جست‌وجوی استاد و پژوهشگر

Alessandro Toniمشاهده پروفایل

استاد پژوهشی

• Social Psychology
• Developmental Psychology
• Attachment Theory
• +۷ مورد دیگر

Alessandro Toni is a Research Professor at the Department of Social and Economic Sciences, Sapienza University of Rome. He teaches courses such as Psychology in Social Services and Social Psychology , coordinating exams and student advising. His office hours and course schedules are regularly updated via institutional platforms like Google Classroom. His research spans social and developmental psychology, with emphases on: Attachment theory and early-life experiences, including child abuse impacts Cognitive and attributional processes in moral development Emotional regulation, alexithymia, and mindfulness Leadership styles and interpersonal communication He employs quantitative methods to study psychosocial disorders, parenting dynamics, and trauma outcomes. Publications (2019–2025) focus on moral disengagement, emotional skills mediation, and psychosocial distress. Trends include longitudinal analyses of attachment styles, intergenerational trauma transmission, and pandemic-related mental health crises. No awards or funded grants are documented.

• Pigmentary Disorders
• Skin of Color
• Dermatology
• +۳ مورد دیگر

Dr. Nisma Mujahid serves as a Clinical Assistant Professor in the Department of Dermatology at the University of Utah, providing specialized care at University of Utah Hospital and Stansbury Health Center. Her clinical expertise centers on pigmentary disorders in diverse populations, with strong commitment to medical education and research. Her academic foundation includes: MD, PhD from Boston University School of Medicine Dermatology Residency at University of Utah Spencer Fox Eccles School of Medicine Internal Medicine Internship at University of Florida B.S. in Biochemistry and Pre-Medicine from Mississippi State University Dr. Mujahid's research critically examines pigmentary disorders including vitiligo and lichen planus pigmentosa, with specialized focus on skin of color and multi-ethnic dermatology . Her work bridges clinical practice and translational science, addressing therapeutic gaps in conditions affecting underrepresented populations while investigating systemic issues like gender representation in academic dermatology. Analysis of her publication record reveals three dominant research trajectories: molecular mechanisms of pigmentation (particularly UV-independent pathways), clinical interventions for scarring disorders, and health equity studies. Her interdisciplinary approach spans human dermatology, veterinary comparative models, and evidence-based procedural reviews. No scientific awards were documented in the provided materials. She actively mentors dermatology residents and medical students, with patient feedback averaging 4.9/5 across 389 reviews highlighting her clinical thoroughness and patient-centered communication, though occasional notes mention scheduling challenges. Her educational leadership extends to curriculum development in pigmentary disorders and skin of color.

Faiz Hamidمشاهده پروفایل

دانشیار

• Operations Research
• Combinatorial Optimization
• Network Optimization
• +۳ مورد دیگر

Faiz Hamid serves as an Associate Professor in the Department of Management Sciences at Indian Institute of Technology Kanpur. With a Ph.D. in Decision Sciences & Information Systems from IIM Lucknow (2012) and a B.Tech. in Computer Science and Engineering from Institute of Engineering & Management (2007), he brings strong technical and analytical expertise to his academic position. His research interests span Operations Research, Combinatorial Optimization, Network Optimization, and Data Science, with particular focus on transportation systems, pandemic response modeling, and revenue management applications. Dr. Hamid's scholarly work demonstrates consistent publication in high-impact journals including European Journal of Operational Research, Omega, Transportation Research, and IEEE Transactions on Signal Processing. His recent publications reveal a strong trend toward applying optimization techniques to real-world problems, particularly addressing pandemic-related challenges in transportation systems and developing sophisticated mathematical models for railway operations. His 2024 edited volume 'Optimization Essentials: Theory, Tools, and Applications' demonstrates his leadership in the field. Ph.D. Thesis recognized as runner-up for 2014 Best Dissertation Award by The INFORMS Technical Section in Telecommunications Best Paper Award at COSMAR 2010 Doctoral Conference, Indian Institute of Science, Bangalore Professor Dipak C Jain Best Paper Award at IMR Doctoral Conference 2010, IIM Bangalore Silver Medal, National Mathematics Olympiad 2002 Dr. Hamid has advised numerous students and collaborated extensively with researchers globally, particularly in transportation optimization problems. His professional journey includes industry experience as Associate Functional Architect at JDA Software and post-doctoral research at Telecom SudParis, France, before joining IIT Kanpur's faculty.

