جست‌وجوی استاد و پژوهشگر

Hakduran Kocمشاهده پروفایل

استاد

• Computer Engineering
• Digital Design
• Embedded Systems
• +۵ مورد دیگر

Dr. Hakduran Koc is a Professor of Computer Engineering at the University of Houston – Clear Lake (UHCL), affiliated with the College of Science and Engineering. He holds a B.S. in Electronics Engineering from Ankara University (1997) and M.S./Ph.D. in Computer Engineering from Syracuse University (USA). His research focuses on digital design, embedded systems, and computer architecture optimization. He has received numerous teaching and leadership awards, including multiple Piper Award nominations and IEEE honors. Education: B.S., Electronics Engineering, Ankara University (1997) M.S., Computer Engineering, Syracuse University (USA) Ph.D., Computer Engineering, Syracuse University (USA) Research interests include performance improvements in many-core architectures, energy minimization in embedded systems, and reliability enhancements through fault-aware design. His work bridges theoretical computer engineering with practical applications in robotics, wireless communication, and educational tools. He has advised multiple student researchers and maintains active IEEE/ACM memberships. His publications emphasize embedded system reliability, memory optimization, and low-power design strategies. Key contributions include the AYSE automated system synthesis tool and frameworks for fault propagation mitigation. Awards: Minnie Stevens Piper Award Finalist (2011-2014) NSF/TCPP CDER Early Adopter Award (2013) IEEE Outstanding Small Section Award (2012) Dr. Koc teaches graduate courses like Advanced Digital System Design and undergraduate courses including Microcontroller Programming. He mentors students through thesis/research projects and has organized IEEE events recognized nationally.

Wei Yuمشاهده پروفایل

استاد

• Cybersecurity
• Privacy
• Cyber-Physical Systems
• +۳ مورد دیگر

Dr. Wei Yu is a Full Professor in the Department of Computer and Information Sciences at Towson University, USA, and serves as the Ph.D. program director in Information Technology since 2023. He holds a Ph.D. in Computer Engineering from Texas A&M University (2008), with prior degrees from Chinese institutions. His research focuses on cybersecurity, privacy, cyber-physical systems (CPS), IoT, data science, and machine learning applications. Key contributions include foundational work on secured edge intelligence in CPS domains like smart energy, manufacturing, and transportation. He has pioneered federated learning frameworks for privacy-preserving data analytics, digital twin architectures, and reinforcement learning for industrial IoT control. He has received prestigious awards including the NSF CAREER Award (2014–2021), USM Regents’ Faculty Award (2015), and Wilson H. Elkins Professorship (2016). His professional service includes senior editorial roles at IEEE Transactions on Information Forensics and Security, IEEE Internet of Things Journal, and IEEE Access. Research spans CPS security, IoT forensics, and AI-driven CPS applications. Notable projects include adversarial mitigation in federated learning, CAPTCHA robustness, and edge computing for smart transportation systems.

Bo Zhaoمشاهده پروفایل

استادیار

• Distributed Systems
• Machine Learning Systems
• Large-Scale Data Processing
• +۲ مورد دیگر

Bo Zhao is an Assistant Professor in the Department of Computer Science at Aalto University, leading the Aalto Data-Intensive System group (ADIS). His research focuses on building efficient data-intensive systems across multiple layers, from scalable machine learning systems to distributed data management systems. Research Focus: Scalable machine learning systems Distributed data processing Hardware-software co-design Quantum computing systems High-performance computing Current Projects: AthenaRL (scalable RL systems), LARA (quantum ML algorithms), FlexMoE (efficient mixture-of-experts systems). His group develops systems enabling ML deployment across hardware from quantum computers to mobile devices. Education & Career: PhD from Humboldt-Universität zu Berlin. Previously at Queen Mary University of London, Imperial College London, and Amazon Web Services. Research published in SOSP, VLDB, USENIX ATC.

