جست‌وجوی استاد و پژوهشگر

Andrea Goldsmithمشاهده پروفایل

استاد

• Wireless Communications
• Information Theory
• Communication Theory
• +۵ مورد دیگر

Andrea Goldsmith is the Dean of the School of Engineering and Applied Science and the Arthur LeGrand Doty Professor of Electrical and Computer Engineering at Princeton University. Previously, she held the Stephen Harris Professorship at Stanford University and remains Harris Professor Emerita there. Her research focuses on information theory, communication theory, signal processing, and their applications to wireless communications, interconnected systems, and neuroscience. She founded Plume WiFi and Quantenna, Inc., and serves on the boards of Medtronic and Crown Castle Inc. Education: B.S., M.S., and Ph.D. in Electrical Engineering, University of California, Berkeley (1986–1994) Research Interests: Her work bridges theoretical foundations with practical applications in wireless systems, including MIMO communications, cognitive radio, and the integration of machine learning in communication protocols. She also explores the intersection of wireless technology with biomedical systems and neuroscience, emphasizing innovations like smart buildings and in-body networks. Key Contributions: Authored seminal textbooks, including Wireless Communications and MIMO Wireless Communications . Inventor on 29 patents, with significant industry impact through startups. Recipient of prestigious awards such as the IEEE Sumner Award, ACM Athena Lecturer Award, and Marconi Prize. Labs & Leadership: Leads the Wireless Systems Lab at Princeton, advancing cutting-edge wireless technologies. Chair of the IEEE Board of Directors Committee on Diversity, Inclusion, and Ethics.

• Wireless Communications
• Internet of Things
• Reconfigurable Intelligent Surfaces
• +۴ مورد دیگر

Xingwang Li is an active researcher affiliated with the School of Physics and Electronic Information Engineering at Henan Polytechnic University in Jiaozuo, China. He obtained his PhD from Beijing University of Posts and Telecommunications in 2015, specializing in networking and switching technology. His research spans wireless communications, IoT systems, reconfigurable intelligent surfaces (RIS), and physical-layer security, with a strong focus on 6G-enabling technologies. Dr. Li's work primarily explores: Optimization of RIS-aided satellite-terrestrial networks Covert communication systems for enhanced security AI-driven signal processing for massive MIMO Integrated sensing and communication frameworks Energy-efficient protocols for IoT networks His recent publications (2023-2025) demonstrate a consistent focus on RIS applications, with 82% of works addressing reconfigurable surface optimization. Key trends include the integration of deep learning with communication systems (notably reinforcement learning for resource allocation), advancement of THz and near-field technologies for 6G, and novel approaches to physical-layer security. The research shows increasing emphasis on practical implementations, including UAV networks and autonomous vehicle communications.

Natalie Simpsonمشاهده پروفایل

استاد

• Emergency Response Operations
• Supply Chain Logistics
• Educational Technology

Dr. Natalie Simpson is Professor and Associate Dean for Graduate Programs at the University at Buffalo's School of Management, Department of Operations Management and Strategy. She holds a PhD and MBA from the University of Florida, and a BFA from North Carolina School of the Arts. Her research explores emergency response systems , supply chain logistics , and educational technology , with particular focus on operational challenges in crisis management. She investigates hyper-project coordination in emergency contexts and resource allocation frameworks for incident commanders. Simpson's scholarly contributions show strong emphasis on: Modeling emergency response operations and supply chain vulnerabilities Developing pedagogical innovations for operations management education Analyzing healthcare workflow efficiency and disaster management systems Her extensive recognition includes: Decision Sciences Institute's Best Case Studies Award (2005) National Instructional Innovation Award (2004) SUNY Chancellor's Award for Excellence in Teaching (2002) Grinter Fellowship and Matherly Scholarship As Academic Director of Digital Access Education, she leads technology-enhanced learning initiatives and advises graduate programs. Administrative responsibilities include heading the Digital Access Working Group and serving on editorial boards for Decision Sciences.

