جست‌وجوی استاد و پژوهشگر

• Computational Multiscale Modeling
• Artificial Intelligence
• Process Control
• +۵ مورد دیگر

Davood B. Pourkargar is an Assistant Professor in the Tim Taylor Department of Chemical Engineering at Kansas State University (K-State), part of the Carl R. Ice College of Engineering. He is also a graduate faculty member at the Food Science Institute and a faculty researcher at the Johnson Cancer Research Center. His professional experience includes roles at ExxonMobil Research and Engineering, the University of Minnesota, and the University of Delaware. Education: Ph.D. in Chemical Engineering, Pennsylvania State University (2015) M.S. in Chemical Engineering, Sharif University of Technology (2010) B.S. in Chemical Engineering, Sharif University of Technology (2008) Research Interests: Focuses on computational multiscale modeling, artificial intelligence, optimal control, and automation for sustainable energy/chemical production. Key areas include physics-informed machine learning, cyber-physical systems, and smart materials synthesis. His lab integrates process systems engineering with digital twin technology to enhance decision-making in complex systems. Key Research Trends: Recent work emphasizes distributed control architectures, resilient process networks, and applications in renewable energy (e.g., green ammonia, solar cell production). His publications span AI-driven modeling, cybersecurity for manufacturing systems, and data-driven predictive frameworks. Awards: 2024 Carl R. Ice College Outstanding Assistant Professor NSF EPSCoR Fellowship AFOSR Faculty Fellowship Multiple Best Presentation Awards at AIChE/ACC conferences Advising & Grants: Advises over a dozen graduate/undergraduate students. Secured grants including NSF funding for physics-informed machine learning in organ-on-a-chip systems. Active in lab automation and robotic additive manufacturing initiatives. Labs & Teams: Director of the Intelligent Sustainable Process Systems Lab (ISPSL), with computational and experimental facilities in Durland Hall. Collaborates across disciplines including food science, cancer research, and biomedical engineering.

• Industrial Automation
• Robotics
• Flexible Manufacturing Systems
• +۴ مورد دیگر

Mikel Bueno Viso is a Researcher at Cranfield University's School of Aerospace, Transport and Manufacturing, affiliated with the Centre for Robotics and Assembly. His work focuses on Robotics , Industrial Automation , and Flexible Manufacturing Systems . He holds a BSc and MSc in Industrial Engineering from the University of the Basque Country and a Robotics MSc from Cranfield University. His research centers on ROS 2-based frameworks , robot perception , and modular middleware for reconfigurable manufacturing. Key projects include developing software architectures for object detection , pose estimation , and seamless robot integration . Mikel is currently a part-time PhD candidate investigating Flexible and Reconfigurable Manufacturing . His 2024-2025 publications demonstrate applications in Reconfigurable robotic cells Modular software frameworks Industry 4.0 automation His work leverages technologies like YOLOv8 for object detection and OpenCV for pose estimation, aiming to transform traditional manufacturing through software abstraction and interoperability .

A. Erdem Sariyuceمشاهده پروفایل

دانشیار

• Graph Mining
• Social Network Analysis
• Network Science
• +۴ مورد دیگر

A. Erdem Sariyuce is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. His research focuses on graph mining, network science, and distributed computing. He holds a PhD from Ohio State University (2015) and a BS from Middle East Technical University (2010). His work explores temporal network analysis, social network dynamics, and algorithm design for large-scale systems. Notable contributions include methods for motif detection, core decomposition, and stream processing in bipartite networks. Sariyuce has received prestigious awards such as the NSF CAREER Award (2023) and the UB Exceptional Scholar—Young Investigator Award (2023). His research is supported by grants including the LDRD Project at Sandia National Laboratories (2016-2017). Education: PhD, Computer Science and Engineering, Ohio State University, 2015 BS, Computer Engineering, Middle East Technical University, 2010 Research interests emphasize graph algorithms, network resilience, and parallel computing. His recent projects include analyzing financial networks, identifying cohesive communities, and developing efficient algorithms for temporal data. His work bridges theoretical foundations with practical applications in social media, cybersecurity, and bioinformatics. Awards: UB Exceptional Scholar—Young Investigator Award (2023) NSF CAREER Award (2023) SEAS Early Career Researcher of the Year (2020) Advising and grants highlight his leadership in collaborative projects, including the NSF-funded Collaborative Research: OAC Core: Fast Tools for Complex Event Detection over Bipartite Graph Streams (2021). His research often involves industry partnerships and government labs, such as Sandia National Laboratories.