Milijana Surbatovichمشاهده پروفایل

استادیار

• Programming Languages
• Formal Methods
• Systems and Networking
• +۳ مورد دیگر

Milijana Surbatovich is an Assistant Professor in the Department of Computer Science at the University of Maryland, affiliated with the Maryland Cybersecurity Center and the University of Maryland Institute for Advanced Computer Studies (UMIACS). Her research focuses on programming languages, formal methods, and systems for non-traditional computing platforms, particularly addressing correctness and security guarantees in intermittent computing and energy-harvesting systems. Education: PhD in Electrical & Computer Engineering, Carnegie Mellon University (2023) MS in Electrical & Computer Engineering, Carnegie Mellon University (2020) BS in Computer Science, University of Rochester (2017), Summa cum Laude Research Interests: Her work bridges programming languages, hardware/software interactions, and formal methods to ensure reliability in emerging computing platforms. She designs type systems, enforcement mechanisms, and abstractions for intermittent systems, enabling developers to write trustworthy code for energy-constrained devices. Current projects explore WAR-aware crash types, charge management interfaces, and formal verification for non-traditional architectures. Publications: Her recent work emphasizes type systems for intermittent computing, architectural charge management, and formal foundations for energy-harvesting systems. These contributions advance both theoretical models and practical tools for ensuring correctness in resource-limited environments. Awards: CyLab Presidential Fellowship (2021) First Place in PLDI 22 SRC (2022) 2022 Rising Star in EECS Advising & Grants: Advises PhD students Kalyan Bhetwal and Yi Cai. Actively seeks grants to advance research in intermittent computing and formal methods. Teaches graduate courses on Language-based Security and Programming Languages & Computer Architecture. Labs/Teams: Part of the PLUM lab at UMD, focusing on programming language research. Collaborates with the Maryland Cybersecurity Center on system security challenges.

Marc Moreno Mazaمشاهده پروفایل

استاد

• Computer Algebra
• Polynomial System Solving
• Parallel Algorithms
• +۳ مورد دیگر

Marc Moreno Maza is a Professor in the Computer Science and Applied Mathematics Departments at the University of Western Ontario, and a Principal Scientist at the Ontario Research Centre for Computer Algebra (ORCCA). His research focuses on applying computer science to mathematics, particularly polynomial system solving and algorithm design. Key areas include parallel computing, high-performance algebraic algorithms, and GPU acceleration. He leads projects funded by NSERC and industry partnerships, such as 'Hardware Acceleration Technologies for Polynomial Systems' and collaborative work with IBM and CAS Research. His research spans four directions: theoretical foundations of polynomial equations, efficient algorithm development, software implementation (e.g., RegularChains library in Maple), and applications to real-world challenges. He has delivered over 100 talks worldwide on topics like cylindrical algebraic decomposition, GPU-based polynomial arithmetic, and parametric system solving. His work emphasizes optimizing algorithms for modern architectures and leveraging parallelism. Notable contributions include the BPAS and CUMODP libraries for polynomial arithmetic, and the RegularChains library for semi-algebraic set computations. He collaborates internationally, with grants supporting both theoretical and applied research. His team addresses challenges in computational algebra, from theoretical breakthroughs to practical software tools.

Shahrzad Zargariمشاهده پروفایل

مدرس ارشد

• Digital Forensics
• Mobile Forensics
• Intrusion Detection
• +۹ مورد دیگر

Dr. Shahrzad Zargari serves as Associate Head and Cyber Security and Computer Networks Subject Group Lead at Sheffield Hallam University's College of Business, Technology and Engineering. With over 20 years of experience in the IT industry and academic teaching since 2012, she holds a PhD in Applied Statistics from the University of Leeds, an MSc in Forensic Computing and Security, and a BSc (Hons) in Statistics. She also earned a PgCert in Learning and Teaching in Higher Education and achieved Senior Fellowship status in July 2019. Her research spans multiple areas of cybersecurity with particular expertise in digital forensics, mobile forensics, intrusion detection, and data mining applications in security contexts. She leverages her background in applied statistics to enhance network security methodologies and has published extensively on topics including memory forensics, IoT device investigations, drone forensics, and metaverse-related forensic challenges. Her work demonstrates a consistent focus on practical forensic methodologies and security enhancement techniques across evolving technological landscapes. Dr. Zargari's recent publications reveal a strong trend toward addressing emerging forensic challenges in new technologies, with increasing focus on IoT devices, robotics, drones, and the metaverse. Her research combines statistical analysis with practical forensic applications, showing particular strength in developing novel methodologies for evidence collection and analysis across diverse platforms. She has established herself as a leading researcher in mobile forensics and continues to expand her expertise into newer technological domains. As an active educator, Dr. Zargari teaches across multiple programs including BSc Cyber Security, BSc Cyber Security with Forensics, and MSc Cyber Security. She serves as associate editor for the Information Security Journal: A Global Perspective at Taylor & Francis and is an active researcher within CENTRIC. Her supervision includes PhD and MSc students, with documented supervision of O. Ajao's 2019 doctoral thesis on "Content-aware Location Inference and Misinformation in Online Social Networks." Dr. Zargari actively promotes collaboration among government, industry, and academia within the cyber security sector, focusing on initiatives to bridge the skills gap in this critical field. She has presented at numerous international conferences and workshops, including the Annual Teaching Computer Forensics Workshop series and the British Computer Society events. Her work with the Industry and Innovation Research Institute demonstrates her commitment to translating academic research into practical industry applications.