Marco L. Della Vedovaمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence and Machine Learning
• Interpretable and Explainable AI
• Geospatial AI
• +۷ مورد دیگر

Marco L. Della Vedova is a Senior Lecturer in Applied Artificial Intelligence at Chalmers University of Technology, Sweden. He works in the Vehicle Engineering and Autonomous Systems division within the Department of Mechanics and Maritime Sciences, as part of Prof. Mattias Wahde's research group. Since 2025, he has served as Director of the Data Science and AI master's programme (MPDSC) at Chalmers, where he teaches courses including Introduction to Artificial Intelligence and Digitalization in Sports. Dr. Della Vedova earned his academic foundation at the University of Pavia, Italy, where he completed his BSc (2006), MSc (2009), and PhD (2013) in Computer Engineering. His doctoral research focused on "Real-Time Physical Systems and Electric Load Scheduling" under Prof. Tullio Facchinetti. During his PhD studies, he spent a year at U.C. Berkeley hosted by Prof. Francesco Borrelli at the Model Based Predictive and Distributed Control Lab. His research spans multiple AI domains with a strong emphasis on interpretability. Dr. Della Vedova develops interpretable methods for conversational AI, naturalness evaluation of forests using canopy height models, and geospatial applications. His work bridges theoretical AI with practical societal benefits, particularly in environmental monitoring, transportation systems, and orienteering. He has previously contributed to cloud computing, hate speech detection, and cyber-physical energy systems, demonstrating his interdisciplinary approach to AI research. Dr. Della Vedova's publication record reveals a consistent trajectory of impactful research across multiple domains of artificial intelligence. His recent work shows a strong focus on interpretability in AI systems, with significant contributions to natural language processing, geospatial analysis, and causal inference. The research demonstrates both theoretical depth and practical applications, particularly in environmental monitoring and social media analysis. His methodology often combines traditional machine learning approaches with novel interpretability techniques, creating bridges between complex AI systems and human understanding. Dr. Della Vedova has received several prestigious recognitions for his work: Best PhD thesis award from the Order of the Engineers of Bergamo (2013) Italian champion of Il Cervellone (2012) Top Italian performer in IEEEXtreme 6.0 programming competition (148th overall globally, 2012) Premio Arturo Schena award from Fondazione Credito Valtellinese (2010) With over 50 students supervised through bachelor's and master's theses, Dr. Della Vedova has established himself as a dedicated mentor in the AI community. His current PhD students include Minerva Suvanto working on interpretable NLP and Vivien Lacorre developing AI for railway infrastructure inspection. His supervision spans diverse topics from forest naturalness evaluation to hate speech detection and transportation optimization. Beyond formal supervision, he actively contributes to educational initiatives including serving as Director of Chalmers' Data Science and AI master's program and developing innovative teaching methods that connect theoretical concepts with real-world applications. Dr. Della Vedova is deeply embedded in both academic and professional communities. He leads the Applied Artificial Intelligence research group at Chalmers while maintaining strong connections with European research networks through projects like the ERASMUS+ EUrienteering initiative. His interdisciplinary approach is reflected in collaborations across computer science, environmental science, and social sciences. Notably, he applies his AI expertise to orienteering both as a researcher developing localization methods and as a licensed Event Advisor for the International Orienteering Federation, demonstrating how his professional and personal interests converge in innovative ways.

• Information Visualization
• Data Visualization
• Human-Computer Interaction
• +۴ مورد دیگر

Dr. Stuart Marshall serves as Associate Dean of Academic Development in the Faculty of Science and Engineering at Victoria University of Wellington - Te Herenga Waka, where he also holds the academic rank of Senior Lecturer. Previously, he served as Head of School for the School of Engineering and Computer Science from 2015-2021 after joining the institution as a Lecturer in 2003. His academic journey includes completing his BSc, MSc, and PhD in Computer Science at Victoria University of Wellington, with his doctoral research focusing on software reuse. Marshall's research interests center on information and data visualization, particularly exploring how visualization can function as collaborative tools in team environments rather than single-user applications. He also investigates explainable AI and mobile user interface design with emphasis on promoting healthy device usage patterns. His work bridges theoretical computer science with practical applications in education and environmental analysis. Analysis of his publication record reveals a consistent focus on visualization techniques, with recent work shifting toward immersive analytics and virtual reality applications for complex data analysis, particularly in ecosystem services. Earlier publications concentrated on mobile learning applications grounded in transactional distance theory, software visualization for large codebases, and graph layout algorithms. Marshall has supervised six PhD students and eight Masters students to completion, with current doctoral supervision spanning immersive environments for reading assistance, medical diagnosis interfaces, and cardiac procedure simulation. His grant portfolio includes multiple ACM ISS 2022 projects with industry partners including Sensor Holdings Limited, Niantic, Autodesk, and Northeastern University, along with an Australian Research Council grant for digital games preservation. Teaching responsibilities encompass foundational programming, safety-critical systems, human-computer interaction, and data visualization across undergraduate and graduate courses. He teaches subjects including SWEN326 (Safety-Critical Systems), CGRA151 (Introduction to Computer Graphics and Games), and DATA301 (Data Science in Practice), with teaching assignments scheduled through 2026.

