Find Academic Supervisors

Gavrilovska LiljanaView profile

Associate Professor

• Telecommunications
• Mobile Edge Computing (MEC)
• Blockchain Technology
• +8 more

Liljana Gavrilovska is an Associate Professor at the Faculty of Electrical Engineering and Information Technologies (FEIT) of Ss. Cyril and Methodius University of Skopje (UKIM), specializing in the Department of Telecommunications. Her work focuses on advanced telecommunications systems, including 5G/Beyond 5G networks, mobile edge computing (MEC), blockchain applications in healthcare and IoT, cognitive radio networks, and network virtualization. She leads research groups addressing challenges in wireless resource management, energy efficiency, and distributed consensus mechanisms. Her research interests span telecommunications infrastructure , blockchain for healthcare systems , IoT optimization , and network slicing . Recent work includes developing the BloHeS consensus mechanism for blockchain systems and the Shapeshifter framework for MEC latency optimization. She also investigates dynamic spectrum allocation strategies and energy-efficient WuR-based IoT protocols. Publications emphasize practical implementations like the CHEST COPD e-Health platform and the FALCON project for virtualized network resource allocation. While no specific awards are listed, her contributions to open-source solutions like eWALL and SmartWine reflect industry engagement. Advising activities and grants are not explicitly detailed in the provided texts, though her involvement in EU projects like 5G-MEC and cognitive radio initiatives suggests significant collaborative work. Current projects include system design for blockchain-based public healthcare systems and analysis of heterogeneous network performance in LTE and DVB-T coexistence scenarios. She is actively involved in the FEIT Telecommunications Institute, contributing to both academic and applied research in telecommunications engineering.

Takayuki MizunoView profile

Associate Professor

• Computational Social Science
• Econophysics
• Network Science
• +12 more

Takayuki Mizuno is an Associate Professor at the National Institute of Informatics and SOKENDAI (The Graduate University for Advanced Studies), where he leads interdisciplinary research at the intersection of informatics, econophysics, and computational social science. His work focuses on analyzing complex global systems such as economic networks, financial markets, human mobility, and geopolitical dynamics using big data and network science. Doctor of Science, Chuo University (Physics) JSPS Research Fellow (2004) Lecturer, Institute of Economic Research, Hitotsubashi University (2007–2010) Associate Professor, University of Tsukuba (2011–2013) Senior Research Fellow, Canon Institute for Global Studies (2009–present) His research interests include computational social science, econophysics, network science, wealth inequality, financial bubbles, cryptocurrency regulation, public opinion manipulation, and global supply chain ethics. He develops models to understand market dynamics, detect hidden financial influences, and visualize geopolitical power shifts. The recent articles highlight a consistent trend in applying big data and network analysis to real-world socio-economic problems: visualizing China's indirect control in global shareholder networks, detecting financial risks, analyzing online market competition, studying supply chain ethics, and understanding cultural integration through human mobility. The work bridges physics, economics, computer science, and political science. Scientific Awards: Best Paper Award, Japanese Society for Artificial Intelligence (2019) Best Paper Award, Information Processing Society of Japan (2019, 2013) Student Encouragement Award, IPSJ (2019) Best Paper Award, Transdisciplinary Federation of Science and Technology (2019) JSPS Research Fellow (2004) Dr. Mizuno advises multiple Ph.D. and master’s students and leads the Mizuno Laboratory, which conducts cutting-edge research on global challenges. He has secured significant research grants from JSPS, JST (Sakigake), and other funding bodies. His work is frequently featured in major media outlets including Nikkei, NHK, The Wall Street Journal, and Yomiuri Shimbun, indicating broad societal impact. He is actively involved in professional service, including as Director of the Society for Computational Social Science of Japan and member of the Editorial Board of the Japanese Society for Artificial Intelligence. He also participates in government advisory committees on big data, economic policy, and telecommunications. His lab, the Mizuno Laboratory, focuses on the fusion of political economy and data science, aiming to disentangle complex global networks to address issues like economic bubbles, terrorism, and social polarization.