Guifang Liمشاهده پروفایل

استاد

• Optical Communication
• Networking
• RF Photonics
• +۳ مورد دیگر

Guifang Li is a Professor of Optics and Electrical & Computer Engineering at the University of Central Florida (UCF), affiliated with CREOL, The College of Optics and Photonics. He holds the position of Editor-in-Chief of Advances in Optics and Photonics . His academic journey includes a Ph.D. from the University of Wisconsin-Madison and leadership roles such as Director of the NSF IGERT program in Optical Communications and Networking at UCF. Dr. Li's research focuses on optical communication and networking , RF photonics , and all-optical signal processing . His innovations include pioneering work on photonic computing architectures and high-capacity optical communication systems. He co-founded Optium, UCF's first venture startup, which became a public company (OPTM) in 2006 and later part of II-VI. His scientific contributions are recognized through prestigious awards, including the NSF CAREER Award, Office of Naval Research Young Investigator Award, and fellowships from IEEE, OSA, SPIE, and the National Academy of Inventors. He has advised over 20 Ph.D. students and leads a multidisciplinary research group involving postdoctoral scholars and graduate students. Recent research trends in his publications emphasize photonic computing (e.g., photonic matrix processors, floating-point arithmetic) and advanced optical systems (e.g., quantum cascade lasers, MPLC-based demultiplexers). His work bridges fundamental optics with practical applications in telecommunications and sensing. Labs/Teams: His research team specializes in optical communication systems, photonic integrated circuits, and computational optics.

Francesc Moll Echetoمشاهده پروفایل

دانشیار

• Energy Harvesting
• Integrated Circuit Design
• Low Power Electronics
• +۵ مورد دیگر

Francesc Moll Echeto is an Associate Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Departament d'Enginyeria Electrònica and the Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona. He leads the HIPICS research group focused on high-performance integrated circuits and systems design. His expertise spans energy harvesting, low-power electronics, process variability management, and secure circuit design. He coordinates the Doctorat en Enginyeria Electrònica program and has coordinated EU-funded projects like the European Processor Initiative (EPI). Education: M.S. in Physics, Universitat de les Illes Balears, 1991 Ph.D. in Electronic Engineering, Universitat Politècnica de Catalunya, 1995 Research Focus: His work addresses energy-efficient computing, including: - Design of circuits tolerant to manufacturing variability - Energy harvesting from mechanical and RF sources - Secure hardware countermeasures against side-channel attacks - RISC-V architecture implementations in advanced technologies - Edge computing and autonomous sensor systems Grants & Collaborations: Coordinator of R&D projects like 'ARQUITECTURA DE COMPUTADORES DE ALTAS PRESTACIONES' (PID2023-146511NB-I00) Part of the Barcelona Zettascale Lab consortium Collaborations with Barcelona Supercomputing Center and industry partners Awards: HiPEAC Paper Award (2023, 2024) for innovations in vector processing and DNN acceleration Labs/Teams: Leads the HIPICS group and the EFRICS subgroup, collaborating on EU-funded initiatives like the European Processor Initiative. Active in open-source silicon projects (e.g., Sargantana RISC-V processor).

• Astrophysics
• Radio Pulsars
• Neutron Stars
• +۴ مورد دیگر

Benjamin Stappers is a Professor of Astrophysics at the University of Manchester's Jodrell Bank Centre for Astrophysics within the School of Physics and Astronomy. His research focuses on radio pulsars, neutron stars, and rapid radio transients. He is part of the European Pulsar Timing Array (EPTA) and International Pulsar Timing Array (IPTA), which aim to detect nanohertz gravitational waves from early universe processes. He co-leads the transients project for LOFAR and heads the pulsar science group for the Square Kilometre Array (SKA). Research interests include using pulsars as probes of gravity and the interstellar medium, and expanding pulsar population studies via LOFAR surveys. His work involves hardware/software development for radio astronomy data analysis. Publications focus on pulsar timing, transients, and gravitational wave detection, with recent work exploring millisecond pulsars and radio transients. Awards include contributions to the Square Kilometre Array's development.

