جست‌وجوی استاد و پژوهشگر

Asad Razaمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Network Security
• Blockchain Technology
• +۳ مورد دیگر

Asad Raza is a Senior Lecturer in the Department of Computer Science at NJIT. With 13 years of teaching experience across four countries, he focuses on cybersecurity, network security, and related disciplines. He holds an M.S. in Information & Communication Systems Security from KTH Royal Institute of Technology (2009) and a B.S. in Software Engineering from the University of Engineering & Technology (2005). His expertise includes providing cybersecurity trainings to government, military, and private sectors, along with delivering courses such as Network Protocols Security and Introduction to Cybersecurity. He has published widely on topics ranging from blockchain oracle solutions to intrusion detection systems. Research interests encompass cybersecurity fundamentals, wireless sensor networks, and cyber-physical systems. Recent work addresses blockchain oracle vulnerabilities, risk management in industrial systems, and energy-efficient routing protocols. His contributions to forensic processes in virtualized environments and automated network security tools further highlight his interdisciplinary approach. Notable collaborations include industry partnerships for cybersecurity trainings and invited speaking roles at international conferences. While no specific grants or awards are listed, his active research and teaching reflect a commitment to advancing cybersecurity education and practice.

Ria D. Corderمشاهده پروفایل

استادیار

• Rheology
• Polymer Science
• Biomedical Applications
• +۴ مورد دیگر

Ria D. Corder is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at the University of Tennessee, Knoxville, housed within the Tickle College of Engineering. Her research focuses on the rheological characterization of complex materials, including soft tissues, polymers, and nanocomposites, with applications in biomedical engineering, sustainable materials, and additive manufacturing. Education: BS and MS in Chemical Engineering, University of Alabama (2014) PhD in Chemical Engineering, North Carolina State University (2020) Lillian Gilbreth Postdoctoral Research Fellow at Purdue University College of Engineering (2021–2023) Research interests span rheological studies of biological tissues, enzyme-assisted biomass processing, and the design of functional materials for 3D printing. Her work integrates experimental techniques with data-driven modeling to understand and optimize material behavior under mechanical and chemical stimuli. Key areas include drug delivery systems, tumor mechanics, and ceramic-polymer composites. Publications reflect a focus on rheology-driven insights into material behavior, covering topics from thermosensitive drug carriers to nonlinear flows in industrial and biomedical contexts. Recent studies emphasize interdisciplinary applications, such as enzyme-mediated tissue digestion and additive manufacturing challenges in ceramics. Notable awards include the prestigious Lillian Gilbreth Postdoctoral Fellowship (2021–2023). While her advising record is not detailed here, her postdoctoral mentorship and collaborative projects suggest active involvement in training early-career researchers. She contributes to grants focused on sustainable biomaterials and advanced manufacturing technologies. No specific labs or research teams are explicitly mentioned, though her work aligns with UT’s initiatives in bioengineering and materials innovation.

• Geochemistry
• Petrology
• Mantle Dynamics
• +۶ مورد دیگر

Dr. Carl Spandler is an Adjunct Associate Professor at James Cook University, specializing in geochemistry and petrology. His research focuses on Earth’s mantle evolution, basaltic magma formation, subduction zone processes, and the tectonic significance of rare earth element (REE) deposits. Current projects include studies on REE mobility in the crust, crustal evolution of NE Australia, and high-pressure metamorphic rocks. Key research themes include: Geochemical cycling of REEs and critical minerals Magmatic processes in continental arcs and ophiolites Ore genesis in volcanic and carbonatite systems He has led projects such as the 'Jurassic Arc' reconstruction of eastern Gondwana and investigations into the Rukwa Rift Basin’s magmatic history. His work combines field studies, isotopic analysis (U-Pb, Nd), and experimental petrology. Teaching involvement includes mentorship in geology, particularly in analytical techniques and mineral systems. Collaborations span institutions globally, including studies in Tanzania, Peru, and China. His publications emphasize methodological advancements in laser ablation ICP-MS and the application of detrital zircon data to tectonic reconstructions. Laboratory contributions include work on the Gifford Creek Carbonatite Complex and the Tommy Creek Domain, highlighting his focus on interdisciplinary approaches to crustal evolution and mineral resource exploration.