Dongyoon Leeمشاهده پروفایل

استادیار

• Software Engineering
• Programming Languages
• Security
• +۲ مورد دیگر

Dongyoon Lee is an Assistant Professor in the Department of Computer Science at Stony Brook University's College of Engineering and Applied Sciences. His research focuses on software engineering challenges in programming languages and security, with emphasis on regular expression analysis and empirical studies. His research interests include: Software reliability through regex generalizability testing Developer decision-making in security-critical contexts Empirical measurement of programming language features across ecosystems Security implications of common coding patterns His publication trends reveal strong focus on practical security vulnerabilities in developer tools, particularly analyzing regular expression implementations across multiple programming languages. The work combines empirical measurement with human factors analysis to identify systemic risks. Lee actively contributes to the software engineering community through leadership roles in major conferences: LCTES 2025: Program Committee & Steering Committee LCTES 2023: Program Chair & Session Chair CGO 2022: Author of HECATE compiler optimization work ASE 2019: Two regex-related research papers His advising and community engagement is demonstrated through consistent program committee service since 2016 across PLDI, LCTES, CC, CGO, and ASE conferences. He has chaired sessions on storage systems, scheduling, and techniques for specific domains, showing breadth in systems software research.

Andrew Mortonمشاهده پروفایل

مدرس

• Computer Architecture
• Digital Hardware
• Real-time Systems
• +۳ مورد دیگر

Andrew Morton, PhD, PEng, is a Continuing Lecturer in the Department of Electrical and Computer Engineering at the University of Waterloo. He holds a BSc in Computer Science (Guelph, 1993), MSc in Computer Science (Guelph, 1996), and a PhD in Computer Engineering (Waterloo, 2005). Education: BSc (Guelph, 1993) Major: Computer Science, Minor: Chemistry MSc (Guelph, 1996) Computer Science PhD (Waterloo, 2005) Computer Engineering His research focuses on the software/hardware boundary, including embedded systems, hardware acceleration, and real-time operating systems. Key areas include FPGA placement, real-time scheduling, and system-on-chip design. Teaching responsibilities span courses such as CS 137 (Programming Principles), CS 450 (Computer Architecture), and ECE 252 (Systems Programming and Concurrency). He has advised multiple students on topics including MPSoC scheduling and dynamically reconfigurable systems.

Nikil Duttمشاهده پروفایل

استاد

• Embedded Systems
• Electronic Design Automation
• Computer Architecture
• +۶ مورد دیگر

Nikil Dutt is a Chancellor’s Professor at the University of California, Irvine (UCI), with academic appointments in Computer Science, Electrical Engineering and Computer Science (EECS), and Cognitive Sciences. He is affiliated with UCI's Center for Embedded Computer Systems (CECS), Center for Cognitive Neuroscience and Engineering (CENCE), Calit2, CPCC, and LUCI. His research focuses on embedded systems, electronic design automation, computer architecture, and healthcare IoT. Dutt has authored/co-authored seven books and holds IEEE Fellow and ACM Distinguished Scientist titles. Education: B.E. (Mechanical Engineering) from Birla Institute of Technology and Science (Pilani, India), 1980; M.S. (Computer Science) from Pennsylvania State University, 1983; Ph.D. (Computer Science) from University of Illinois at Urbana-Champaign, 1989. Research Interests: Embedded systems, brain-inspired architectures, neuromorphic computing, and healthcare IoT. Current projects include the Information Processing Factory (IPF) for autonomous systems and CareDex for disaster resilience in aging communities. Awards: Multiple Best Paper Awards, NSF grants, and fellowships. Serves as editor for ACM TECS, IEEE TVLSI, and former Editor-in-Chief of ACM TODAES. Active in academic service, including ESWEEK Steering Committee roles. Grants: NSF IPF, UNITE, CareDex, and industry partnerships (e.g., Facebook). Research addresses energy-efficient data centers, autonomous driving systems, and wearable health technologies. Labs/Teams: Leads the Dutt Research Group (DRG), focusing on self-aware systems, edge computing, and neuromorphic architectures.

