جست‌وجوی استاد و پژوهشگر

• Strategic Sales Management
• Customer Relationship Management (CRM)
• Marketing Communications
• +۳ مورد دیگر

Thomas E. DeCarlo , Ph.D., is the Ben S. Weil Endowed Chair of Industrial Distribution and Professor of Marketing and Industrial Distribution at the University of Alabama at Birmingham since 2009. He previously served at Iowa State University (1993-2006) and earned his Ph.D. in Business from the University of Georgia (1993) and BA in Accounting from North Carolina State University (1982). Research focus on strategic sales management , customer relationship management , and marketing communications Key methodologies: in-depth interviews , field experiments , and multivariable regression analysis Research Trends : His 15 most recent publications (2015-2025) examine: Salesperson ambidexterity and stress dynamics Consumer suspicion and persuasion knowledge Digital crowdfunding strategies Internal selling process optimization Service ecosystem theory in B2B contexts Scientific Awards : Recognized for outstanding teaching Multiple business impact awards Professional Activities : Served as Interim Department Chairperson (2014-2015) and ID Faculty Search Chair (2020). Actively reviews for journals like European Journal of Marketing and Industrial Marketing Management .

Juan Manuel Cebrian Gonzalezمشاهده پروفایل

استادیار

• Computer Architecture
• Parallel Computing
• Power Management
• +۴ مورد دیگر

Juan Manuel Cebrian Gonzalez is an Assistant Professor at the Department of Computer Engineering and Technology, Faculty of Informatics, University of Murcia. His work focuses on computer architecture, parallel systems, and energy-efficient computing. Doctorate: University of Murcia (2011), thesis on fine-grain power and thermal management in multicore processors. Research interests: Designing architectural mechanisms for optimizing power consumption and thermal management in multicore systems, cache coherence in parallel architectures, and vectorization techniques for high-performance computing. His work also explores heterogeneous architectures, fault tolerance, and efficient memory systems. Recent article trends: Focus on cache management, speculative execution, lock-free constructs, and performance-energy trade-offs in edge and heterogeneous computing. Key methodologies include gem5 simulation, Arm SVE, and AVX-512 vectorization. Collaboration: Supervised by Dr. Juan Luis Aragón Alcaraz and Dr. Stefanos Kaxiras. Active in the Computer Architecture and Parallel Systems research group.

Y. Charlie Huمشاهده پروفایل

استاد

• Mobile Systems
• Distributed Systems
• Operating Systems
• +۵ مورد دیگر

Y. Charlie Hu is the Michael and Katherine Birck Professor of Electrical and Computer Engineering and Professor of Computer Science (by courtesy) at Purdue University, where he leads the PurNET Lab and contributes to the Systems and Networking Group. His research spans Mobile Systems, Distributed Systems, Operating Systems, and Computer Networks , with a focus on energy-efficient AI systems and edge computing. His groundbreaking work on smartphone energy management has been widely adopted by the mobile industry and recognized with multiple test-of-time awards , including from ACM SIGOPS and ACM SIGMOBILE . He has received prestigious honors like the NSF CAREER Award , Honda Initiation Grant , and industry accolades from Google Research and Qualcomm . Notable Funded Projects: NSF's NeTS: Black-box Optimization of White-box Networks (2023-2026) Intel -NSF's SPLICE initiative His research has produced 15+ PhD graduates now in academia (University of Arizona, Virginia Tech) and industry (Google, Apple, Qualcomm). The articles reflect a career-long focus on edge computing , 5G network optimization , and energy-aware systems , with recurring themes in mobile AR/VR , video analytics , and network protocol design . Scientific Awards Honda Initiation Grant NSF CAREER Award Purdue Early Career Research Award Google Research Award Qualcomm Faculty Award ACM SIGOPS EuroSys Best Student Paper Award ACM MobiCom Best Community Paper Award IEEE Fellow ACM Distinguished Scientist Purdue PRF Innovator Hall of Fame