• Control Systems
• Machine Learning
• Electrical Engineering
• +4 more

Marko Tanasković (born December 6, 1986) is a researcher at Singidunum University with a PhD in Information Technology and Electrical Engineering from ETH Zurich (2015). His academic background includes master's (ETH Zurich, 2011) and bachelor's (University of Belgrade, 2009) studies in Electrical Engineering. Doctoral studies: Information Technology and Electrical Engineering, ETH Zurich (2011-2015) Master studies: Information Technology and Electrical Engineering, ETH Zurich (2009-2011) Basic studies: Electrical Engineering, University of Belgrade (2005-2009) Tanasković's research focuses on control systems , predictive modeling , and optimization algorithms for mechanical and electrical systems. His work addresses adaptive model predictive control (MPC), sensorless motor positioning, and data-driven approaches for nonlinear systems. Recent publications (2018-2024) demonstrate expertise in: Embedded control systems (rotor polarity detection) Drone forensics and autonomous navigation Industrial automation (LabVIEW applications) Biomedical sensor development ('Smart Anklet') Machine learning optimization (firefly algorithm)

Visham RamsurrunView profile

Senior Lecturer

• Cybersecurity
• Internet of Things (IoT)
• Network Security
• +7 more

Visham Ramsurrun is a Senior Lecturer and Programme Coordinator of the MSc Cyber Security programme at Middlesex University Mauritius. He holds a Ph.D. and B.Sc. in Computer Science & Engineering from the University of Mauritius, and a Postgraduate Certificate in Higher Education from Middlesex University (UK). His research focuses on cybersecurity, IoT, network design, machine learning, and smart agriculture. Education: Ph.D. in Computer Science & Engineering (2007-2010), University of Mauritius Postgraduate Certificate in Higher Education (2017-2018), Middlesex University (UK) BSc (Hons) Computer Science & Engineering (2000-2003), University of Mauritius Research interests include: Cybersecurity frameworks for IoT and autonomous systems Blockchain applications in healthcare and data management Network defense mechanisms (e.g., SDN-based moving target defense) Energy-efficient sensor networks and transmission optimization Smart agriculture systems and environmental monitoring Recent publications emphasize cybersecurity in autonomous vehicles, IoT-enabled healthcare systems, and sensor-based home security solutions. He has secured grants from the Mauritius Research and Innovation Council (MRIC) and collaborates with industry partners on innovation projects. His work includes developing augmented reality control platforms and low-cost air quality monitoring systems. As a member of the IPv6 Forum Mauritius, he advocates for network architecture advancements. His research spans academic collaborations across disciplines, with a focus on underserved regions' technological challenges.

Wanda OrlikowskiView profile

Professor

• Information Systems
• Organizational Studies
• Sociomaterial Practices
• +4 more

Wanda Orlikowski is the Alfred P. Sloan Professor of Information Technology and Organization Studies at MIT's Sloan School of Management. She is a leading scholar in the field of information systems and organizational studies, with a focus on how digital technologies reshape work practices, organizational structures, and accountability mechanisms. Dr. Orlikowski received her Ph.D. from New York University. Her academic journey has established her as a prominent figure in understanding the sociomaterial dimensions of digital work and organizational change. Orlikowski's research examines how technologies in the workplace generate significant shifts in organizing, coordination, and accountability. She is particularly known for her work on sociomaterial practices in digital work, exploring how digital reconfigurations transform organizational life. Her theoretical contributions have significantly advanced our understanding of technology's role in shaping contemporary work practices and organizational structures. Through her research, she has illuminated the complex interplay between material technologies and social practices, demonstrating how they co-constitute each other in organizational settings. Her publications reveal a consistent focus on digital transformation, organizational change, and the sociomaterial nature of work. Recent work increasingly examines AI, algorithmic coordination, and the "digital undertow" - the corollary effects of digital transformation that often go unnoticed but significantly impact industry standards and organizational practices. Her research spans multiple sectors including public libraries, hospitality, financial services, and general organizational settings, demonstrating the broad applicability of her theoretical frameworks. Distinguished Scholar Award of the Organizational Communication and Information Systems (OCIS) Division of the Academy of Management Lasting Impact Award from the ACM's Computer-Supported Cooperative Work Community Fellow of the Academy of Management (2019) Fellow of the British Academy (2021) Seegal Prize (2024) Lifetime Achievement Award (2023) Best Information Systems Publications Award (with JoAnne Yates) Recipient of an honorary doctorate Professor Orlikowski has served as an editor for Organization Science and MIS Quarterly, and currently serves on the editorial boards of Information and Organization, Organization Science, and the Annals of the Academy of Management. She has published widely in top-tier journals including ACM Transactions on Information Systems, Administrative Science Quarterly, Information Systems Research, Organization Science, and MIS Quarterly. Her work has been highly influential in both information systems and organizational studies fields, bridging theoretical perspectives and empirical investigations of digital work practices. As a member of several MIT research centers including the MIT Center for Information Systems Research, MIT Center for Collective Intelligence, The MIT Initiative on the Digital Economy, and the MIT Leadership Center, Orlikowski contributes to interdisciplinary research on digital transformation and its organizational implications. Her executive education courses, such as "Unlocking the Power of Perspectives," demonstrate her commitment to translating academic insights into practical leadership development.