Deborah Talmiمشاهده پروفایل

دانشیار

• Emotional Cognition
• Memory Mechanisms
• Neurobiology of Emotion
• +۷ مورد دیگر

Dr. Deborah Talmi is a University Associate Professor in the Department of Psychology and a Fellow of Lucy Cavendish College at the University of Cambridge. Her research focuses on the cognitive, computational, and neurobiological mechanisms underlying emotional processes, particularly their intersection with memory, perception, and attention. She leads the Emotional Cognition Lab, which employs behavioral experiments, EEG, fMRI, and computational modeling to explore how emotions influence memory formation and retrieval. Roles: Associate Professor (Department of Psychology), Fellow (Lucy Cavendish College), Principal Investigator (Emotional Cognition Lab) Affiliations: School of Biological Sciences, Cambridge Neuroscience Her research investigates questions such as why emotional experiences feel a certain way, how emotion shapes memory, and the neural basis of similarity perception. A recent study demonstrated that emotionally charged stimuli evoke more similar neural representations than neutral ones, even when controlling for thematic content. This work was published in the Journal of Neuroscience and is part of broader efforts to model emotional memory using frameworks like the Bayesian Brain hypothesis. Dr. Talmi collaborates with institutions like the Swiss Centre for Affective Sciences and employs interdisciplinary methods, including animal models of emotional memory with Prof. Amy Milton. She actively mentors PhD students and welcomes volunteers through the SONA platform. Her lab’s findings have implications for understanding chronic pain, decision-making, and mental health. Her work has been featured in The Conversation and TEDx, emphasizing public engagement. She is also committed to advancing education, as seen in her reflections on remote teaching during the pandemic.

• Environmental Epidemiology
• Air Pollution
• Climate Change
• +۶ مورد دیگر

Professor Klea Katsouyanni is a distinguished academic at the National and Kapodistrian University of Athens (NKUA), serving as Professor of Public Health and Medical Statistics and Epidemiology. She holds leadership roles including Director of the Postgraduate Programme in Biostatistics, Head of the Environmental Epidemiology Unit, and Head of the Applied Biostatistics Unit. She also holds a part-time professorship at King's College London and has been affiliated with Imperial College London. Education: She earned a first degree in Mathematics, an MSc in Statistics, and a PhD in Epidemiology from NKUA. She has taught Biostatistics at NKUA’s Medical and Dental Schools for over 35 years. Research Interests: Focus on environmental stressors (air pollution, noise, climate change), epidemiological methods, and health impact assessment. Notable projects include the EU-funded APHEA network, PHEWE, RESPOZE, and ESCAPE projects. Her work has provided foundational evidence on air pollution’s effects on mortality, respiratory health, and cardiovascular outcomes. Awards and Leadership: Member of the WHO committees on air quality guidelines and advisory boards for major environmental health initiatives. She has led ERC review panels and contributed to EU Environmental Health Strategy committees. Teaching and Supervision: Coordinates core courses in Medical Statistics and supervises PhD students in air pollution epidemiology and biostatistics. Active in interdisciplinary programs like the MSc in Air Pollution Science at King's College London.

• Paid and Unpaid Care Work
• Austerity and Neoliberalism in Human Services
• Nonprofit Work and Organization
• +۳ مورد دیگر

Donna Baines is a Professor at the University of British Columbia (UBC) School of Social Work, part of the Faculty of Arts. Previously, she served as Director of the UBC School of Social Work, Chair of the School of Social Work and Social Policy at the University of Sydney, and held professorial roles at Dalhousie University and McMaster University. Her research focuses on paid/unpaid care work, anti-oppressive social work theory, austerity's impact on human services, and nonprofit organizational dynamics. She co-edits *Social Work & Policy Studies: Social Justice, Practice and Theory*. Key research collaborations include SSHRC grants examining Indigenous decolonizing dialogue and age-friendly communities. Her work critiques neoliberalism’s effects on care labor, advocating for emancipatory practices foregrounding Indigenous and marginalized voices. Awards include an Editor’s Choice Article (2024) and recognition in The Hill Times’ Top 100 Books (2022). Publications span over 30 years, addressing topics like resistance in nonprofit care work, post-pandemic social work, and global aging policies. She actively mentors PhD students and engages in critical pedagogy, emphasizing social justice and anti-oppressive frameworks.