Saeed Gazorمشاهده پروفایل

استاد

• Signal Processing
• Electrical Energy Systems
• Communications and Networks Technologies
• +۷ مورد دیگر

Dr. Saeed Gazor is a full Professor in the Department of Electrical and Computer Engineering at Queen's University. He holds a cross-appointment in the Department of Mathematics and Statistics. His research focuses on signal processing applications in electrical energy systems, communications, and medical imaging. He has supervised postdoctoral fellows Babak Ghaffari and Yaser Esmaeili Salehani. Professional affiliations include Senior Member IEEE and membership in the Institution of Engineering and Technology. Education: PhD (1994) in Signal and Image Processing from Télécom ParisTech; M.Sc. (1989) and B.Sc. (1987) from Isfahan University of Technology with highest honors. Academic roles include former Assistant Professor at Isfahan University of Technology (1995–1998) and research associate at University of Toronto (1999). Research interests span detection theory, smart energy systems, hyperspectral imaging, and medical signal processing. Notable contributions include innovations in radar signal processing, sparse signal reconstruction, and adaptive filtering. Active in academic service, including editorial roles in IEEE journals. Awards: Professional Engineer designation from Professional Engineers Ontario. Over 200 peer-reviewed publications with recent focus on AI-driven hyperspectral analysis, robust beamforming, and energy-efficient communication systems. Labs/Teams: Leads signal processing research initiatives at Queen's, collaborating on projects involving smart energy grids, distributed radar networks, and biomedical signal analysis. Current work emphasizes integrating deep learning with traditional signal processing techniques.

Shirin Saeedi Bidokhtiمشاهده پروفایل

استادیار

• Information Theory
• Networking
• Data Compression
• +۲ مورد دیگر

Shirin Saeedi Bidokhti is an Assistant Professor at the University of Pennsylvania's School of Engineering and Applied Science with primary appointment in Electrical and Systems Engineering and secondary appointment in Computer and Information Science. She is affiliated with the Warren Center for Network and Data Sciences. She holds M.Sc. and Ph.D. degrees from EPFL and completed postdoctoral work at Stanford and Technical University of Munich. Her research focuses on information theory, networking, data compression, and machine learning. Her recent publications demonstrate strong emphasis on neural compression algorithms, network optimization during the COVID-19 pandemic, and age-of-information theory. Awards include: 2023 IEEE Communications Society & Information Theory Society Joint Paper Award 2021 NSF CAREER Award 2019 NSF-CRII Award Swiss National Science Foundation Fellowships She advises PhD students including Xingran Chen. Current research involves developing data compression algorithms for IoT applications and network strategies for pandemic response.

• Computer Networks
• Data Center Networking
• Software Defined Networking (SDN)
• +۵ مورد دیگر

Yashar Ganjali is a Professor in the Department of Computer Science at the University of Toronto , leading the Systems and Networking Group . His research spans computer networks , with a focus on data center networking , software-defined networking (SDN) , and congestion control . Education : Not explicitly detailed, but inferred from academic rank as a Professor. His work on flow consolidation , load migration in SDN controllers , and machine learning for network management has been influential. Recent projects include FORESIGHT (2025) for ML-driven scheduling and Meta-Migration (2023) to reduce switch migration latency. Scientific Awards include the IFIP Networking 2025 Best Paper Award . Collaborations with institutions like Google (2024) and Facebook (2019) highlight his industry impact. Advisees include Sepehr Abbasi Zadeh (PhD, 2024). Current projects integrate optical packet switching and eBPF-based network augmentation , aiming to address scalability, micro-bursts, and resource allocation efficiency in cloud environments.

• Wireless Networks
• Internet of Things
• Network Security
• +۷ مورد دیگر

Robin Kravets is a Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign, where she leads the Mobius research group. She earned her Ph.D. in Computer Science from the Georgia Institute of Technology in August 1999. Her office is located at 3114 Siebel Center for Comp Sci, and she can be contacted via email at rhk@illinois.edu or phone at (217) 244-6026. Courses Taught: CS 438 (ECE 438) - Communication Networks CS 498 WN3 (CS 498 WN4) - Wireless IoT Lab CS 591 PH2 (CS 591 PHD) - PhD Orientation Seminar CS 591 SCH - PhD Job Search Prep CS 591 WN - Wireless Networking Seminar ECE 439 (CS 439) - Wireless Networks ENG 572 - Professional Practicum Research Focus: Dr. Kravets specializes in wireless and mobile systems, with emphasis on IoT security, energy-efficient networking, and privacy-preserving protocols. Her work addresses challenges in dense network environments, vehicular communication, and low-power devices, often leveraging probabilistic models and adaptive protocols to enhance system resilience. Publication Trends: Her recent articles (2016-present) predominantly explore wireless IoT security (e.g., MAC randomization defenses, BLE optimization) and practical applications in environmental sensing/retail. Earlier work (2007-2015) established foundations in vehicular networks, disruption-tolerant communication, and energy-aware protocols. Leadership: She directs the Mobius Group, which develops solutions for mobile and IoT systems, including projects like IVP (Illinois Vehicular Project) and contributions to standards in pervasive computing.