Christopher Paul Andersonمشاهده پروفایل

استادیار

• Quantum Physics
• Quantum Engineering
• Materials Science
• +۵ مورد دیگر

Christopher Paul Anderson is an Assistant Professor affiliated with the University of Illinois at Urbana-Champaign, holding joint appointments in the Departments of Materials Science and Engineering, Physics, and Electrical and Computer Engineering. He is also associated with the Micro and Nanotechnology Lab and the Materials Research Lab. His research focuses on quantum systems, semiconductor materials, and spintronics, particularly exploring defect qubits in materials like silicon carbide and diamond. Anderson leads a team advancing quantum coherence times and applications in quantum computing/sensing. Research Interests : Quantum Coherence and Control Defect-Based Qubits (e.g., Spin Qubits in Diamond, Silicon Carbide) Electro-Optic and Piezoelectric Materials for Quantum Technologies Photoluminescence and Magnetic Materials Key Achievements : Recipient of the NSF CAREER Award (2025) Author of over 36 peer-reviewed publications, including work on tin-vacancy qubits, microwave spin control, and quantum critical materials. Labs/Teams : Anderson’s work is conducted in the Micro and Nanotechnology Lab and Materials Research Lab, focusing on experimental and theoretical advancements in quantum materials.

Lesley Shannonمشاهده پروفایل

دانشیار

• Computer Engineering
• Reconfigurable Computing
• FPGA CAD Tools
• +۶ مورد دیگر

Lesley Shannon is an Associate Professor in the School of Engineering Science at Simon Fraser University (SFU), specializing in computing system design and reconfigurable computing. She leads the Reconfigurable Computing Lab (RCL), focusing on FPGA-based architectures, heterogeneous multicore systems, and CAD tools. Her academic journey includes a B.Sc. from the University of New Brunswick (1999), M.A.Sc. and Ph.D. from the University of Toronto (2001 and 2006). Her research spans FPGA CAD algorithms, Networks-on-Chip (NoCs), dynamic partial reconfiguration (DPR), and application-specific architectures. Key projects include FUSE (OS abstraction for hardware accelerators), PolyBlaze (multicore system emulation), and uROAMs (microfluidic reconfigurable devices). She has secured funding from NSERC, Xilinx, and Altera, among others. Education: B.Sc., Electrical Engineering (Computer Option), University of New Brunswick, 1999 M.A.Sc., Applied Science, University of Toronto, 2001 Ph.D., Applied Science, University of Toronto, 2006 Roles: NSERC Chair for Women in Science and Engineering (BC/Yukon) Faculty Advisor, SFU WEST (Women in Engineering, Science, and Technology) Her lab employs 5 current students and has graduated 7, including work on FPGA CAD, microfluidics, and embedded systems. Courses taught include Advanced Digital Systems Design and Real-Time/Embedded Systems. Her research emphasizes reducing design time through on-chip profiling and CAD tools, with applications in biomedical imaging and quantum computing. Awards & Grants: NSERC Discovery Grant NSERC Strategic Grant (Lead PI, 2009; Co-PI, 2010) SFU Startup Grant and President’s Research Grant Lab & Collaborations: The RCL develops silicon and non-silicon architectures, including quantum computing and microfluidic systems. Partnerships include industry collaborations and open-source tools like Odin II synthesis framework.

James R. Greenمشاهده پروفایل

استاد

• Machine Learning
• Biomedical Informatics
• Computational Biology
• +۹ مورد دیگر