Dominik BaumannView profile

Assistant Professor

• Systems and Control Theory
• Machine Learning
• Communication Networks
• +3 more

Dominik Baumann is an Assistant Professor at the Department of Electrical Engineering and Automation at Aalto University in Espoo, Finland. His research focuses on the interplay of systems and control theory with machine learning and communication networks, with a current emphasis on causal inference in control systems. Education: Diploma in Electrical Engineering from TU Dresden, Germany (2016) PhD from KTH Stockholm, Sweden (2020), supervised by Sebastian Trimpe (Max Planck Institute) and Karl H. Johansson Postdoctoral positions at RWTH Aachen University (1 year) and Uppsala University with Thomas Schön (1 year) Dr. Baumann's research bridges theoretical foundations with practical applications in robotics, wireless networks, and decision-making systems. His work spans safe reinforcement learning, event-triggered control systems, causal inference in dynamical systems, and ergodicity economics perspectives on long-term decision-making. He applies mathematical rigor to address challenges in resource-constrained environments, particularly focusing on safety guarantees and computational efficiency for real-world implementation. His recent publication record demonstrates a strong trajectory in safe learning-based control, with increasing focus on ergodicity economics in reinforcement learning, multi-agent coordination, and human-robot interaction. The research consistently balances theoretical guarantees with practical implementation constraints, particularly in bandwidth-limited wireless control systems and robotics applications. Scientific Awards: Best Paper Award for 'Feedback control goes wireless: Guaranteed stability over low-power multi-hop networks' at ACM/IEEE International Conference on Cyber-Physical Systems (2019) Dr. Baumann maintains extensive international collaborations, evidenced by numerous seminar invitations worldwide including Oxford University, ETH Zürich, University College London, and institutions across Asia. His research program addresses fundamental challenges in cyber-physical systems with applications in industrial automation, robotics, and the Internet of Things, securing research funding for projects focused on safe learning in control systems and wireless cyber-physical systems. His research group at Aalto University develops both theoretical foundations of learning-based control and practical algorithms for real-world deployment, with active software repositories on GitHub related to predictive triggering, causal structure identification, and ergodic reinforcement learning.

Nathaniel OsgoodView profile

Professor

• Computational Epidemiology
• Public Health Informatics
• Agent-Based Modeling
• +6 more