Mohammad Alizadehمشاهده پروفایل

دانشیار

• Computer Networks
• Systems
• Machine Learning
• +۶ مورد دیگر

Mohammad Alizadeh is an Associate Professor in the Department of Electrical Engineering and Computer Science (EECS) at MIT, affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL). He holds additional roles as Director of the 6-A MEng Thesis Program and Industry Officer for EECS, overseeing the EECS Alliance industry outreach program. His research focuses on computer networks, systems, and their applications in datacenters, cloud computing, and edge computing. Notable areas include machine learning for systems, congestion control, and network protocols. Education: PhD (Stanford University), MS in Electrical Engineering (Stanford), BS (Sharif University of Technology). Industry Experience: Former roles at Microsoft Research, Insieme Networks, and Cisco Systems. Research Interests: Alizadeh’s work emphasizes improving network performance, robustness, and management in large-scale systems. Key projects include DCTCP, CONGA, and Pensieve (adaptive video streaming with reinforcement learning). His contributions span network architecture, programmable switches, and learning-based systems. Awards: NSF CAREER Award Alfred P. Sloan Research Fellowship SIGCOMM Rising Star Award Microsoft Research Faculty Fellowship Teaching: Courses include 6.888 (Advanced Topics in Networking), 6.829 (Computer Networks), and 6.02 (Digital Communication Systems). His teaching emphasizes cutting-edge networking research and practical system design. Labs/Teams: Active member of CSAIL, leading projects in distributed systems, network protocols, and cloud computing.

Stefanie Muellerمشاهده پروفایل

دانشیار

• Human-Computer Interaction (HCI)
• Computational Fabrication
• Robotics
• +۴ مورد دیگر

Stefanie Mueller is an **Associate Professor** in the Department of Electrical Engineering and Computer Science (EECS) at MIT, jointly appointed in Mechanical Engineering. She leads the **HCI Engineering Group** at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). Her research focuses on **computational fabrication** and **human-computer interaction**, developing novel fabrication techniques that integrate hardware, materials, and algorithms to enable new forms of interaction with physical objects. **Education**: PhD in Computer Science (summa cum laude) from the Hasso Plattner Institute, Germany (2011–2016). **Affiliations**: Member of MIT CSAIL, TIBCO Career Development Professor, and holds joint appointments in EECS and Mechanical Engineering. She teaches courses like 6.810 (Engineering Interactive Technologies), 6.08 (Interconnected Embedded Systems), and 6.100 (Introduction to Computer Science and Programming). **Research Interests**: Her work spans reprogrammable materials (e.g., Photo-Chromeleon), interactive fabrication tools (LaserFactory, FlexBoard), health sensing (EIT-kit, MuscleRehab), and educational technologies (InStitches, Fabricaide). Her lab emphasizes democratizing fabrication through accessible tools and methods. **Awards & Recognition**: Includes MIT Technology Review's 'Innovators Under 35' (2022), Microsoft Research Faculty Fellowship (2020), NSF CAREER Award (2019), and numerous best paper awards at CHI/UIST conferences. She is a Sloan Fellow and has received MIT's Outstanding Educator Award (2018). **Grants & Funding**: Over $3.8M in funding from NSF, MIT initiatives, and industry partners like Accenture. She leads projects on adaptive interfaces, fabrication-aware design, and educational maker tools. **Outreach & Service**: Co-organized Rising Stars in EECS workshops to support underrepresented genders in academia. Served as program chair for ACM CHI and UIST, steering committee member for Computational Fabrication conferences, and advocate for diversity in STEM.