James R. Green is a Professor in the Department of Systems and Computer Engineering at Carleton University , where he has been a faculty member since 2005. He holds a PhD from Queen's University and is a licensed Professional Engineer (P.Eng.) and Senior Member of IEEE. His work integrates machine learning, biomedical informatics, and high-performance computing. His educational background includes: B.A.Sc. in Systems Design Engineering, University of Waterloo (1998) M.Sc.(Eng.), Queen's University (2000) PhD, Queen's University (2005) Dr. Green's research focuses on machine learning challenges in biomedical informatics , particularly class imbalance and rare event prediction. Key areas include protein structure, function, and interaction prediction; microRNA detection in unique species; non-contact neonatal monitoring; and accelerating scientific computing via parallel architectures like the Cell BE processor. His lab has developed several widely used bioinformatics tools such as PIPE, ProtDCal, and PCI-SUMO. His recent publications reflect a strong trend in computational biology and machine learning , with applications in proteomics, genomics, and medical diagnostics. He has published over 100 peer-reviewed papers and secured funding from NSERC, CIHR, CFI, ORF, OCE, MITACS, and IBM. Scientific and teaching recognitions include: Three teaching awards NSERC Best Project Award (twice: 2006-2007 and 2007-2008) Multiple student projects resulting in conference papers (e.g., CMBEC) He has supervised numerous undergraduate capstone projects in areas such as assistive technologies, robotic systems, and bioinformatics. His teaching portfolio includes courses in Pattern Classification, Machine Learning, Computer Architecture, and Biomedical Engineering. He leads an active research group that bridges computer engineering and life sciences, fostering interdisciplinary collaboration. Lab and research team initiatives include: Development of open-access web servers for protein analysis Collaborations with biologists and clinicians Integration of hardware and software for medical applications

Dana S. Nauمشاهده پروفایل

استاد

• Automated Planning
• Game Theory
• Artificial Intelligence
• +۳ مورد دیگر

Dana S. Nau is a Professor in the Department of Computer Science and a member of the Institute for Systems Research at the University of Maryland. He is renowned for his contributions to automated planning and game theory, including landmark algorithms like SHOP and foundational studies on game-tree pathology and strategic planning in computer bridge. With over 500 refereed publications and an H-index of 61, his work bridges theoretical computer science and practical applications in multiagent systems and evolutionary game theory. His research interests include hierarchical task network (HTN) planning, Bayesian network inference techniques, and the evolution of social norms through evolutionary game theory. Recent work focuses on spatial evolutionary games, surrogate Bayesian models, and strategic communication in multiagent environments. Awards: AAAI Fellow (202?), ACM Fellow (202?) Key Collaborations: Co-authored papers with leaders like Malik Ghallab (LAAS-CNRS), Satyandra K. Gupta (USC), and Vincent Hsiao (Bayesian networks research). Grants/Advising: Supervised students including Sunandita Patra (17+ joint papers) and Ruoxi Li, contributing to HTN planning and reinforcement learning advancements. His labs and research teams actively explore AI planning systems, probabilistic reasoning, and the intersection of game theory with social science phenomena like gossip evolution.

Dominic Pjontekمشاهده پروفایل

دانشیار

• Multiphase reactor engineering
• CO2 conversion and utilization
• Bio-oil upgrading
• +۷ مورد دیگر

Dominic Pjontek is an Associate Professor in the Department of Chemical and Biochemical Engineering within the Faculty of Engineering at Western University. He is based in Room 377 of the Thompson Engineering Building and serves as an active researcher and educator in multiphase reactor engineering. His work is conducted both on the Western University campus and at the Institute for Chemicals and Fuels from Alternative Resources (ICFAR), a specialized facility for sustainable technology development. Dr. Pjontek received his Ph.D. and B.A.Sc. in Chemical Engineering from the University of Ottawa, where he earned multiple prestigious scholarships including the NSERC Postgraduate Scholarship for Doctoral Studies and the University of Ottawa Excellence Scholarship for Graduate Studies. His research focuses on the development and optimization of multiphase reactors through experimental studies, process modeling, and scale-up considerations. Key research areas include CO 2 conversion/utilization using gas-liquid-solid reactors, fundamental understanding of interfacial area and flow behavior in multiphase reactors, and innovative sustainable technologies for converting waste streams to value-added products. His work addresses critical technological barriers in developing next-generation reactors for sustainable chemical production. Analysis of Dr. Pjontek's recent publications reveals a strong trend toward carbon dioxide conversion technologies, fluid coker optimization, and sustainable process development. His research group has published extensively on gas-liquid-solid fluidized beds, reactor fouling mechanisms, and CO 2 hydrogenation processes, with increasing focus on sustainable chemical production methods that align with global decarbonization efforts. Scientific Awards and Recognitions: R. Mohan Mathur Award for Excellence in Teaching (2018) Maurice Bergougnou Teaching Award for Heat Transfer Operations (2015-2018) NSERC Postgraduate Scholarship for Doctoral Studies Multiple University of Ottawa Excellence Scholarships NSERC Canada Graduate Scholarship for Master's Studies Dr. Pjontek actively supervises numerous graduate students working on cutting-edge projects related to multiphase reactor engineering. His research group includes multiple Ph.D. and M.E.Sc. students working on projects such as CO 2 conversion to commodity chemicals, biosurfactant production, fluid coker heater modifications, and stripper shed fouling monitoring. He has successfully graduated numerous students who have completed theses on topics including fluid coker cyclone fouling, hydrodeoxygenation processes, and particle agglomeration phenomena. His research is supported through collaborations with industry partners like Syncrude Canada Ltd. and Origin Materials, as well as government funding agencies. Dr. Pjontek's laboratory work is conducted within the Chemical and Biochemical Engineering facilities at Western University, with specialized equipment for studying multiphase reactor systems. His research group maintains collaborations with other faculty members including Cedric Briens, Lars Rehmann, and Jose Herrera, forming a strong research cluster focused on sustainable process engineering and reactor technology development.

