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Jai TusharView profile

Research Fellow

• Numerical Analysis
• PDE constrained optimization
• Polytopal Finite Element Methods
• +3 more

Jai Tushar is a Research Fellow at the School of Mathematics, Monash University. His research focuses on numerical analysis, PDE-constrained optimization, and polytopal finite element methods. He holds a Ph.D. in Mathematics from Birla Institute of Technology and Science, where his thesis explored Virtual Element Methods for optimal control problems governed by diffusion equations. Before joining Monash, he served as a Research Associate at the Indian Institute of Technology Roorkee (Dec 2022 – Aug 2023). Research Interests: Tushar’s work emphasizes developing robust numerical methods for interface problems, optimal control systems, and fluid dynamics. His recent contributions include advancements in virtual element methods (VEM) for elliptic and diffusion interface problems, as well as BDDC preconditioners for polytopal discretizations. He also investigates doubly diffusive flows and Darcy flow control, blending theoretical analysis with computational implementations. Publications: His articles highlight trends in polytopal mesh adaptivity, convergence analysis of VEM, and stability studies in predator-prey models. Notable contributions include theoretical studies on Lipschitz domains and practical numerical simulations for ecological systems like Keoladeo National Park. Grants & Advising: No specific grants or student advisement roles are documented. However, his academic trajectory suggests active participation in collaborative research projects.

Hong LiView profile

Professor

• Actuarial Science
• Insurance Economics
• Data Analytics
• +6 more

Hong Li is a Professor in the Department of Economics and Finance at the Gordon S. Lang School of Business and Economics , University of Guelph (ranked #1 in Canada for Actuarial Science). He also holds an Adjunct Associate Professor position at the University of Waterloo's Department of Statistics and Actuarial Science. His research focuses on actuarial science, insurance economics, and data analytics applied to risk management challenges in longevity, climate, and agricultural sectors. Education : PhD in Econometrics & Operations Research, Tilburg University (2015) MPhil in Economics, Tilburg University (2012) B.A. in Finance, Xiamen University (2010) Research Interests include: Machine learning for insurance underwriting and pricing Mortality forecasting and longevity risk transfer Catastrophe bond design and climate risk modeling Optimization of index-based agricultural insurance Dynamic hedging strategies for financial institutions Awards : 2018 Bob Alting von Geusau Prize (best ASTIN Bulletin paper) University Research Award (2022-2023) Grants & Funding include: SSHRC Insight Development Grant ($69,623 CAD) NSERC Discovery Grant ($127,500 CAD) CAS Individual Grant ($18,000 USD) Teaching includes courses on risk management, actuarial economics, and financial econometrics at both undergraduate and graduate levels. Professional Service : Editorial Board Member: Annals of Actuarial Science and Journal of Risk and Insurance Member, Canadian Institute of Actuaries Academic Research Committee

Jagannathan SarangapaniView profile

Professor

• Neural Networks
• Adaptive Control
• Cyber-Physical Systems
• +5 more

Jagannathan Sarangapani is the William A. Rutledge - Emerson Electric Company Distinguished Professor at the Missouri University of Science and Technology, where he holds a primary appointment in the Department of Electrical and Computer Engineering. He also holds courtesy appointments in Computer Science and Engineering Management and Systems Engineering. His research focuses on adaptive control, neural networks, cyber-physical systems, robotics, and big data prognostics. He has supervised over 36 doctoral and 32 M.S. students, with current research funded to the tune of $47M (shared credit: $13.8M). His awards include the IEEE Fellow, Fellow of the National Academy of Inventors, and multiple teaching excellence awards. Education: Ph.D. in Electrical Engineering (University of Texas at Arlington, 1994), M.S. (University of Saskatchewan, 1989), and B.E. (Anna University, India, 1986). Research interests include learning algorithms, neural network decision-making, networked control systems, and healthcare applications. Recent grants include projects on human-machine teaming, resilient deep learning control, and UAV formation control. He has authored/co-authored over 500 publications, including 21 patents and five books. Awards highlight his contributions: IEEE Control Systems Society’s Transition to Practice Award (2018), NSF CAREER Award (2001), and multiple teaching commendations. He directs the Embedded Control Systems and Networking Laboratory and served as Site Director for the NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems.