Anna Brunströmمشاهده پروفایل

استاد

• Computer Networking
• Internet Architectures
• 5G/6G Mobile Systems
• +۳ مورد دیگر

Anna Brunström is a Full Professor and Head of the Distributed Intelligent Systems and Communications Research Group (DISCO) at Karlstad University's Department of Computer Science. She holds a part-time role as a Researcher at the University of Malaga's Institute of Software Engineering and Technologies (ITIS). Her research focuses on computer networking, Internet architectures, low latency communication, and 5G/6G mobile systems. She leads the nationally funded DRIVE initiative and collaborates on European projects like 6G-PATH. She actively contributes to IETF standardization, notably as a former rmcat WG chair. Her work spans over 200 publications, emphasizing network measurement, latency optimization, and multipath protocols. Education: Ph.D. (1996) and M.Sc. (1993) from College of William & Mary, B.Sc. (1991) from Pepperdine University. Research Interests: Distributed systems, IoT networking (NB-IoT), satellite communication (Starlink), machine learning for positioning, and transport protocols (QUIC, MPTCP). Recent work includes latency-aware scheduling, 5G/6G performance analysis, and edge computing frameworks. Publications highlight trends in: 1) Satellite network throughput modeling, 2) 5G/6G architecture validation, 3) Machine learning applications for positioning and network analysis, 4) Cross-layer optimization of latency-critical services. Collaborations with industry and academia drive applied research in smart grids, healthcare, and automotive communication. Labs/Teams: DISCO group at Karlstad University, leading the DRIVE research profile and 6G-PATH consortium involvement.

• Artificial Intelligence (AI)
• Unmanned Aerial Vehicles (UAVs)
• Fuzzy Logic Systems
• +۷ مورد دیگر

Dr. Kelly Cohen is a Professor and Brian H. Rowe Endowed Chair in the Department of Aerospace Engineering and Engineering Mechanics at the University of Cincinnati's College of Engineering and Applied Science. His career spans over two decades, marked by significant contributions in AI, UAV systems, and aerospace engineering. He has led numerous research initiatives, secured grants from agencies like NSF, NIH, and NASA, and developed innovative solutions in autonomous robotics and medical AI applications. Dr. Cohen is also recognized for his teaching excellence and mentorship, having advised 12 PhD and 33 MS students. Education: Ph.D. in Aerospace Engineering, Technion, Israel Institute of Technology (1999) M.Sc. in Aerospace Engineering, Technion (1991) B.Sc. in Aeronautical Engineering, Technion (1986) Research Interests: Focus on AI-driven systems for aerospace and biomedical applications, including trustworthy AI, UAV control, optimization, and safety-critical systems. Current projects involve assured autonomy, medical phenotypic plasticity modeling, and advanced air mobility. Scientific Awards: Over 20 awards, including the UC Dolly Cohen Award, AIAA Technical Contribution Award, and Greater Cincinnati Consortium Excellence in Teaching Award. Grants and Advising: Principal Investigator on over 100 grants totaling millions, including projects on UAV traffic systems, AI safety, and medical AI. His labs include the AI Bio Lab and collaborations with NASA, FAA, and industry partners.

Stavrakakis Ioannisمشاهده پروفایل

استاد

• Networking
• Wireless Communication
• Distributed Systems
• +۵ مورد دیگر

Stavrakakis Ioannis is a Professor at the Department of Informatics and Telecommunications, School of Science, University of Athens, where he has served since 2002. He previously held academic positions at Northeastern University (1994-1999) and University of Vermont (1988-1994). Ph.D., Electrical Engineering (1988), University of Virginia Diploma, Electrical Engineering (1983), Aristotle University of Thessaloniki His research focuses on network resource allocation algorithms , cooperative content dissemination , mobile ad hoc networks , and privacy-aware protocols . He leads the Advanced Networking Research (ANR) Group. Recent publications highlight trends in AI-driven network optimization , edge computing for VR , drone-assisted sensor networks , and privacy in vehicular systems . Key themes include game theory applications, energy-efficient protocols, and distributed learning frameworks. Contact: ioannis@di.uoa.gr