• Distributed Systems
• Cybersecurity
• Sports Technology
• +۷ مورد دیگر

Dag Johansen is a Professor in the Department of Informatics at UiT The Arctic University of Norway, Tromso campus. His work spans multiple research areas at the intersection of computer science, sports science, medicine, health technology, and nutrition science. He leads the interdisciplinary "Corpore Sano" research center and is actively involved in several research groups including the Cyber Security Group (CSG) and Crime Control and Security Law. Professor Johansen's research focuses on developing fundamental software solutions for secure and error-free data processing in heterogeneous distributed systems, ranging from lightweight "Internet of Things" devices and mobile phones to large-scale cloud solutions. His work particularly emphasizes applications in sports technology, edge computing, and compliance technology. His research interests include distributed systems, cybersecurity, sports technology, edge computing, data privacy, AI for sports analytics, multimedia forensics, and compliance technology. His recent publication trends show a strong focus on AI applications for sports video analysis, particularly in soccer and ice hockey, where his team has developed AI-based cropping systems for social media representations. He also has significant work in data privacy and GDPR compliance, especially regarding the "third country problem," as well as applications of AI in sustainable fishing practices. His 2024-2025 publications demonstrate continued work in self-healing microservices, lightweight encryption for video feeds, and virtual reality training environments. Professor Johansen is actively involved in mentoring students and research collaborators, as evidenced by his extensive publication record with numerous co-authors including doctoral students and postdoctoral researchers. His work has received funding through various research projects focused on data analytics, privacy technology, cybersecurity, and sports technology applications. He leads the interdisciplinary "Corpore Sano" center, which brings together researchers from computer science, sports science, medicine, health technology, and nutrition science. His work also involves collaboration with the "Njord" project focused on sustainable fishing through AI applications, and he's involved in developing the "Áika" distributed edge system for AI inference.

• CMOS integrated circuits
• Computer architecture
• Electrical and electronic engineering
• +۱۲ مورد دیگر

Maurizio Zamboni is a Full Professor at the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, where he also serves as Student Ombudsman. His academic career spans over three decades with continuous teaching and research contributions in electronics and computing fields. Professor Zamboni's research interests focus on cutting-edge areas including CMOS integrated circuits, computer architecture, quantum computing, semiconductor devices, and VLSI design. His work particularly emphasizes emerging nanotechnologies for digital microelectronic architectures and the design of high-performance or low-consumption processing systems. He has developed expertise in circuit architectures for probabilistic computing, logic-in-memory computing, magnetic devices, and quantum architectures. His recent publications (2021-2025) reveal a strong trend toward quantum computing applications, in-memory processing architectures, and novel approaches to overcoming the memory wall problem. These works span both theoretical algorithm development and practical hardware implementations, with significant focus on quantum annealing, FPGA-based quantum emulation, and memory-mapped processing architectures. Professor Zamboni has been actively supervising PhD students working on quantum computing algorithms, hardware AI accelerators for automotive applications, and quantum-related optimization approaches. He leads research within the VLSILAB Group at DET, focusing on the intersection of nanoelectronics, quantum computing, and advanced computer architectures. His work bridges theoretical computer science with practical electronic design, creating novel solutions for next-generation computing challenges.