Zia FarooqView profile

Research Fellow

• Infectious Disease Modelling
• Climate Change and Health
• Machine Learning in Epidemiology
• +3 more

Zia Farooq is a Research Fellow at the Department of Epidemiology and Global Health, Umeå Universitet, Sweden. His work focuses on predictive modelling of infectious diseases using machine learning and AI, with a particular emphasis on understanding the impact of climate change and human mobility on disease spread. He is a member of Henrik Sjödin Lab and Joacim Rocklöv Lab, and contributes to the Lancet Countdown Europe team addressing emerging infectious disease risks. Farooq holds a Master’s in Applied Mathematics from the Institute of Space Technology, Islamabad, where his thesis explored bifurcation analysis of nonlinear dynamical systems. He previously worked at the Systems Biology and Informatics Lab in Warsaw, Poland, researching cell signaling via dynamic modeling and information theory. His research spans climate-resilient health strategies, outbreak prediction algorithms, and data-driven approaches to assess pandemic severity. Recent publications highlight interdisciplinary work combining epidemiology, climate science, and AI to address global health challenges. Farooq collaborates on projects like the Lancet Countdown reports, emphasizing actionable insights for climate-sensitive health policies. His technical expertise includes advanced statistical methods, disease mapping, and decision-support tools for public health resilience.

Frauke LiersView profile

Professor

• Optimization under Uncertainty
• Distributionally Robust Optimization
• Quantum Computing
• +5 more

Prof. Dr. Frauke Liers holds the Professorship of Optimization under Uncertainty & Data Analysis at the Department of Data Science (DDS), Friedrich-Alexander-University Erlangen-Nürnberg. Her research focuses on robust and distributionally robust optimization, mathematical programming, and applications in energy systems, healthcare logistics, and quantum computing. Email: frauke.liers@fau.de ResearchGate: Frauke Liers Research Interests span optimization under uncertainty, data-driven mathematical programming, and interdisciplinary applications. Key areas include: Distributionally robust optimization with scenario reduction and chance constraints Quantum computing optimization for gate routing and noise suppression Energy system modeling (photovoltaics, gas networks, electricity networks) Healthcare logistics (patient transport scheduling under uncertainty) Nanoparticle technology and chemical process optimization Recent Publications emphasize: Advancements in quantum circuit optimization (2025) Explainable optimization methods (2024) Robust approaches for particle precipitation control (2024) Dynamic trajectory optimization (2023) Time-expanded models for network flows (2022)

Reza AbiriView profile

Assistant Professor

• Robotics
• Artificial Intelligence
• Brain Machine Interfaces
• +6 more

Dr. Reza Abiri is an Assistant Professor in the Department of Electrical, Computer and Biomedical Engineering at the University of Rhode Island's College of Engineering. His research focuses on translational neurorobotics, combining biosignal control systems with AI-enabled medical robotics to address neurorehabilitation challenges. He leads the Translational Neurorobotics Laboratory (TN Lab), established in Fall 2021 with NSF CAREER 2025 funding. Education: Postdoctoral Fellow, University of California, San Francisco and UC Berkeley (2021) Ph.D., Mechanical Engineering, University of Tennessee (2017) M.Sc., Mechanical Engineering, Amirkabir University of Technology, Iran (2011) B.Sc., Mechanical Engineering, K.N. Toosi University of Technology, Iran (2009) Dr. Abiri's research spans multiple disciplines including robotics, artificial intelligence, brain-machine interfaces, and biomedical engineering. His work addresses critical challenges in decoding neural activity for motor control, developing novel actuation mechanisms, and enhancing neurorehabilitation technologies through advanced signal processing and AI integration. Recent publications demonstrate a strong focus on brain-computer interfaces, attention training, and robotic rehabilitation systems. Key topics include EEG signal analysis, shared autonomy algorithms, multimodal AI frameworks, and magnetic actuation technologies. These works reveal a consistent pattern of innovation in connecting neural signals with robotic control systems. Scientific Recognition: NSF CAREER Award (2025) Dr. Abiri's TN Lab develops computational methods to overcome translational barriers in neurorehabilitation and motor control restoration. The lab's work integrates machine learning with biosignal processing to create advanced human-machine interaction systems, particularly focusing on noninvasive neural interfaces and their practical applications in healthcare robotics.