Mario Paoloneمشاهده پروفایل

استاد

• Power Systems
• Smart Grids
• Renewable Energy Integration
• +۵ مورد دیگر

Mario Paolone is a Full Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) , leading the Distributed Electrical Systems Laboratory (DESL) within the School of Engineering (STI). His work focuses on smart grid technologies, power system dynamics, and renewable energy integration. Chair of DESL Teaching roles in Electrical and Electronic Engineering PhD Program Committee Member, Doctoral Program Energy EPFL Academic Strategic Committee Member His research spans real-time monitoring , optimal grid operation , and advanced protection techniques for power systems. Key contributions include PMU-based situational awareness and convex optimization methods for Active Distribution Networks. Recent work explores hybrid AC/DC grids , linear induction motors for transportation, and machine learning applications in energy systems. Notable scientific awards include: IEEE Fellow (2022) Richard B. Schulz Best Paper Awards (2017, 2018, 2020) IEEE EMC Technical Achievement Award (2013) He has supervised numerous PhD theses on grid-aware control , synchrophasor technologies , and renewable energy systems , with research sponsored by the Swiss National Science Foundation , Swiss Electric Research , and the European Union .

Abhishek Dubeyمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Cyber-physical Systems
• Distributed Computing
• +۴ مورد دیگر

Abhishek Dubey is an Associate Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He leads the SCOPE lab, focusing on AI-driven solutions for cyber-physical systems, resilient computing, and smart communities. His work integrates online learning algorithms and decision procedures to address challenges in energy systems, emergency response, and urban mobility. Key projects include partnerships with Nashville's fire department, transit agencies, and state transportation departments. Education: Ph.D. and M.S. in Electrical Engineering from Vanderbilt University (2009 and 2005), B.Tech. in Electrical Engineering from IIT Banaras Hindu University (2001). Research Interests: Resilient computational abstractions, energy-efficient transit systems, transactive energy systems, and AI for decision-making under uncertainty. Recent work emphasizes reinforcement learning, federated learning, and urban mobility optimization frameworks like NS-Gym and PDPTW-DB. Grants and Partnerships: Funded by NSF, NASA, DOE, ARPA-E, AFRL, DARPA, Siemens, Cisco, and IBM. Projects include grid-aware charging optimization, wildfire resilience, and equitable transit network design. Labs and Tools: SCOPE lab, NS-Gym simulation environment, E-Transit-Bench platform, and SmartTransit AI. His work bridges theory and practice, addressing real-world challenges in smart cities and critical infrastructure.

Chen Dingمشاهده پروفایل

استاد

• Locality theory and optimization
• Compilers and run-time systems
• Memory management
• +۳ مورد دیگر

Chen Ding is a Professor of Computer Science and Chair of the Department of Computer Science at the Hajim School of Engineering & Applied Sciences, University of Rochester. He holds a PhD from Rice University (2000). His research focuses on program analysis, optimization, and memory management, particularly in the areas of locality theory, compilers, parallel programming, and high-performance computing. He has received prestigious awards including the DOE Early Career Principal Investigator award (2001), NSF CAREER award (2002), and IBM CAS faculty fellowship (2005-2009). Education: PhD in Computer Science, Rice University, 2000 Research Interests: Locality theory and optimization Compilers and runtime systems for parallelism Memory management strategies High-performance computing systems Key Contributions: His work on reuse distance in memory hierarchy and compiler-assisted cache management (CLAM) has been foundational in optimizing data movement and parallelism. Recent research explores data movement complexity for machine learning and generative AI-driven memory workload synthesis. Awards: IPDPS Best Paper Award (2001) DragonStar Lecturer (ICT China, 2008) Grants & Advising: As department chair, he oversees research grants and faculty development. No specific student advising details are listed here.

Sreepathi Paiمشاهده پروفایل

دانشیار

• Compilers
• Heterogeneous Architectures
• GPU Algorithms
• +۳ مورد دیگر

Sreepathi Pai is an Associate Professor of Computer Science at the Hajim School of Engineering & Applied Sciences, University of Rochester. He holds a PhD from the Indian Institute of Science. His research focuses on experimental computer systems, particularly the performance of computer programs, with emphasis on heterogeneous architectures combining CPUs and GPUs. He develops optimizing compilers for irregular/graph algorithms on GPUs and creates performance models for these systems. Key research interests include compilers, heterogeneous architectures, GPU algorithms, and performance modeling. His work addresses challenges in large-scale automata processing, graph processing frameworks like Groute, and modular GPU emulation (Horus). He collaborates on projects such as TriForce for multiphysics simulations and explores efficient electromagnetic algorithms for plasma simulations. Recent projects include formal methods for scientific computing (DANUBE), lightweight GPU performance simulation, and autotuning for volunteer computing. His research also spans statistical caching, compiler-assisted memory management, and parallel triangle counting algorithms. His work bridges theory and practice, with contributions to frameworks like PLASMA for heterogeneous accelerators and tools for analyzing memory utilization in shared-memory systems. He has published extensively on topics ranging from tensor core modeling to preemptive thread block scheduling in GPUs.

