided text. Yu Xia's technical expertise includes Python scripting for image analysis, in-situ electron microscopy , and multifunctional graphene-based materials .

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Sheng YangView profile

Assistant Professor

University of GuelphCanada

Dr. Sheng Yang is an Assistant Professor in the School of Engineering at the University of Guelph. He leads the Design Innovation and Intelligent Manufacturing (DIIM) lab, focusing on advancing additive manufacturing, generative design, and smart manufacturing technologies. His research integrates IoT, big data analytics, and bio-inspired design to address challenges in aerospace, green energy, and healthcare. Key areas include computational design for additive manufacturing, data-driven mass customization, and digital twin-based optimization. Education: Ph.D. in Mechanical Engineering from McGill University (2019), followed by a Postdoctoral Fellowship at McGill (2019–2020). Joined University of Guelph in 2020. Research interests span energy efficiency, complex system optimization, and personalized healthcare products. Recent work emphasizes digital twin synchronization in robotics, machine learning for quality prediction, and sustainable additive manufacturing processes. Notable awards include the 2019 Association of Commonwealth Universities Blue Charter Fellowship and 2018 ASME Best Paper Award. His lab actively seeks partnerships in personalized healthcare, product design, and smart manufacturing. Grants and collaborations focus on advancing manufacturing technologies and sustainability. No formal advisees listed, but active in graduate training through lab projects. The DIIM lab explores cutting-edge solutions for industrial and societal challenges through interdisciplinary approaches.

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Jonathan BonesView profile

Associate Professor

University College DublinIreland

Dr. Jonathan Bones is an Associate Professor in the School of Chemical and Bioprocess Engineering at University College Dublin (UCD) and Principal Investigator of the Characterisation and Comparability Group at NIBRT. His research focuses on analytical methods for biopharmaceuticals, including liquid chromatography-mass spectrometry (LC-MS) for protein characterization, glycomics, and process optimization. He holds a BSc and PhD in Analytical Chemistry from Dublin City University. His work has been recognized through inclusion in the Medicine Maker Power List. He leads a team of 18 researchers, supported by SFI, EI, and industry partnerships. Education: BSc in Analytical Science (Chemistry), Dublin City University PhD in Analytical Chemistry, Dublin City University Research Interests: Development of advanced LC-MS platforms for glycomics, proteomics, and bioprocess analysis. Key areas include: Quantitative proteomics/metabolomics for bioprocess monitoring Liquid phase separations for complex bioanalysis Process analytical technology (PAT) His group collaborates with ThermoFisher Scientific on analytical workflows for biopharmaceutical characterization. Articles Trends: Recent work emphasizes analytical methods for AAV vector characterization, biosimilar comparability via MAM/iMAM, and process clearance of excipients. Over 126 publications highlight his contributions to biopharmaceutical quality control and process understanding. Awards: Medicine Maker Power List (2023): Top 100 influential scientists in biopharmaceutical manufacturing and analysis Advising & Grants: Supervises PhD students in bioprocessing and analytical chemistry Funding from Science Foundation Ireland (SFI), Enterprise Ireland (EI), and EU FP7 Industry collaborations with ThermoFisher Scientific and Bristol Myers Squibb Labs & Teams: Leads the Characterisation and Comparability Lab at NIBRT, focused on cutting-edge analytical tools for bioprocess development and product quality assurance.

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Haoming LiuView profile

Associate Professor

National University of SingaporeSingapore

Assoc Prof Haoming Liu is an Associate Professor in the Department of Economics at National University of Singapore. His research focuses on applied economics, econometrics, and labor economics, with a particular emphasis on labor and demographic economics, health, education, and welfare, as well as economic development and technological change. His work often examines the intersections between environmental factors (e.g., heat, pollution) and economic outcomes, such as labor productivity, crime rates, and educational attainment. He has also contributed to studies on minimum wage policies, housing markets, and fertility-education trade-offs in developing economies. Education: PhD in Economics from the University of Western Ontario, Canada. Research highlights include analyzing the impact of heat on economic activity in tropical cities like Singapore, the effects of air pollution on labor productivity in China, and the role of discount rates in long-term housing market decisions. His teaching interests span labor economics, income distribution, and applied econometrics. Key contributions include demonstrating how heat influences workplace attendance and student performance in air-conditioned versus non-air-conditioned environments, and how minimum wage increases reduce urban crime disparities between low- and high-income communities. His articles frequently employ innovative econometric methods to address policy-relevant questions, such as optimal contest design, microgrid energy trading mechanisms, and urban density pricing in housing markets.