Gaofeng Jiaمشاهده پروفایل

دانشیار

• Structural Engineering
• Risk Assessment
• Infrastructure Resilience
• +۴ مورد دیگر

Gaofeng Jia is Associate Professor in Civil and Environmental Engineering at Colorado State University's Walter Scott, Jr. College of Engineering. He specializes in natural hazard risk assessment, infrastructure resilience, and uncertainty quantification. Research integrates simulation-based approaches with high-performance computing for assessing complex engineering systems. Core areas include infrastructure deterioration modeling, wave energy converter optimization, tsunami evacuation planning, and surrogate modeling techniques. Recent work emphasizes physics-informed machine learning for engineering applications. Publications demonstrate consistent methodological innovation in uncertainty quantification across domains including seismic engineering, coastal hazards, renewable energy systems, and structural reliability. Articles employ advanced computational statistics, Bayesian methods, and multi-fidelity modeling. Young Researcher Best Paper Award Best Student Paper Award

Hao Louمشاهده پروفایل

استادیار

• Pharmaceutical Formulations
• Computational Modeling
• Molecular Dynamics
• +۵ مورد دیگر

Dr. Hao Lou is an Assistant Professor in the Department of Pharmaceutical Chemistry at the University of Kansas School of Pharmacy. His research integrates computational modeling and experimental approaches to advance drug formulation design, with emphasis on subcutaneous delivery systems for biologics and oral formulations. Research focuses on: Computational pharmaceutics using machine learning and molecular dynamics Subcutaneous delivery of monoclonal antibodies and protein therapeutics In vitro emulation of subcutaneous absorption (ESCAR system) Formulation optimization for cyclic peptides and biologics Protein stabilization and drying techniques Recent publications demonstrate novel applications of molecular dynamics simulations in predicting peptide properties, optimizing high-concentration protein formulations, and developing biorelevant dissolution methods. Work appears in pharmaceutical sciences journals covering formulation design and computational modeling. Developed innovative platforms including an Emulator of Subcutaneous Absorption and Release (ESCAR) and protein-hyaluronic acid precipitation techniques. Contributes to advancing dry powder processing for inhaled formulations.

• Optimization and optimal control
• Inverse problems
• Mathematical imaging
• +۵ مورد دیگر

Karl Kunisch is a Professor at the Department of Mathematics and Scientific Computing at the University of Graz and serves as Scientific Director of the Radon Institute of the Austrian Academy of Sciences in Linz. With a distinguished career spanning several decades, he has established himself as a leading researcher in optimization and control theory. Prof. Kunisch completed his PhD and Habilitation at the Technical University of Graz in 1978 and 1980, respectively. His academic journey includes significant positions at Brown University's Lefschetz Center for Dynamical Systems, INRIA Rocquencourt, Universite Paris Dauphine, and he previously served as a professor of numerical mathematics at the Technical University of Berlin. Research Interests: Prof. Kunisch's research focuses on optimization and optimal control, inverse problems and mathematical imaging, numerical analysis and applications, with current emphasis on life sciences applications. His specific areas include Optimal Control of Partial Differential Equations, Nonsmooth Optimization in Function Spaces, and Applications of Optimization and Control in the Life Sciences. His work bridges theoretical mathematics with practical applications across various scientific domains. His recent publications demonstrate a continued focus on advancing the theoretical foundations of optimal control while developing practical numerical methods. Key trends include work on infinite horizon control problems, feedback stabilization techniques, applications to PDE-constrained optimization, and the integration of machine learning approaches with traditional control theory. His research group actively explores connections between theoretical developments and applications in the life sciences. Scientific Recognition: W.T. and Idalia Reid Prize 2021 SIAM Fellow (2017) European Research Council Advanced Grant (2015) Alwin Walther Medaille (2008) SIAM Outstanding Paper Prize (2006) Prof. Kunisch has made substantial contributions to the mathematical community through his editorial work, serving as editor for prestigious journals including SIAM Journal on Control and Optimization, SIAM Journal on Numerical Analysis, and the Journal of the European Mathematical Society. He leads the Research Group on Optimization and Optimal Control at the Johann Radon Institute for Computational and Applied Mathematics (RICAM) and is involved in the ERC-Project OCLOC "From Open to Closed Loop Control".