Greg Gangerمشاهده پروفایل

استاد

• Cloud Computing
• Storage Systems
• Operating Systems
• +۳ مورد دیگر

Greg Ganger is the Jatras Professor of Electrical and Computer Engineering at Carnegie Mellon University and Director of the Parallel Data Lab (PDL). His research focuses on computer systems, including cloud computing, storage systems, distributed systems, and machine learning infrastructure. He holds a Ph.D. in Computer Science and Engineering from the University of Michigan and completed postdoctoral work at MIT. Education: Ph.D., M.S., and B.S. in Computer Science from the University of Michigan (1991–1995). Research Interests: Ganger leads projects in cloud computing, storage/file systems, operating systems, and systems for big data and large-scale machine learning. Recent work includes optimizing cloud resource scheduling, developing sustainable storage solutions, and improving ML cluster efficiency. The PDL explores storage system architecture, file systems, and leveraging new storage technologies like non-volatile memory (NVM). Awards: 2021 OSDI Best Paper, 2021 SOSP Best Paper, 2021 SoCC Test of Time Award, and 2021 R&D 100 Award. His team's work on Kangaroo caching and MACARON cloud caching exemplifies cutting-edge contributions. Advising & Grants: Advises graduate students in ECE and Computer Science. Active in grants related to distributed storage, cloud systems, and ML infrastructure. Collaborates with industry partners like Los Alamos National Lab on storage systems. Labs/Teams: Directs the Parallel Data Lab (PDL), a leading research group in storage and distributed systems. Collaborates with CMU’s CyLab on security aspects of storage systems and ML infrastructure.

Laura Toniمشاهده پروفایل

دانشیار

• Machine Learning
• Signal Processing
• Immersive Communications
• +۵ مورد دیگر

Laura Toni is an Associate Professor in the Department of Electronic & Electrical Engineering at University College London (UCL). She serves as Director of the MSc in Telecommunications and Internet Engineering and the MRes in Telecommunications. Additionally, she is a Turing Fellow at the Alan Turing Institute and a member of ELLIS (European Lab for Learning and Intelligent Systems). Her research focuses on coding, streaming technologies, machine learning for immersive communications, decision-making under uncertainty, and large-scale signal processing. She leads the LASP (Learning And Signal Processing) group at UCL. Education: MSc (2005) and PhD (2009) from the University of Bologna, followed by postdoctoral research at UC San Diego and EPFL under Professors L. Milstein, P. Cosman, and P. Frossard. Key roles include Technical Program Chair at ACM MM 2022, Keynote Co-Chair at ACM MMSys 2022, and leadership in organizing workshops on graph-based machine learning and emerging technologies in performing arts. She is a Senior IEEE Member and holds editorial roles in IEEE Multimedia Magazine and EURASIP Journal on Signal Processing. Her work bridges communication systems and machine learning, with contributions to adaptive streaming, network optimization, and graph signal processing. She actively promotes diversity and inclusion in technical conferences, including roles as Diversity Chair at MMSys 2021 and PIMRC 2020.

Xiaojun Ruanمشاهده پروفایل

دانشیار

• Energy-Efficient Systems
• Cloud Computing
• Storage Systems Optimization
• +۷ مورد دیگر

Xiaojun Ruan is an Associate Professor in the Department of Computer Science at California State University, East Bay. He holds a Ph.D. in Computer Science from Auburn University (2011) and a B.E. in Computer Science and Technology from Shandong University (2005). His primary research focuses on energy-efficient systems, cloud computing optimization, storage systems, and security-aware resource management. He has extensive experience in thermal modeling, parallel I/O performance, and distributed deep learning frameworks. Dr. Ruan’s work emphasizes balancing energy efficiency, reliability, and performance in storage and cloud environments. Notable projects include DuoFS (hybrid storage system), energy-aware VM allocation strategies, and securing cloud infrastructure against co-residence attacks. His research bridges hardware-software co-design principles with practical system optimizations. His publications span topics from NVMe SSD performance optimization to text augmentation for spam detection, reflecting a blend of storage systems and machine learning applications. He has actively contributed to improving Shuffle I/O in big data processing, thermal management in clusters, and secure virtualization techniques. Dr. Ruan collaborates on interdisciplinary projects involving distributed computing, cybersecurity, and real-time systems. His lab focuses on deploying energy-efficient solutions while maintaining robust reliability, evidenced by over 50 peer-reviewed articles and ongoing contributions to academic conferences.

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