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Johan MeyersView profile

Professor

KU LeuvenBelgium

Johan Meyers is a full Professor at KU Leuven's Faculty of Engineering Science, Department of Mechanical Engineering, where he heads the Applied Mechanics and Energy conversion (TME) research unit. He serves as a contact person for TME and is an active member of the KIES – KU Leuven Institute for Energy and Society. His administrative roles include membership on the Council of the Faculty of Engineering Science, the Mechanical Engineering Department Council and Board, and chairing the HPC Steering Committee. Professor Meyers' research focuses on turbulent flow simulation and optimization, with particular emphasis on wind energy applications, atmospheric pollutant dispersion, and computational methods. His work spans Direct Numerical Simulation (DNS), Large-Eddy Simulation (LES), and model reduction techniques for applications in energy engineering. Current research categories include flow control & optimization, wind farm engineering, and atmospheric pollutant dispersion modeling, with specific applications in radioactive release scenarios and wind turbine system optimization. His recent publications demonstrate a strong trend toward wind energy applications, particularly in optimizing wind farm layouts and operations through advanced computational methods. The research shows significant emphasis on Large-Eddy Simulation techniques to study atmospheric boundary layer interactions with wind farms, with growing interest in hybrid wind-solar energy systems and the effects of surface temperature heterogeneity on flow patterns. His work increasingly integrates machine learning approaches to enhance computational efficiency in wind farm modeling. Professor Meyers actively supervises numerous PhD students including Bon, T., Janssens, N., Jamaer, S., and ALREWENY, A., among others. His research is supported by multiple ongoing projects through 2028, including 'Wind-farm co-design in the North-Sea basin given climate and market uncertainty' and 'Reconstruction of turbulence from partial observations,' primarily funded by research councils and industry partnerships. He leads the Turbulent Flow Simulation and Optimization (TFSO) research group, which develops efficient supercomputing simulation tools for turbulent flow applications in energy engineering. The group specializes in wind farm optimization, atmospheric pollutant dispersion modeling, and airborne wind energy systems, with a particular focus on LES studies of wind farm interactions with the atmospheric boundary layer.

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Praveen K. KopalleView profile

Professor

Dartmouth CollegeUnited States

Praveen K. Kopalle is the Signal Companies' Professor of Management, professor of marketing, and area chair at the Tuck School of Business, Dartmouth College. He served as associate dean for the MBA program (2015–18) and chairs the marketing area (2012–15, 2022–present). He teaches courses in retail pricing analytics, marketing concepts, and new product development. Education: PhD in Marketing (Columbia University, 1992), MBA (Indian Institute of Management, 1988), BE in Mechanical & Product Engineering (Osmania University, 1986) His research focuses on marketing , machine learning , artificial intelligence , pricing strategy , retail analytics , and new product innovation . Recent work addresses digital customer orientation, loyalty programs in the big data era, and predictive analytics in retailing. He has published in top journals like Journal of Consumer Research , Management Science , and Marketing Science . Praveen serves as departmental editor for Production and Operations Management and associate editor for multiple journals. He has held leadership roles in the INFORMS Society for Marketing Science and contributed to editorial boards of 10+ journals. Scientific Awards: 2018 Lifetime Achievement Award (American Marketing Association’s Retailing and Pricing Special Interest Group) 2015 Core Teaching Excellence Award (Tuck School) 2011 Distinguished Alumni Award (IIM Bangalore) Multiple John Little and Davidson Awards 2022 Distinguished Alumnus Award (Osmania University) His teaching spans MBA core courses ( Marketing , Statistics for Managers ) and electives ( Retail Pricing Strategy , Marketing New Products ). He also leads executive education programs and the Tuck Integrative Experiential Learning (TuckINTEL) initiative.