Gert WitvoetView profile

Assistant Professor

• Motion Control
• Nuclear Fusion
• Astronomy
• +7 more

Gert Witvoet is a part-time Assistant Professor at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e) , specializing in motion control for scientific applications. He is also a Senior Scientist at TNO Technical Sciences since 2012, working on optomechatronic control systems in space, astronomy, and Big Science projects. Research Focus: Motion control, feedback control, and injection locking in fusion plasmas Teaching: Coordinating Control Engineering and Motion Control Tuning courses Collaborations: TNO, DIFFER, and FOM Rijnhuizen His research explores the intersection of nuclear fusion and control technology, with a particular emphasis on stabilizing plasma instabilities in tokamak devices. He has contributed to projects like TROPOMI , LISA , and ITER , focusing on precise control mechanisms for high-tech systems. Recent work involves free-space optical communication systems, where he develops control algorithms for accurate pointing mechanisms in satellite-ground communications. His article trends highlight expertise in reset control , feedback stabilization , and dynamic noise budgeting . 2008: Best Junior Presentation (BJP) Award 2020: Best Paper Recognition at IEEE AMC2020 At TU/e, Witvoet supervises research projects and collaborates with industry partners via the Mechatronics Academy. His grants include TNO and FOM Rijnhuizen funding for fusion control systems. He works with the Control Systems Technology Group and contributes to the Learning, Identification and Control of High-Tech Systems research area.

Birgitta EbertView profile

Professor

• Metabolic Engineering
• Synthetic Biology
• Industrial Biotechnology
• +3 more

Dr. Birgitta Ebert is a Professor and FaBA Future Academic Leader in Fermentation at the Australian Institute for Bioengineering and Nanotechnology (AIBN), University of Queensland. Her research focuses on developing eco-friendly biotechnological solutions for pollution, climate change, and resource sustainability through metabolic engineering, synthetic biology, and systems analysis. She holds a PhD in Systems Biotechnology from TU Dortmund University and led a research group at RWTH Aachen University (2012–2019) before joining UQ in 2019. Her work emphasizes microbial cell factory engineering for converting renewable resources into valuable products, collaborating with chemists and engineers to enhance process efficiency. Key research areas include systems metabolic engineering, synthetic biology applications, and bioeconomy strategies. Ebert’s projects span triterpenoid production, cyanobacterial bioproduction, and lignin valorization, with a focus on sustainable chemical manufacturing. Recent articles highlight advancements in precision fermentation for food production, microbial triterpenoid synthesis, and biofuel development. She actively supervises PhD students in projects like vaccine adjuvant production, lignin conversion, and carbon-efficient bioprocesses. Ebert leads grants from funders such as Queensland-Germany Bioeconomy, ARC, and the U.S. Army, addressing challenges like lignin valorization and CO2-derived bioproducts. Her lab integrates omics technologies, synthetic biology tools, and high-throughput experimentation to drive innovation in industrial biotechnology.

• International Economics
• Macroeconomics
• International Finance
• +6 more

Jeffrey A. Frankel is the James W. Harpel Professor of Capital Formation and Growth at Harvard University's Kennedy School. He is a Research Associate at the National Bureau of Economic Research (NBER) and served in the Clinton Administration's Council of Economic Advisers (CEA) from 1996-99. Prior to Harvard, he was a Professor of Economics at UC Berkeley. His research focuses on international economics, monetary policy, fiscal policy, and environmental issues. Frankel holds a PhD from MIT and graduated from Swarthmore College. Frankel's work spans currencies, commodities, crises, and regional trade blocs. He is ranked among the 40 most-cited economists globally. Recent publications include analysis of the dollar's reserve status, recession forecasting, and climate policy. He frequently contributes to Project Syndicate and co-directs the NBER International Seminar on Macroeconomics. His advocacy includes air traffic control reform and opposition to protectionist trade policies. Frankel is affiliated with Harvard's Center for International Development and Mossavar-Rahmani Center for Business and Government. His expertise spans globalization, public finance, and energy policy. He actively engages in public debates on economic policy through media commentary and academic conferences, including recent discussions on Trump administration policies and global economic governance.

• Numerical Analysis
• Partial Differential Equations
• Finite Element Methods
• +5 more

Prof. Dr. Dietmar Gallistl is a faculty member at Friedrich-Schiller-Universität Jena, holding the Professorship for Numerical Mathematics within the Faculty of Mathematics and Computer Science. His research focuses on numerical methods for partial differential equations, including mixed finite elements, multiscale methods, adaptive algorithms, and computational homogenization. He teaches courses such as Theory and Numerics of Partial Differential Equations and Iterative Solvers for Partial Differential Equations . His research interests span various areas including discretization techniques for nonlinear PDEs, error analysis, and computational methods for wave propagation. He has contributed to software tools for finite element mesh refinement and numerical simulations. Recent work includes publications on the Gross-Pitaevskii eigenvalue problem, Monge-Ampère equations, and time-harmonic Maxwell equations. Prof. Gallistl's academic work emphasizes rigorous mathematical analysis alongside practical numerical implementation. His teaching materials include lecture notes on computational PDEs and finite element methods available on his university webpage.