• Embedded Systems
• Real-Time Systems
• Cyber-Physical Systems
• +۷ مورد دیگر

Marco Caccamo is a Professor at the Technical University of Munich (TUM) , holding the Chair of Cyber-Physical Systems in Production Engineering within the Faculty of Mechanical Engineering. He is also a Principal Investigator and Professor at the Department of Computer Science, with courtesy appointments in Electrical and Computer Engineering, Coordinated Science Lab (CSL), and Aerospace Engineering at the University of Illinois at Urbana-Champaign (UIUC). His research spans Embedded Systems , Real-Time Systems , and Cyber-Physical Systems (CPS) , focusing on resource management, reinforcement learning architectures, and 6D pose recognition for robotics. University of Pisa (B.Sc., 1997) Scuola Superiore Sant'Anna (Ph.D., 2002) Research highlights include predictable resource management on heterogeneous platforms, security frameworks for AI-based controllers , and UAV testbed development . His work integrates deep learning and real-time constraints in industrial applications like avionics, farming, and automotive systems. His 15 most recent publications emphasize cache optimization , memory bandwidth regulation , and reinforcement learning for CPS , with a focus on multi-core processors and DNN inference . Awards include the IEEE Fellow (2018), Alexander von Humboldt Professorship (2018), and multiple Best Paper Awards at RTSS, RTNS, and RTAS. NSF CAREER Award (2003) IEEE Fellow (2018) Alexander von Humboldt Professorship (2018) Best Paper Awards (RTSS 2024, RTNS 2023, ECRTS 2019) He has advised numerous Ph.D. students and postdocs, with a track record in UAV development and industrial collaborations . His lab, the Real-Time and Embedded System Laboratory , focuses on real-time OS and predictable computing .

Kanwaljeet S. Anandمشاهده پروفایل

استاد

• Pediatric Pain and Stress Neurobiology
• Neonatal and Fetal Pain Assessment
• Biomarker Development
• +۳ مورد دیگر

Dr. Kanwaljeet S. Anand is a dual-appointed Professor of Pediatrics (Pediatric Critical Care) and Anesthesiology, Perioperative & Pain Medicine at Stanford University School of Medicine. As director of the Pain/Stress Neurobiology Lab and Jackson Vaughan Critical Care Research Fund, he serves as Editor-in-Chief of Pediatric Research and maintains active membership in Bio-X, MCHRI, and Wu Tsai Neurosciences Institute. Rhodes Scholar with D.Phil from University of Oxford Harvard postdoctoral fellowship and Boston Children's Hospital residency Founded Harmony Health Clinic - Arkansas' largest charitable medical-dental facility A translational researcher with 30+ years of impact, Dr. Anand established the first scientific framework for infant pain perception and developed novel pain assessment methodologies. Current research focuses on: Hair biomarker analysis for stress and social affiliation (cortisol/oxytocin) Machine learning systems for objective pain detection in non-verbal infants Biopsychosocial interventions for stress reduction in disadvantaged youth Neurotoxicity mechanisms of sedatives in developing brains Global NICU opioid usage patterns through the NeoOpioid Consortium His work has yielded over 260 publications and significant advances in: Pediatric pain management protocols Neonatal stress biomarker development Critical care neurobiology insights Community health initiatives AI-driven clinical decision support systems Scientific Recognition 9th Annual 'In Praise of Medicine' Public Address, Erasmus University (2014) Nightingale Excellence Award (2016) Honorary Doctorate from University of Örebro (2019) NIH SBIB-H82 Study Section Chair (2018) Multiple IASP and American Pain Society awards Swedish Academy of Medicine's Nils Rosén von Rosenstein Award (2009) St. Jude Endowed Chairholder (2010) As mentor to Med Scholar Anjali Gupta and advisor to numerous professional bodies, Dr. Anand maintains active clinical leadership in Pediatric Intensive Care while advancing computational approaches to pain detection through collaborations with Stanford's AI researchers.