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Tamás KoltaiView profile

Professor

Budapest University of Technology and EconomicsHungary

Dr. Tamás Koltai is a Professor and Dean at the Faculty of Economics and Social Sciences of Budapest University of Technology and Economics (BME). He leads the doctoral school's Specialization Group in Production Management. His roles include overseeing academic programs and research in production management, operations research, and efficiency analysis. Education: Doctor of the Hungarian Academy of Sciences (2016) Dr. habil. (2000), Budapest University of Technology and Economics Candidate of Technical Sciences (1987), Hungarian Academy of Sciences M.Sc. in Mechanical Engineering (1983), BME Faculty of Mechanical Engineering Research Interests: Dr. Koltai focuses on production management optimization, including the application of Data Envelopment Analysis (DEA), sensitivity analysis in mathematical models, and the integration of robotics in assembly lines. His work bridges theoretical models (e.g., MILP/CP optimization) with practical industrial challenges, particularly in healthcare efficiency and educational management. Notable Awards: IEOM Society Teaching Excellence Award (2021) BME GTK Faculty Memorial Medal (2016) János Susánszki Award (2013) Széchenyi Professorship Scholarship (1999–) Teaching & Leadership: He has held visiting roles at the University of Seville (1990–1992) and the University of Michigan (1988/89). His teaching excellence is recognized through awards and his contributions to business simulation education. His research often collaborates with industry partners to address real-world operational challenges. Labs/Teams: Leads the Production Management Specialization Group and contributes to interdisciplinary teams focusing on manufacturing efficiency and healthcare operations within BME.

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Andrea BurattinView profile

Associate Professor

Technical University of DenmarkDenmark

Andrea Burattin is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark. His work bridges formal methods and practical process analysis, focusing on process mining, business process management, and hybrid modeling techniques. He actively contributes to research in healthcare process optimization, streaming data analysis, and system verification through Petri nets and CCS transformations. UN Sustainable Development Goals: Poverty eradication, environmental protection, and prosperity for all (via process optimization) Active projects: Immersive Process Mining (2024-2027), Usability and Understandability of Hybrid Process Models (2018-2021) His research explores large language model integration with process mining, proposing frameworks like Tiramisù for multi-faceted process visualization and PN2CCS for formal model translation. Recent work emphasizes real-time monitoring, conformance checking, and IoT-driven process analytics. Key trends in his publications include: 1) Streaming process mining pipelines (2022-2025); 2) LLM-plan generation frameworks (2024); 3) Formal verification techniques (Petri nets, CCS); 4) Healthcare process modeling (2019-2023); 5) Behavioral pattern analysis in process compliance. Scientific Awards Best Demo Award (2022, 2016) Best Process Mining Dissertation Award (2014) Best Workshop Paper (EDBA and PODS4H, 2023) As advisor, he supervises PhD projects on process mining and hybrid modeling. His editorial roles include Information Systems reviewer (2024-2025) and past editor for Engineering Applications of AI (2022-2023). Collaborations span Denmark, Italy, and the Netherlands.

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Christian MessierView profile

Professor

University of Quebec in Abitibi-TémiscamingueCanada

Christian Messier is a Professor at the University of Quebec in Outaouais (UQO) in the Department of Natural Sciences and at the University of Quebec in Montreal (UQAM) in the Department of Biological Sciences. He serves as Scientific Director of the Institute of Temperate Forest Sciences (ISFORT) and holds two prestigious research chairs: the Canada Research Chair on Tree Resilience to Global Changes and the NSERC/Hydro-Québec Chair on Tree Growth Control. His academic career spans over three decades since completing his Ph.D. in forest sciences from the University of British Columbia in 1991. Dr. Messier's research focuses on two primary areas: the complex functioning of managed natural forest systems to develop management approaches that promote resilience in the face of global changes, and the study of trees and urban forests to reconcile the needs of minimizing negative impacts of trees on human infrastructure while maximizing ecosystem services. His work integrates field studies, simulation modeling, and network theory to address pressing challenges in forest ecology and management. His recent publications demonstrate a strong emphasis on urban forest resilience, functional diversity in forest ecosystems, and nature-based solutions for climate adaptation. The research shows a clear trajectory toward more applied, solution-oriented approaches that bridge fundamental ecological understanding with practical forest management applications across diverse spatial scales from individual trees to entire landscapes. Francqui Foundation Chair (Belgium) - 2020 Member of The Royal Society of Canada - 2019 Personality of the Year 'Radio-Canada/Le Droit' - 2017 Humboldt Research Award - 2016 Prix Acfas – Michel-Jurdant - 2010 Canadian Forestry Scientific Achievement Award - 2006 Dr. Messier has supervised over 40 graduate students throughout his career and currently leads multiple major research projects including the Canada Research Chair on Forest Resilience, the NSERC/Hydro-Québec Chair on Tree Growth Control, and the SylvCIT project for urban forest immunization against global change. His research has been supported by significant grants from NSERC, Canada Research Chairs program, Hydro-Québec, and other major funding agencies. He directs the Messier lab with research assistants Kim Bannon and Fanny Maure, and collaborates with numerous researchers across Canada and internationally. His team studies diverse aspects of forest ecology including soil dynamics, functional composition of tree communities, nature-based solutions for climate adaptation, and ecophysiology of maple water flow. The lab maintains strong connections with the International Diversity Experiment Network with Trees (IDENT) and other major forest research initiatives.