Kaiming Biمشاهده پروفایل

استادیار

• Infectious Disease Modeling
• Epidemic Forecasting
• Public Health Decision-Making
• +۱۲ مورد دیگر

Kaiming Bi, Ph.D., is an Assistant Professor in the Department of Management, Policy & Community Health at the University of Texas Health Science Center at Houston (UTHealth Houston) School of Public Health . As an affiliated member of the Center for Health Care Data , his research bridges quantitative methods and public health, focusing on infectious disease modeling , epidemic forecasting , and data-driven health policy . B.S. in Mathematics from Northeastern University (2015) Ph.D. in Industrial Engineering from Kansas State University (2020) Postdoctoral training at University of California San Diego School of Medicine (2020-2021) and University of Texas at Austin (2021-2024) His methodological expertise spans mathematical modeling , machine learning , and optimization , applied to diverse public health challenges including respiratory infections , vector-borne diseases , STIs , and the opioid epidemic . Recent work includes modeling SARS-CoV-2 Omicron subvariants , population immunity dynamics , and multi-pathogen burden projections for the 2023-2024 US winter season. Dr. Bi has received prestigious accolades such as the Pencis Best Researcher Award (2021) and IISE Best Paper (2018). He previously taught graduate courses in Integer Programming , Information Systems , and Industrial Simulation at Kansas State University. Currently leading the Big-data and Infectious Disease Modeling Lab (BI Lab) , he seeks STEM-motivated PhD students to develop computational solutions for epidemic control.

Tanvir Arafinمشاهده پروفایل

استادیار

• Hardware Security
• Trusted Computing
• IoT Security
• +۴ مورد دیگر

Tanvir Arafin serves as an Assistant Professor in the Department of Cyber Security Engineering at George Mason University, where his research focuses on hardware security and trust mechanisms for emerging computing platforms. With publications in premier venues including IEEE Transactions on Very Large Scale Integration Systems, IEEE Transactions on Computers, and ACM International Conference on Computer-Aided Design, he addresses critical security challenges in next-generation systems through rigorous hardware-software co-design approaches. His research portfolio spans Hardware Security, Trusted Computing, and IoT Security, with specialized expertise in Side-Channel Attacks and Secure Hardware Design. Dr. Arafin investigates electromagnetic side-channel vulnerabilities in O-RAN networks, develops countermeasures for autonomous vehicle cybersecurity, and pioneers RRAM-based security solutions for memory-constrained devices. His work bridges theoretical security models with practical implementations, emphasizing real-world applicability in edge computing environments and autonomous navigation systems. Current projects explore machine learning integration for anomaly detection in connected vehicles and secure acceleration of cryptographic operations. Analysis of Dr. Arafin's 2022-2025 publications reveals strategic focus areas: electromagnetic fingerprinting for radio units in O-RAN (2025), spatial acceleration of Kolmogorov-Arnold Networks (2025), and NTT-based cryptography accelerators (2024). His research demonstrates consistent innovation in securing autonomous navigation systems and edge devices, with emerging work on in-memory computing architectures using resistive memory technologies. Key trends include hardware-centric defense against model inversion attacks, voltage overscaling for lightweight authentication, and robust multi-robot coordination in dynamic environments. Scientific Awards: No scientific awards, fellowships, or medals were documented in the source materials. Dr. Arafin leads significant collaborative research, including the NSF CISE-MSI grant (DP: CNS) for edge-based robust multi-robot systems. His educational initiatives feature Capture-the-Flag competitions targeting underrepresented students in cybersecurity. Current grant activities emphasize practical security solutions for autonomous navigation, multi-robot coordination, and IoT edge devices, with demonstrated focus on translating research into deployable countermeasures for real-world threats in dynamic operational environments.