Georgios Andrikopoulosمشاهده پروفایل

استادیار

• Robotics
• Biomedical Engineering
• Control Systems
• +۴ مورد دیگر

Georgios Andrikopoulos is an Assistant Professor at KTH Royal Institute of Technology's Department of Industrial and Environmental Management (ITM), affiliated with the Digital Futures Faculty. He serves as Co-Principal Investigator (Co-PI) on the 'Real-time exoskeleton control for human-in-the-loop optimization' project, focusing on advanced robotics and human-technology interaction. His research spans soft robotics, exoskeleton systems, and adaptive climbing robots, with applications in healthcare, aerospace, and education. Key projects include: "Connecting Bodies – Designing Shape-changing Wearables" (Postdoc Fellowship, 2023–2025) "Advancing real-time exoskeleton control for human-in-the-loop optimization" (Demonstrator Project) SEC scholar collaboration with Mohamed Elbadawi (May–June 2024) Research interests emphasize: Soft robotic actuators for safe human interaction Optimization of compliant mechanisms in robotics Vortex adhesion systems for autonomous inspection Design of child-friendly interactive robots His work integrates robotics with control systems, biomechanics, and human-centered design. Over 50 peer-reviewed articles demonstrate contributions to exoskeleton technology, climbing robot algorithms, and soft actuator modeling. He advises students like Laia Turmo Vidal (Postdoc) and Mohamed Elbadawi (SEC scholar). Affiliated with the cross-disciplinary Digital Futures initiative, he collaborates with Stockholm University and RISE Research Institutes to address societal challenges through digital innovation.

Andrea Crovettoمشاهده پروفایل

دانشیار

• Photovoltaics
• Solar Energy Conversion
• Thin Film Technology
• +۳ مورد دیگر

Andrea Crovetto is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the National Centre for Nano Fabrication and Characterization and the Department of Nanofabrication. His research focuses on advanced materials for photovoltaic applications, including solar cell technologies, thin films, and semiconductor materials. His work contributes to UN Sustainable Development Goals related to affordable and clean energy. Key research interests include photovoltaic materials discovery, tandem solar cell design, and semiconductor characterization. Notable achievements include developing monolithic selenium/silicon tandem solar cells and pioneering studies on phosphosulfide semiconductors. He has authored over 90 publications and datasets, including high-impact articles in journals like JPhys Energy and PRX Energy . Dr. Crovetto has received the Young Scientist Award (2016) and actively supervises PhD students in projects such as Experimental Discovery of Phosphosulfide Materials for Solar Cells and Thiophosphate Thin Films for Quantum Technology . His research also involves collaborations on material synthesis, computational modeling, and device fabrication. He has presented at international conferences, including talks on monolithic tandem solar cells and materials discovery methodologies. His lab, based at DTU’s Produktionstorvet , integrates experimental and theoretical approaches to advance sustainable energy technologies.

Rosario B. Jaime-Laraمشاهده پروفایل

استادیار

• Nutrition
• Neurophysiology
• Obesity Research
• +۵ مورد دیگر

Rosario B. Jaime-Lara is an Assistant Professor at the University of California, Los Angeles (UCLA) School of Nursing. She holds advanced degrees including a PhD in Nursing from the University of Pennsylvania, MSN from Columbia University, and dual BS degrees in Nursing and Biological Sciences from University of Pennsylvania and UC Davis. Her research focuses on neurophysiological mechanisms of eating behavior, nutritional disparities in Mexican-American communities, and chemosensory science. Key themes include obesity research, sensory neuroscience, and translational clinical studies. She employs rodent models and clinical research methodologies to explore taste/smell physiology and metabolic health. Jaime-Lara has received over 17 honors including the 2022 Hommer Memorial Award and multiple diversity fellowships. Her work spans interdisciplinary collaborations in genomics, microbiome research, and health IT interventions for chronic disease management. Recent publications emphasize olfactory dysfunction in coronaviruses, fat taste mediators, and metabolic profiling. Her research bridges basic science and clinical practice, with particular attention to underserved populations.