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Nabil NasrView profile

Professor

Rochester Institute of Technology (RIT)United States

Dr. Nabil Nasr serves as Associate Provost for Academic Affairs and Director of the Golisano Institute for Sustainability (GIS) at Rochester Institute of Technology (RIT). He also holds leadership positions as CEO of the REMADE Institute and Member of the United Nations Environment Programme (UNEP) International Resource Panel (IRP). His academic journey includes a BS from Helwan University (Egypt), M.Eng. from Pennsylvania State University, and MS and PhD from Rutgers University. Dr. Nasr is an internationally-recognized leader in sustainability research with expertise spanning sustainable manufacturing, remanufacturing, circular economy, and sustainable product development. His work emphasizes systems thinking and technological innovation to build regenerative industrial systems. He has pioneered research in value-retention processes, establishing frameworks for remanufacturing, refurbishment, repair, and direct reuse as strategic approaches to resource efficiency. His publication record demonstrates significant contributions to circular economy implementation across multiple sectors. Analysis of his recent work reveals strong focus on practical applications of circular strategies in industrial systems, automotive production, and urban mobility solutions, with emphasis on developing decision support tools and business cases for sustainable practices. Remanufacturing Industries Council 2017 ACE Award Rochester Engineering Society 2017 Engineer of Distinction APRA Asia-Pacific Most Influential Expert on Remanufacturing Award (2016) Institute of Industrial and Systems Engineers (IISE) Fellow Dr. Nasr has established numerous research centers and initiatives including the world's first university-based remanufacturing research hub (1997), the Center for Integrated Manufacturing Studies (2002), and the REMADE Institute - the largest recycling and remanufacturing consortium in the United States. His leadership extends to international forums including the UN Environment Programme, World Trade Organization, and OECD, where he influences global sustainability policy.

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Timothy TricasView profile

Professor

University of Hawaiʻi at MānoaUnited States

Timothy Tricas is a Professor at the University of Hawaii at Manoa's School of Life Sciences, specializing in fish sensory systems and coral reef ecology. He leads a research lab focused on understanding acoustic communication, neuroethology, and behavioral ecology in marine species. His work integrates field observations with neurophysiological and anatomical studies, often using advanced techniques like rebreather diving and hydrophone recordings. Affiliations: School of Life Sciences, Department of Zoology, Hawaii Institute of Marine Biology Courses Taught: Ethology, Animal Behavior, Sensory Ecology, Fish Behavior and Sensory Biology Research Interests: His studies explore how fish use sensory systems (auditory, lateral line, electrosense) to navigate, communicate, and survive in coral reef ecosystems. Key projects include decoding fish acoustic behaviors, understanding the evolution of specialized sensory adaptations (e.g., butterflyfish hearing mechanisms), and applying bioacoustics for coral reef health monitoring. Grants & Funding: Secured grants from NOAA, NSF, and the Hawaii Undersea Research Laboratory for projects like parrotfish soundscapes analysis and stingray electrosensory systems. Lab Activities: Mentors graduate and undergraduate students in field experiments, neuroanatomical studies, and acoustic data analysis. Current projects include parrotfish home range behavior and开发 new bioacoustic monitoring tools.