• Cloud Computing
• Cybersecurity
• Internet of Things (IoT)
• +۷ مورد دیگر

Gokop Goteng is a Senior Lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science, specializing in cloud computing, IoT security, and middleware systems. He holds a PhD in Grid Computing from Cranfield University (2009) and has held postdoctoral roles at Qatar Computing Research Institute (2012-2014) and King Abdullah University of Science and Technology (2012-2014). Currently, he leads the BUPT joint program's Cloud Computing and Middleware modules, focusing on industry-relevant skills in distributed systems and software engineering. His research integrates cloud technologies, cybersecurity, and AI to address challenges in smart cities, energy systems, and digital healthcare. Notable projects include malware detection in IoT devices and optimizing cloud service latency via deep learning. He is an Oracle Certified Professional (OCP), Java Certified Programmer (JCP), and active member of the British Computer Society (BCS) and IEEE. Teaching responsibilities include Cloud Computing (BUPT joint programme) Middleware for IoT Software Engineering , emphasizing hands-on programming with APIs, secure middleware design, and team-based software development. His work emphasizes industry collaboration, as seen in AWS Academy partnerships to enhance student employability. He maintains a research website at gotengphdstudents for doctoral supervision and project updates.

• Operating Systems
• Energy-Aware Systems
• Power Management
• +۴ مورد دیگر

Frank Bellosa is a Professor and head of the Operating Systems Group at the Karlsruhe Institute of Technology (KIT). Previously, he held roles at the University of Erlangen, including Assistant Professor and researcher in the Operating Systems Department. He earned his PhD from the University of Erlangen in 1998, focusing on memory-conscious scheduling in multiprocessor systems. His research interests center on energy-aware systems, including OS-directed power management, thermal management in distributed systems, and flexible operating system architectures. Key projects include Event-Driven Clock Scaling (Process Cruise Control) and Energy-Aware Memory Management. He has advised numerous students on topics like temperature-aware scheduling and power management for embedded systems. Bellosa's publications span dynamic thermal management, cooperative I/O, and energy-efficient file systems. His work emphasizes reducing energy consumption while maintaining performance through innovative OS mechanisms. He has contributed to international conferences and workshops, including EuroSys and USENIX, and serves on program committees for major systems conferences. Current roles include leading the Operating Systems Group at KIT and contributing to initiatives like the Disruptive Memory Systems workshop. His research bridges hardware and software, addressing challenges in modern computing systems' efficiency and scalability.

Rosta Farzanمشاهده پروفایل

استاد

• Social Computing
• Urban Informatics
• Online Communities
• +۴ مورد دیگر

Rosta Farzan is a Professor and Associate Dean for Diversity, Equity & Inclusion at the University of Pittsburgh's School of Computing and Information. She specializes in social computing, focusing on online communities, socio-technical systems, and digital equity. Her work emphasizes empowering marginalized groups through technology design and fostering equitable participation in knowledge production. Education: Ph.D. from the University of Pittsburgh Affiliations: School of Computing and Information, Department of Informatics and Networked Systems Research Interests: Farzan's research integrates computational methods with social sciences to address societal challenges. Key areas include: Designing privacy-centric sensor systems Community-engaged digital equity programs Collaborative platforms for health support and education Recent Contributions: Recent work includes studies on algorithmic governance, LGBTQ+ suicide prevention interventions, and cyberbullying mitigation strategies. She leads projects funded by NSF and the R. K. Mellon Foundation addressing digital divides and hyperlocal community engagement. Awards: Leverhulme Trust Fellowship (2019) Teaching: Courses like Social Computing, Network and Web Data Technologies, and Information Systems Analysis Labs/Initiatives: Leads projects such as 'Critical Data Literacy for Advocacy' and 'Fostering Hyper-local Digital Equity.'