• Clinical Pharmacology
• Quality Use of Medicines
• Geriatric Pharmacology
• +۳ مورد دیگر

Professor Andrew McLachlan is the Head of School and Dean of Pharmacy at the Sydney Pharmacy School, University of Sydney. He holds a BPharm(Hons1 Medal) and PhD, and is a Member of the Order of Australia (AM). His research focuses on clinical pharmacology, particularly optimizing medication use in special populations such as older adults, children, and critically ill patients. He has led initiatives like the NHMRC Centre for Research Excellence in Medicines and Ageing, and his work emphasizes translating clinical evidence into real-world practice. Education: Bachelor of Pharmacy (First Class Honours) PhD in Clinical Pharmacology Research Interests: Variability in drug response across populations Quality use of medicines in geriatrics Pharmacotherapy optimization in critical care Deprescribing strategies for older adults Grants & Projects: PROSPER Trial (2025): Evaluating opioid alternatives for postoperative pain DREAM Trial (2024): Duloxetine for chronic sciatica Awards: Member of the Order of Australia (AM) Key Contributions: Leading deprescribing initiatives Advancing personalized pharmacotherapy Improving medication safety in vulnerable populations

• Machine Learning
• Reinforcement Learning
• Sample-efficient Generalization
• +۵ مورد دیگر

Dr. Yangchen Pan is a Departmental Lecturer in Machine Learning at the University of Oxford's Department of Engineering Science. His research focuses on achieving sample-efficient generalization in machine learning, particularly in settings involving distribution shifts (e.g., adversarial learning, domain adaptation) and adaptive capabilities like offline/online reinforcement learning and continual learning. He has contributed to foundational work in reinforcement learning, robustness, and risk-averse optimization. Education and Academic Background: While specific degree details are not explicitly listed, his academic trajectory includes roles at leading institutions such as the University of Alberta (PhD, 2017-2020), where he collaborated with prominent researchers like Martha White and Amir-massoud Farahmand. Additional affiliations include teaching roles at the University of Waterloo, University of Toronto, and Indiana University. Research Interests: Pan's work spans machine learning theory and applications, with emphasis on scalable algorithms for complex decision-making systems. Key areas include adversarial robustness, offline reinforcement learning, and mitigating distribution shifts in real-world deployments. His recent contributions explore risk-aware policy optimization and novel approaches to sample efficiency. Professional Service: Pan serves on the program committees of top conferences like NeurIPS, ICML, and ICLR. He has reviewed for journals including the Journal of Machine Learning Research and Transactions on Machine Learning Research. Teaching: Pan teaches advanced courses in optimization, machine learning, and AI at the University of Oxford, including C25 Optimization and AI/ML with Python. He has also taught at the University of Alberta and Indiana University. Labs/Teams: While no specific lab name is mentioned, his research is closely tied to Oxford's Engineering Science department and collaborative projects with institutions like the ZERO Institute (as seen in event leadership at IMAD2025).

• Entrepreneurial Education
• Experiential Learning
• Digital Business Models
• +۳ مورد دیگر

Apurva Ganoo is a Lecturer at the Department of Management Studies, Aalto University. Their research focuses on experiential learning methodologies in entrepreneurial education, digital business models, and future-ready skill development. They explore topics such as anti-rivalry dynamics in digital goods, transdisciplinary collaboration, and pedagogical frameworks for innovation. Research interests emphasize bridging theoretical concepts with practical application through experiential approaches. Their work analyzes student perceptions in multidisciplinary team settings and the design of educational systems that foster entrepreneurship and adaptability. No academic awards or grants are explicitly mentioned in the provided materials. Their professional contributions center on advancing management education through innovative teaching methods and curriculum development.

Alan Kaptanogluمشاهده پروفایل

استاد

• Applied Mathematics
• Scientific Machine Learning
• Nuclear Fusion
• +۳ مورد دیگر