Somayeh SojoudiView profile

Associate Professor

• Artificial Intelligence
• Control Systems
• Intelligent Systems
• +7 more

Somayeh Sojoudi is an Associate Professor in the Departments of Electrical Engineering & Computer Sciences and Mechanical Engineering at UC Berkeley, affiliated with the Berkeley Institute for Data Science (BIDS). Her research focuses on Artificial Intelligence, Control Systems, Optimization Theory, and Power and Energy systems. She teaches courses like EECS 127 and EECS 227AT on optimization models in engineering. Education: PhD in Control & Dynamical Systems from the California Institute of Technology (2013). Research Interests : AI and Machine Learning, particularly neural network robustness and generative models Optimization methods for non-convex and low-rank problems Control systems, power grids, and distributed energy resources Game-theoretic approaches in dynamic systems Awards : NSF CAREER Award (2021) ONR Young Investigator Award (2021) INFORMS Optimization Society Prize for Young Researchers (2015) IEEE PES Best-of-the-Best Conference Paper Award (2022) Her work bridges theoretical advancements in optimization with practical challenges in energy systems and AI, emphasizing robustness and safety-critical applications.

Aurelio PiazziView profile

Professor

• Control Theory
• Autonomous Robotics
• Mechatronics Systems
• +7 more

Aurelio Piazzi is a Full Professor of Systems and Control Engineering at the Department of Engineering and Architecture , University of Parma , Italy, where he has been a faculty member since 1992. He holds a Laurea magna cum laude in nuclear engineering and a PhD in Systems Engineering, both from the University of Bologna. He founded the Active Control Laboratory (ACtLab) in 1995 and currently serves as the director of the Polytechnic Library and president of the Laurea Magistrale in Informatics Engineering. Academic Rank: Professor Department: Department of Engineering and Architecture University: University of Parma Email: aurelio.piazzi@unipr.it Office Location: Campus Scienze e Tecnologie - Padiglione 10, Parco Area delle Scienze, 181/A, 43124 Parma, Italy Personal Website: http://www.ce.unipr.it/people/piazzi His research is centered on control theory , with a focus on inversion-based and optimal feedforward control methods , feedforward-feedback control strategies , and autonomous navigation of wheeled robots and vehicles. He also investigates vision-based control systems and mechatronics . His work bridges theoretical advancements with industrial applications, including food ovens and railway pantograph inspection. The recent publications highlight a strong trend in inversion-based control architectures , feedforward regulation , and trajectory planning for autonomous systems. His work frequently employs polynomial interpolation , spline methods (e.g., eta3, eta4) , and dynamic inversion to achieve smooth, optimal, and robust motion control. The research spans from theoretical equivalence proofs to practical implementations in robotics and industrial automation. He has led significant research projects such as: COOKIES: EU-funded project on vision-based control of food industrial ovens. PAVISYS: Vision-based inspection system for railway pantographs, developed in collaboration with RFI Ferrovie dello Stato. PRIN Projects: National research units on automation and control theory funded by MIUR. He has published over 100 scientific papers in top journals like IEEE Transactions on Automatic Control , Automatica , and IEEE Transactions on Robotics . He is a Senior Member of IEEE and a member of SIAM , reflecting his standing in the international control and applied mathematics communities. He teaches core courses including Fundamentals of Automatic Control and Nonlinear Systems at both undergraduate and graduate levels. He has supervised numerous research students and mentored early-career researchers. His laboratory, ACtLab (Active Control Laboratory) , serves as the primary hub for both teaching and research in automation and control systems at the University of Parma, fostering innovation and practical experimentation.