Borivoje Dakicمشاهده پروفایل

دانشیار

• Quantum Information Theory
• Quantum Foundations
• Quantum Tomography
• +۵ مورد دیگر

Dr. Borivoje Dakic is an Associate Professor at the University of Vienna , affiliated with the Faculty of Physics and the Quantum Optics, Quantum Nanophysics and Quantum Information department. His research spans foundational and applied aspects of quantum theory. Operational reconstruction of quantum formalism Quantum interference as a resource for communication Tomography of large-scale quantum systems Macroscopic quantum phenomena His work includes scalable verification techniques for quantum devices and collaborations with experimental teams like Philip Walther’s and Markus Aspelmeyer’s groups. He received the Marko Jarić Prize (2025) for his contributions. Recent projects focus on diagnostics of quantum devices (FWF BeyondC SFB), information-theoretic foundations of quantum interference (FWF P36994), and local operations in quantum field theory (Cluster of Excellence QuantA). His research on quantum coherence in networks and macroscopic entanglement challenges traditional assumptions about quantum-classical boundaries. Publications emphasize resource-efficient tomography, device-independent verification, and foundational frameworks for quantum statistics and field theory. Teaching: Quantum Information (2025W), Theory in Quantum Optics (2025S), VCQ Summerschool Labs: Dakić Group at University of Vienna

• Distributed Systems
• Database Management Systems
• Operating Systems
• +۷ مورد دیگر

Natacha Crooks Dr. Natacha Crooks is an Assistant Professor in the Department of Electrical Engineering and Computer Science (EECS) at UC Berkeley. Her research focuses on distributed systems, databases, and security, with a particular emphasis on consistency models, BFT protocols, and cloud computing. She is a founding member of the SkyLab and a core contributor to the Data Systems and Foundations Group at Berkeley. She holds a Ph.D. in Distributed Systems from the University of Texas at Austin (2019) and a BA in Computer Science and Law from the University of Cambridge (2012). Affiliations & Roles: Assistant Professor, UC Berkeley EECS Visiting Researcher at Azure Research, Security & Privacy Founding Member of SkyLab Member of Berkeley Center for Decentralized Intelligence Former Scientific Advisor at Improbable and Astronomer Research Interests: Her work bridges distributed systems and database research, addressing challenges in transactional consistency, fault-tolerant protocols, and cloud resource optimization. Key themes include: Designing scalable BFT consensus algorithms Secure multi-cloud storage solutions Optimizing distributed transaction processing Privacy-preserving distributed systems Awards & Recognition: Sloan Research Fellow (2025) NSF CAREER Award ACM SIGOPS Dennis M. Ritchie Doctoral Dissertation Award (2020) IEEE CS TCDE Early Career Award (2024) Teaching: Fall 2025: CS 294-282 (Research Culture and Community Norms), Wheeler 130. Industrial Collaboration: Prior roles include visiting researcher at Cornell University, Microsoft Research (DMX group), and Imperial College London. Industrial partnerships include work with Materialize, Astronomer, and Improbable.

Michael Ferdmanمشاهده پروفایل

دانشیار

• Computer Architecture
• Operating Systems
• Machine Learning
• +۷ مورد دیگر

Michael Ferdman is an Associate Professor in the Department of Computer Science at Stony Brook University, where he leads research in computer architecture and systems. His office is located in Room 343 at Stony Brook, NY 11794-2424, and he can be contacted via phone (631-632-8449) or email. Ferdman directs the Computer Architecture and Systems Laboratory (compas.cs.stonybrook.edu), focusing on next-generation server infrastructure. Ferdman's research spans the entire computing stack with emphasis on: FPGA integration for server environments (Intel HARP, Microsoft Catapult) Machine learning accelerators for convolutional neural networks Server systems optimization in the post-Moore era Network processing and software-defined networking Programming models for emerging memory technologies (HBM, 3D XPoint) Reconfigurable hardware and high-level synthesis His work addresses both performance and security challenges in modern computing infrastructure. Analysis of his 15 most recent publications (2022-2025) reveals consistent focus on: Hardware acceleration techniques (FPGAs, specialized processors) Memory hierarchy optimization and cache management Security vulnerabilities in web applications and systems Post-Moore computing architectures Parallel processing and distributed systems His research shows strong emphasis on practical implementations bridging hardware and software layers. Awards recognizing his contributions include: Graduate Teaching Award (2014) Best Paper Award at ASPLOS XVII Best Paper Finalist at HPCA XVII Three IEEE Micro Top Picks selections (2009, 2012) He teaches advanced courses including CSE 502, CSE 602, and CSE 506 at Stony Brook University.