• Embedded real-time systems
• Computer architectures
• Hardware/software co-design for IoT
• +۵ مورد دیگر

Tiago Manuel Ribeiro Gomes is an Assistant Professor at the Department of Industrial Electronics within the School of Engineering at the University of Minho, Portugal. He is also a Senior Researcher at Centro ALGORITMI and a member of both the IE R&D Group and the ESRG R&D Lab. Holding a Ph.D. in Electronics and Computers Engineering, his research focuses on embedded real-time systems, computer architectures, and hardware/software co-design for IoT devices. Academic Degree: Ph.D. in Electronics and Computers Engineering Current Position: Assistant Professor, School of Engineering, University of Minho Gomes has led extensive research in IoT systems over 15 years, particularly in hardware acceleration for automotive LiDAR sensors, secure embedded systems, and efficient OS frameworks for low-end devices. His work includes the EU-funded CROSSCON project and spans hardware-assisted security, dynamic binary translation, and wireless sensor networks. Recent publications highlight his expertise in automotive sensor technology, with articles like FOG-Zip for LiDAR compression, SecureQNN for TinyML security, and Hardware-Assisted Range Image Generation for LiDAR processing. His work bridges IoT, embedded systems, and cybersecurity, focusing on real-time performance and hardware-software co-design. Projects include the development of reliable/secure automotive sensor solutions and EU project CROSSCON. He contributes to open-source frameworks like UTango for IoT security and investigates heterogeneous fault tolerance architectures using Arm/RISC-V processors. Labs: IE R&D Group, ESRG R&D Lab Education: Ph.D. in Electronics and Computers Engineering, Master’s in Telecommunications Engineering (both from University of Minho)

• Medical Informatics
• Statistical Science
• Bioinformatics
• +۵ مورد دیگر

Dr. Masato Inoue is a Professor at the Faculty of Science and Engineering , School of Advanced Science and Engineering at Waseda University. He holds a Doctor of Medical Science from Kyoto University. Education: 2003 - Kyoto University Graduate School of Medicine 2003 - Kyoto University His research spans multiple disciplines at the intersection of Medical Informatics , Bioinformatics , and Statistical Mechanics . Key areas include: Medical Imaging : Developing Bayesian super-resolution algorithms and Prior Ensemble Learning for improved MRI reconstruction Voice Analysis : Creating innovative voice quality quantification systems for clinical diagnostics Genetic Analysis : Advancing haplotype inference methods and gene network modeling Signal Processing : Applying statistical mechanics to diverse problems from coding theory to neuroscience His recent publications (2021-2012) demonstrate consistent contributions to medical imaging algorithms , voice disorder classification , and genetic data analysis . Notable collaborations include work with Kyoto University researchers , Swedish medical institutions , and cross-disciplinary teams in bioengineering.

• Heterogeneous Catalysis
• Catalytic Processes
• Environmental Catalysis
• +۳ مورد دیگر

Fabio H. Ribeiro is the William Nicholas and Elizabeth Holstein Delgass Distinguished Professor of Chemical Engineering at Purdue University's Davidson School of Chemical Engineering. He serves as Director of the Center for Innovative and Strategic Transformation of Alkane Resources (CISTAR). His research focuses on heterogeneous catalysis, particularly in catalytic combustion, NOx traps, biomass-to-fuels conversion, and low-temperature water-gas shift reactions. He has advised over a dozen graduate students and collaborates with industry partners. Education: B.S. Chemical Engineering, Instituto Militar de Engenharia, Brazil (1982) M.S. Chemistry, Instituto Militar de Engenharia, Brazil (1984) M.S. & Ph.D. Chemical Engineering, Stanford University (1986–1989) Research Interests: His group combines experimental and computational methods to study catalyst kinetics and design. Key areas include catalyst stability under dynamic conditions, industrial process optimization, and sustainable energy solutions. Techniques involve surface science, microkinetic modeling, and operando spectroscopy. Publications: Recent work emphasizes catalytic dehydrogenation of light alkanes, NOx selective catalytic reduction, and shale gas upgrading. Themes include catalyst structure-reactivity relationships and reaction mechanisms. Awards: Herman Pines Award (2015) AIChE Fellow (2014) Purdue Research Excellence Award (2014) Lab & Teams: Leads CISTAR, a NSF Engineering Research Center, and collaborates with the Purdue Catalysis Center. Active in developing catalysts for renewable energy and pollution control.