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Yiorgos MakrisView profile

Professor

University of Texas at DallasUnited States

Yiorgos Makris is a Professor in the Department of Electrical and Computer Engineering at the Erik Jonsson School of Engineering & Computer Science, The University of Texas at Dallas, since July 2011. Previously, he was a faculty member at Yale University for over a decade. He holds a Ph.D. in Computer Engineering from the University of California, San Diego, and a Diploma in Computer Engineering from the University of Patras, Greece. Education: Ph.D. in Computer Engineering, University of California, San Diego (2001) M.S. in Computer Engineering, University of California, San Diego (1997) Diploma in Computer Engineering and Informatics, University of Patras, Greece (1995) Research Interests: Hardware Security and Trustworthiness Statistical Side-Channel Fingerprinting Machine Learning in Semiconductor Manufacturing Trusted and Reliable Integrated Circuits Hardware Trojans in Wireless Cryptographic ICs On-Die Learning and Emergent Technologies His work focuses on enhancing hardware security through statistical methods, machine learning, and formal verification, with applications in analog/RF ICs, post-production calibration, and secure IC design. Key Contributions: Co-Founder and Site-PI of NSF CHEST I/UCRC (Hardware and Embedded System Security and Trust) Leader of the Safety, Security, and Healthcare Thrust at TxACE (Texas Analog Center of Excellence) Director of the Trusted and RELiable Architectures (TRELA) Lab Grants and Funding: NSF, NIH, SRC, ARO, AFRL, AFWERX, DARPA, DOE, and industry partnerships with Boeing, Northrop Grumman, IBM, Intel, Qualcomm, etc. Recent grants include projects on DNA storage security, analog neural networks, and malicious hardware detection. Awards and Recognition: IEEE Fellow (2025) Best Paper Awards at DATE'13, VTS'15, DCAS'22 Best Hardware Demonstration Awards at HOST'16 and HOST'18 Erik Jonsson School Faculty Research Award (2020) Labs and Teams: TRELA Lab (Focus: Secure Hardware Design, Trusted Architectures) CHEST I/UCRC (Industry-University Collaboration)

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Heikki HandroosView profile

Professor

Lappeenranta-Lahti University of Technology LUTFinland

Heikki Handroos is a Full Professor of Mechanical Engineering at LUT University, leading the Laboratory of Intelligent Machines since 1993. He holds a DSc (Technology) from Tampere University of Technology and has served as Vice-Dean of the Faculty of Technology (2007-2009) and currently chairs the Collegiate Body of LUT University. His research focuses on mechatronics, robotics, control systems, and fluid power, with over 300 publications and 2,400+ citations. He has supervised 34 doctoral theses and 150+ MSc projects, managed R&D projects exceeding €20M, and co-founded four tech startups. His work spans industrial collaborations, digital twin applications, and innovative robotics for nuclear energy (e.g., DEMO reactor maintenance systems). He has held visiting professorships in the U.S., Japan, and Russia, and actively contributes to academic editorial roles and professional societies like ASME and IEEE.

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Lars HansonView profile

Professor

University of SkövdeSweden

Lars Hanson is a Professor of Product Design Engineering at the University of Skövde's School of Engineering Science. His research focuses on ergonomics, digital human modeling, and optimizing manufacturing systems with a strong emphasis on human well-being and sustainable production. He leads projects like LITMUS (Industry 4.0 to 5.0 transition) and has contributed to developing tools such as IPS IMMA for ergonomic simulations. Active in virtual verification of human-robot collaboration and smart textile systems for workplace safety Published extensively in journals like International Journal of Human Factors Modelling and Simulation and IEEE Access Editor of conference proceedings and contributor to industry standards in automotive and healthcare sectors Research interests include multi-objective optimization of factory layouts, musculoskeletal risk assessment, and integrating ergonomic evaluations into product design processes. Current projects address Industry 5.0 sustainability challenges through digital twin technologies and smart manufacturing solutions.

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Gudrun P. KiesmüllerView profile

Professor

Technical University of MunichGermany

Prof. Dr. Gudrun P. Kiesmüller is a full professor of Operations Management at TUM Campus Heilbronn since 2019. Previously, she held full professorships at Kiel University (Supply Chain Management) and Otto von Guericke University Magdeburg (Operations Management). She studied mathematics at Julius-Maximilians-University of Würzburg and later worked as a postdoc and assistant professor at Eindhoven University of Technology. Her research focuses on supply chain management, inventory management (particularly spare parts), maintenance process planning, and manufacturing system design. She develops optimization approaches for decision support, with publications in journals like IISE Transactions and Production and Operations Management . Key awards include an Honorary Doctorate (2023), ISIR Service Award (2022), and multiple teaching and reviewer awards. She has contributed to advancing stochastic inventory models and operational efficiency in complex systems. Her work integrates theoretical rigor with practical applications, addressing challenges in inventory routing, buffer allocation, and component reliability optimization. Current research emphasizes dynamic maintenance planning and capital goods design.

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