Turaj AshuriView profile

Professor

• Multiphysics Modeling
• Design Optimization
• Renewable Energy Systems
• +5 more

Dr. Turaj Ashuri is an Assistant Dean of Research Initiatives and Graduate Programs (interim) at the College of Engineering and Engineering Technology, Kennesaw State University. He previously held faculty positions at the University of Texas at Dallas and Arkansas Tech University, where he served in leadership roles such as Director of the Interdisciplinary Research Center and Graduate Program Director. Before academia, he accumulated over a decade of industry experience as a Structural Design Engineer, Research Engineer, and R&D Project Manager. PhD, Aerospace Engineering, Delft University of Technology MSc, Aerospace Engineering, Sharif University of Technology BSc, Mechanical Engineering, Tehran Azad University Postdoctoral Research Fellowship, University of Michigan - Ann Arbor Dr. Ashuri's research focuses on Multiphysics Modeling and Design Optimization , spanning theoretical and applied domains. His work develops numerical methods for unsteady flow fields, nonlinear composite structures, and machine learning algorithms, while applying these techniques to soft robots, unmanned aerial vehicles, and renewable energy systems. He actively explores Uncertainty Quantification and Optimal Control in energy systems, with particular emphasis on wind turbine technology and biomedical soft robotics. His recent publications demonstrate expertise in Wind Farm Optimization (2016-2018), Soft Robotics (2020), and Hydrogen Fuel Cell Vehicles (2019). These works intersect Computational Design , Control Theory , and Renewable Energy Systems , reflecting his multidisciplinary approach. Scientific recognitions include: Associate Fellow, American Institute of Aeronautics and Astronautics (AIAA) Chair, 2023 AIAA Aviation Forum Discipline Committee Dr. Ashuri's lab at KSU conducts research in Multidisciplinary Design Optimization and Machine Learning applications for intelligent mechanical systems. The lab receives funding from NASA and NIH , supporting work on soft robots, wind turbine engineering, and energy systems optimization.

Andrew LammasView profile

Lecturer

• Robotics
• Autonomous Systems
• Electrical and Electronic Engineering
• +17 more

Andrew Lammas is a Lecturer in Electrical and Electronic Engineering at Flinders University, within the College of Science and Engineering and affiliated with the Centre for Defence Engineering Research and Training. He holds a PhD and Bachelor of Engineering from Flinders University and has been actively contributing to research and teaching since 2023. His work spans robotics, control systems, machine learning, and renewable energy systems. Education: Bachelor of Engineering (Computer Systems), Flinders University, 2004 Doctor of Philosophy (Engineering), Flinders University, 2012 His research interests include robot localisation, control, state estimation, sensor fusion, battery management, and renewable energy systems. He has developed expertise in Bayesian filtering, Kalman and particle filters, digital twins, and hydrodynamic modeling. His teaching responsibilities include coordination and lecturing in Electronic Circuits and Estimation & Machine Learning. The most recent research articles highlight a strong focus on autonomous underwater vehicles, digital twins for defence applications, sim-to-real transfer in control systems, and condition-based maintenance using hybrid neural-physical models. These works reflect a consistent trajectory in intelligent robotic systems, adaptive control, and real-world deployment of AI in engineering contexts. Scientific Awards: No awards explicitly mentioned. Andrew Lammas supervises Honours, Master’s, and PhD students, with registered interests in robot planning, battery management, sensor processing, and control of robotic platforms. He has led industry and defence-affiliated research projects, including multiple technical reports for the Department of Defence. He is also involved in community outreach, such as regional roadshows and Science Alive events, promoting engineering and robotics. He is actively involved in the RobotX Maritime Robotics Competition and contributes to curriculum development in electrical and electronic engineering. His research aligns with UN Sustainable Development Goals in renewable energy and sustainable infrastructure.

Szende TonkView profile

Associate Professor

• Environmental chemistry
• Biochemistry
• Biotechnology
• +4 more

Szende Tonk is an Associate Professor at the Department of Environmental Science, Sapientia Hungarian University of Transylvania, Faculty of Sciences and Arts. She teaches courses including General Biochemistry, Organic Chemistry, Meteorology-Climatology, and Sustainable Waste Management at both undergraduate and master's levels. Research Focus: Environmental chemistry, biosorption, phytoextraction, chemical pollution analysis, and environmental remediation technologies. Recent Publications: 2024 study on tetracycline adsorption using waste biosorbents; 2023 work on drug residue toxicity; extensive 2022-2020 studies on dye adsorption mechanisms using brewery waste, mineral clay, and eggshell biosorbents; and PM10 pollution analysis in Eastern Carpathians. Collaborations: Regularly works with researchers like E. Rápó, K. Posta, and Á. Szabó on adsorption studies and environmental monitoring projects.