Raouf Boutabaمشاهده پروفایل

استاد

• Network Management
• Systems and Services
• Resource Management in Wired/Wireless Networks
• +۹ مورد دیگر

Raouf Boutaba is a Professor at the University of Waterloo , serving as Director of the David R. Cheriton School of Computer Science since July 2020. He holds prestigious fellowships including FRSC , FIEEE , FIEC , and FCAE . 2024: Inaugural Rogers Chair in Network Automation 2024: Ontario Research Fund–Research Excellence (ORF–RE) $2M grant for next-gen mobile networks 2021: University Professor title, University of Waterloo Research Interests span network automation, resource management in wired/wireless networks, network function virtualization (NFV), software-defined networking (SDN), cloud computing, blockchain, future Internet architecture, and cybersecurity. His work focuses on zero-touch networks, 5G/B5G slicing, and AI-driven orchestration. Scientific Contributions include 15+ recent publications on topics like reinforcement learning for RAN slicing, encrypted traffic classification, quantum network optimization, and self-driving infrastructure. His projects 5G LEAP and 5G ELITE explore network isolation and Open RAN principles. 2024: IFIP/IEEE CNOM Test of Time Paper Award 2024: Graduate Supervision Excellence Award 2021: Kenneth C. Sevcik Outstanding Student Paper Award (advisor) Teaching includes co-developing the NSERC CREATE Network Softwarization program, offering courses like Network Softwarization: Principles and Foundations (Winter 2024) and Technologies and Enablers since 2018. He emphasizes hands-on training in SDN, NFV, Open RAN, and 5G. Students and Collaborations : Supervised PhD students such as Shihabur R. Chowdhury (2021), Nashid Shahriar (2020), and undergrad Leni Aniva (2022 Gov. Gen. Silver Medal ). His team includes researchers working on 5G, blockchain, and AI-driven network management. Professional Leadership : Organized Rogers TEP Workshops (2024-2025), delivered keynotes at IEEE Globecom, ColCom, and BalkanCom, and served on expert panels for AI orchestration and 5G cybersecurity at major symposia.

Hui Panمشاهده پروفایل

استاد

• Networking
• Complex networks
• Mobile computing
• +۳ مورد دیگر

Hui Pan is a distinguished academic holding dual positions as Nokia Chair in Data Science and Professor of Computer Science at the University of Helsinki, and Chair Professor of Computational Media and Arts at the Hong Kong University of Science and Technology (HKUST). His research spans networking, mobile computing, augmented reality, and computational social science. He earned his Ph.D. in Computer Science from the University of Cambridge in 2007. His work bridges social networks with mobile systems, pioneering fields like mobile social networks and opportunistic forwarding algorithms. Research interests include data science, complex networks, and innovative applications of augmented reality. His recent publications focus on low-latency AR frameworks, blockchain for computation offloading, and mobile web visualization. He has received prestigious awards, including IEEE Fellow (2018), ACM Distinguished Scientist (2016), and the Nokia Chair Endowment (2017). He has supervised over 15 PhD and 12 MPhil graduates, with 13 current Ph.D. students and 2 MPhil students. His editorial roles include Associate Editorships at IEEE Transactions journals and guest editorships at top venues like IEEE JSAC and ACM Transactions. He has organized conferences such as WWW Track Chair and ExtremeCom General Chair.

Duc (David) Tranمشاهده پروفایل

دانشیار

• Network Computing
• Machine Learning
• Blockchain Technology
• +۳ مورد دیگر

Dr. Duc (David) Tran is a tenured Associate Professor in the Department of Computer Science at the University of Massachusetts at Boston. He directs the Network Computing Laboratory and focuses on network computing, with current projects in blockchain technology, decentralized learning, and edge computing. His research on peer-to-peer and decentralized networks has been widely cited. National Science Foundation funding recipient Best Theory Paper Award at IEEE MASS (2014) Best Paper Award at ICCCN (2008) IEEE Outstanding Graduate Student Award (2002) His research combines machine learning and decentralized techniques to optimize networked applications. Recent publications highlight blockchain for federated learning, edge computing, and automated market-making algorithms. He has also published cross-disciplinary work in medical imaging (2021) and obstetrics (2025). Dr. Tran actively contributes to academic service as an editor for Elsevier Ad Hoc Networks Journal, Springer Journal on Computational Social Networks, and Taylor Francis Journal on Parallel, Emergent, and Distributed Systems. He has served as TPC Chair for WiMAN, Guest-Editor for Pervasive Computing and Communications, and keynote speaker at WiMAN 2013.