• Economic Theory
• Social Networks
• Health Economics
• +۴ مورد دیگر

Yves Zenou is a Professor of Economics at Monash University, Australia, and a part-time professor at the University of Southampton, UK. He is affiliated with the Research Institute of Industrial Economics (IFN), the Center for Economic Policy Research (CEPR), and the Institute for the Study of Labor (IZA). His research focuses on social networks, peer effects, health economics, and development economics, with contributions to understanding vaccine hesitancy, market competition, and juvenile crime dynamics. He is a recipient of prestigious awards including Fellowships from the Econometric Society and the Academy of the Social Sciences in Australia. Yves Zenou’s research spans interdisciplinary topics, emphasizing the interplay between social structures and economic outcomes. His work on peer effects and spatial interactions has advanced theoretical frameworks, while empirical studies address real-world challenges like public health interventions. He actively supervises PhD students and collaborates internationally through research institutes and networks.

Azadeh Ansariمشاهده پروفایل

دانشیار

• Nano/Micro-Electro-Mechanical Systems (N/MEMS)
• RF Applications
• Resonant Devices
• +۳ مورد دیگر

Azadeh Ansari is an Associate Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology, holding the Sutterfield Family Early Career Professorship. She received her B.S. from Sharif University of Technology (2010), and M.S. and Ph.D. from the University of Michigan (2013, 2016), followed by a postdoctoral fellowship at Caltech (2016–2017). Her research focuses on nano/micro-electro-mechanical systems (N/MEMS), with emphasis on III-V semiconductors and piezoelectric materials. Key areas include resonant devices for RF applications, nonlinear devices, and integrated microsystems. Ansari leads projects in microscale robotics, phononic frequency combs, and III-V electro-acoustic devices. Research Interests: Resonant devices for timing, sensing, and RF applications III-V mm-wave acoustic filtering Microscale robot design and control Nonlinear resonators and phononic frequency combs III-V electro-acoustic devices and HEMTs Her recent work includes collaborations with NASA JPL on extraterrestrial micro-swimmers and DARPA-funded projects on inertial sensors and high-temperature pressure sensors. Ansari has secured grants from DARPA DSO and presented at IEEE Transducers 2025 with four papers. She advises graduate students such as Zhijian (Chris) Hao, who defended his PhD in 2024. Ansari’s awards include the 2017 ProQuest Distinguished Dissertation Award and the University of Michigan Towner Prize (2016). She serves on the IEEE Sensor’s Young Professional Committee and technical committees for IEEE IFCS 2018. Lab and Collaborations: The Ansari Lab is part of Georgia Tech’s Institute for Electronics and Nanotechnology. Collaborators include Prof. Kimberly Hoang (PBS-featured neurosurgery micro-drillers) and teams at Penn State University. Current projects include DARPA-funded frequency comb inertial sensors and underwater micro-robot sensor development for ICRA 2025.

Igo J.M. Besselinkمشاهده پروفایل

دانشیار

• Vehicle Dynamics
• Tire Behavior Modeling
• Battery Electric Vehicles
• +۳ مورد دیگر