Alan Kaptanoglu is a Professor leading the Plasma Physics Group at New York University's Courant Institute. His research focuses on the intersection of applied mathematics, scientific machine learning, and nuclear fusion. He develops theoretical and computational tools for plasma modeling, control, and optimization in complex dynamical systems. Key areas include stellarator design optimization, machine learning-driven MHD simulations, and reactor-scale plasma confinement solutions. His work advances fusion energy research through innovations in magnetic field shaping, coil optimization, and data-driven modeling of plasma behavior. Research interests span plasma turbulence analysis, magnetohydrodynamics, and the application of physics-informed neural networks (PINNs). He explores how magnetic geometry influences plasma stability and turbulence using machine learning techniques. His team addresses challenges in fusion reactor design, such as minimizing Lorentz forces in electromagnetic coils and optimizing permanent magnet configurations for stellarators. Recent work emphasizes data-driven methods for discovering interpretable models in fluids and plasmas, including reduced-order modeling and sparse regression approaches. He collaborates on projects like the DIII-D tokamak and ITER, advancing fusion energy solutions through interdisciplinary computational and experimental efforts. His group's contributions bridge plasma physics with advanced mathematics and machine learning to tackle grand challenges in energy and astrophysical systems. Advising and grants are not explicitly detailed in the provided texts, but his leadership role suggests active mentorship in graduate research. The NYU Plasma Physics Group serves as a hub for cutting-edge research, hosting internships, summer schools, and collaborations with industry/academic partners.

• Environmental Economics
• Natural Resource Management
• Policy Design
• +۶ مورد دیگر

Rick Horan is a Professor in the Department of Agricultural, Food, and Resource Economics at Michigan State University (MSU), part of the College of Agriculture & Natural Resources. He holds a Ph.D., M.A. from Pennsylvania State University, and dual B.S. degrees from Appalachian State University. His research focuses on environmental and natural resource economics, particularly the interplay between economic and ecological systems. Key areas include endangered species management, invasive species control, wildlife disease dynamics, and agricultural pollution policy. He has published in top journals like PNAS, American Economic Review, and the American Journal of Agricultural Economics. Horan has served as Managing Editor of Resource and Energy Economics (2010–13), Associate Editor roles for American Journal of Agricultural Economics and Natural Resource Modeling , and contributed to a National Academy of Sciences report on environmental policy. His teaching includes Advanced Natural Resource Economics and Microeconomic Theory analysis. Research highlights include modeling ecological thresholds, bioeconomic approaches to species management, and integrating human behavior into epidemiological models. His work has been featured in media outlets like The Economist and Forbes. Horan’s advising and grants focus on interdisciplinary solutions for environmental challenges. His labs and research teams address complex issues like agri-environmental service coordination and sustainable land-use strategies. Current research explores policy mechanisms for balancing economic activities with ecosystem preservation.

Eduardo Gildinمشاهده پروفایل

استاد

• Reservoir Modeling and Simulation
• Control and Optimization of Dynamical Systems
• Model Reduction Techniques
• +۵ مورد دیگر

Eduardo Gildin is a Professor of Petroleum Engineering and Associate Department Head for Graduate Studies at Texas A&M University's College of Engineering. He holds the L.F. Peterson '36 Professorship and directs the university's graduate studies in petroleum engineering. His research focuses on reservoir modeling, control optimization, model reduction techniques, and CO2 sequestration. Gildin has pioneered data-driven approaches for reservoir simulation, integrating machine learning and physics-based models to enhance efficiency and accuracy. Education: Ph.D. in Aerospace Engineering, University of Texas at Austin (2006) M.S. in Mechanical Engineering, University of São Paulo, Brazil (1998) B.S. in Mechanical Engineering, Faculdade de Engenharia Industrial, Brazil (1995) Research Interests: Model reduction of large-scale dynamical systems Control and optimization of reservoir operations CO2 storage and geological carbon sequestration Machine learning applications in reservoir engineering and drilling automation Geomechanics and compaction damage evaluation Key Awards: 2020: William O. and Montine P. Head Memorial Research Award 2017-2018: Dean of Engineering Excellence Award 2013-2019: Energi Simulation Chair in Robust Reduced Complexity Modeling 2021: Distinguished Membership in Society of Petroleum Engineers Grants and Advising: Gildin has secured major funding for projects on reservoir simulation, drilling automation, and CO2 storage. He advises graduate students on topics such as surrogate modeling and reinforcement learning applications in petroleum systems. His lab collaborates with industry partners to translate research into practical tools for reservoir management and subsurface operations. Labs and Teams: He leads the Reservoir Simulation and Control Lab, focusing on advanced computational methods for reservoir optimization. His team develops open-source drilling models and collaborates globally on projects like the DREAMS (Drilling and Extraction Automated System) initiative.