Igo J.M. Besselink is an Associate Professor and Chair of Vehicle Dynamics in the Department of Mechanical Engineering at Eindhoven University of Technology (TU/e). His research focuses on vehicle dynamics analysis, tire behavior modeling, battery electric vehicles, and vehicle control systems. He leads the Automotive Technology lab, emphasizing experimental validation of simulation models to enhance transport safety and efficiency. Academically, he holds an MSc from Delft University of Technology (TU Delft, 1990) and a PhD from TU Delft (2000). He worked at Fokker Aircraft (landing gear dynamics) and TNO Automotive before joining TU/e in 2002 as a part-time lecturer, transitioning to full-time roles as Assistant Professor (2008) and Associate Professor (2016). Research interests include dynamics of commercial vehicles, autonomous operation in confined areas, and sustainable transportation. He has supervised 6 PhD and over 80 Master students, authored/co-authored over 50 publications, and serves on the Editorial Board of Vehicle System Dynamics . Recent work emphasizes neural network-based vehicle behavior estimation, cooperative platoon control, and criticality measures for automated vehicle testing. His lab develops test rigs and prototypes to bridge simulation and real-world performance.

• Statistical Signal Processing
• Pattern Recognition
• Machine Learning
• +۵ مورد دیگر

Ulisses Braga-Neto is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, part of the College of Engineering. He holds a Ph.D. from The Johns Hopkins University (2002), with earlier degrees including an M.S. from the Federal University of Pernambuco (1992). His research focuses on statistical signal processing, pattern recognition, and machine learning, with applications in bioinformatics, materials informatics, and environmental modeling. He leads the TAMIDS Scientific Machine Learning Lab and has authored over 100 publications. Key research areas include physics-informed neural networks for environmental and engineering problems, error estimation in classification systems, and gene regulatory network inference. His recent work emphasizes machine learning applications in agriculture (e.g., cotton detection in corn fields using UAS), CO2 sequestration modeling, and wildfire prediction. He has contributed to foundational texts like Error Estimation for Pattern Recognition (Wiley-IEEE, 2015). Prof. Braga-Neto's interdisciplinary approach bridges computer science, engineering, and biology. His lab develops algorithms for data-poor environments, with applications in genomics, proteomics, and metagenomics. He advises graduate students through Texas A&M's ECE program, emphasizing rigorous statistical methods alongside machine learning innovation.

Quan Zhouمشاهده پروفایل

استادیار

• Markov chain Monte Carlo sampling
• Bayesian methodology
• Variable selection
• +۷ مورد دیگر

Quan Zhou is an Assistant Professor in the Department of Statistics at Texas A&M University, part of the College of Arts & Sciences. His research focuses on developing advanced sampling methods, particularly Markov chain Monte Carlo (MCMC) algorithms, with applications in Bayesian methodology, variable selection, stochastic optimization, and statistical genetics. He holds a BS from Fudan University and a PhD from Baylor College of Medicine, followed by a postdoctoral fellowship at Rice University. He teaches courses such as Mathematical Probability, Multivariate Analysis, and Advanced Stochastic Processes. Notable contributions include work on informed MCMC samplers, Schrödinger bridge theory, and high-dimensional structure learning. He advises PhD students like Hyunwoong Chang (now at UT Dallas) and Guanxun Li (Beijing Normal University). Active in academic service, he served as President of the Southeastern Texas Chapter of the American Statistical Association (SETCASA).

Seth Sullivantمشاهده پروفایل

استاد

• Algebraic Statistics
• Computational Algebra
• Combinatorics
• +۳ مورد دیگر

Seth Sullivant is a Distinguished Professor in the Department of Mathematics at North Carolina State University (NC State), within the College of Sciences. His research focuses on algebraic statistics, computational and combinatorial algebra, and mathematical phylogenetics. He holds a Ph.D. in Mathematics from the University of California, Berkeley (2005). His expertise spans interdisciplinary areas, including algebraic approaches to statistical problems, combinatorial methods in phylogenetics, and the development of algebraic tools for graphical models. He is affiliated with research groups in Algebra and Combinatorics, Mathematical Biology, and Symbolic Computation at NC State. Recent research trends in his publications emphasize the application of algebraic geometry and combinatorics to statistical models, phylogenetic network analysis, and identifiability problems in systems biology. His work bridges abstract mathematical concepts with practical statistical methodologies, addressing challenges in data analysis and model interpretation. No specific scientific awards are listed in the provided texts. His advising and grant activities are not detailed here, though his extensive publication record suggests active research collaborations. He is part of research teams focused on advancing algebraic methods in statistics and computational biology.