Nathaniel Osgood is a Professor in the Department of Computer Science at the University of Saskatchewan, with additional appointments as Associate Faculty in the Department of Community Health & Epidemiology and the Bioengineering Division. His work bridges computer science, public health, and epidemiology, focusing on developing computational tools to improve health decision-making through the integration of Data Science, Systems Science, and Computational Science. Professor, Department of Computer Science Associate Faculty, Department of Community Health & Epidemiology Associate Faculty, Bioengineering Division Office: 254.4 Thorvaldson Building (Computational Epidemiology and Public Health Informatics Lab) Dr. Osgood completed his entire formal education at MIT, earning a B.Sc. in Computer Science and Engineering (1990), an Sc.M. in Electrical Engineering and Computer Science (1993), and a Ph.D. in Computer Science (1999). Prior to joining the University of Saskatchewan, he served as a Senior Lecturer and Research Associate at MIT from 2003 to 2005. His research program centers on Computational Epidemiology and Public Health Informatics , with a distinctive approach that combines Data Science, Systems Science, Computational Science, and Applied Mathematics to improve health decision-making. Dr. Osgood's work emphasizes the development and application of dynamic modeling techniques including Agent-Based Models, System Dynamics, and discrete event simulation, often enhanced with particle filtering and machine learning approaches. His recent work has incorporated Applied Category Theory as a foundation for more powerful tools for studying complex systems. He has developed the Ethica epidemiological data collection system, which leverages smartphones and wearable devices for health surveillance while maintaining strong privacy guarantees. Dr. Osgood's research spans multiple health domains including infectious disease modeling (particularly COVID-19), chronic disease management (especially diabetes in pregnancy), mental health and suicide prevention, substance use disorders, and health systems operations. His publications show a clear trajectory toward increasingly sophisticated integration of modeling approaches with real-time data streams for more reliable policy planning. Google Scholar: Over 100 publications (2017-2025) Notable contributions to particle filtering methods for dynamic models Development of Ethica/iEpi mobile data collection system As an educator, Dr. Osgood teaches CMPT 858 (Dynamic Modeling for Public Health), Software Project Management (CMPT 371), and Advanced Software Engineering (CMPT 470 & CMPT 816). He has developed extensive teaching materials including numerous video lectures available on his YouTube channel and has organized multiple bootcamps on computational modeling for health applications. Dr. Osgood leads the Computational Epidemiology and Public Health Informatics Lab, where he supervises undergraduate, M.Sc., and Ph.D. students. His lab focuses on training students in computational modeling techniques and their application to public health problems. He has mentored numerous students who have gone on to careers in academia, public health agencies, and the tech industry.

Tauhidur RahmanView profile

Assistant Professor

• Mobile and Sensor Systems
• Artificial Intelligence
• Health Informatics
• +5 more

Tauhidur Rahman is an Assistant Professor at the Halıcıoğlu Data Science Institute, UC San Diego, and directs the MOSAIC Lab. His research focuses on mobile health technologies leveraging acoustic/electromagnetic signals from the human body/environment to monitor health behaviors (e.g., eating, sleep, addiction) and environmental factors (e.g., food quality, disease spread). His work integrates applied physics, machine learning, and embedded systems to create low-power, unobtrusive sensing solutions. Education: PhD in Information Science, Cornell University (2017) MS in Electrical Engineering, University of Texas at Dallas (2012) BS in Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology (2009) Research Interests: Rahman's work spans three core areas: Sensor Development: High-fidelity capture of physiological/environmental signals using novel modalities like backscattered waves Signal Interpretation: Algorithm development to map raw signals to behavioral/health metrics (e.g., eating patterns, opioid cravings) Mobile Computing: Efficient implementation of algorithms in low-resource devices Recent Trends in Publications: Recent work emphasizes opioid use tracking, mental health interventions, and digital epidemiology. Notable projects include FluSense (influenza surveillance) and OpiTrack (clinical opioid monitoring), demonstrating real-world impact through NIH/NSF/DARPA funding. Awards: Google Research Scholar Award 2023 Google PhD Fellowship 2016 ACM Ubicomp Best Paper Honorable Mention (2015) Outstanding Teaching Award (Cornell, 2015) Grants & Labs: Current funding includes NIH grants for opioid research and NSF awards for sleep/cognitive studies. His lab collaborates with clinical partners and industry (e.g., Intel Pandemic Response Initiative). He co-founded the Digital Biomarkers Workshop series and edited Springer's Contactless Human Activity Analysis .

Dimitrios D. PiromalisView profile

Associate Professor

• Electronic Embedded Systems
• Autonomous Vehicles
• Internet of Things (IoT)
• +7 more

Dimitrios D. Piromalis is an Associate Professor at the University of West Attica , specifically within the Department of Industrial Design and Production Engineering . He leads the Research Lab of Electronic Automation, Telematics and Cyber-Physical Systems (EATCPS) , focusing on electronic embedded systems for applications in autonomous vehicles, IoT, and cyber-physical systems. With over 120 publications and extensive industry collaboration spanning 25 years, his work bridges academic research and practical engineering solutions. Education : BSc, MSc, and PhD in Electrical and Electronics Engineering. Research Focus : Electronic embedded systems, autonomous vehicles, IoT, cyber-physical systems, digital twins, 3D/4D printing, energy management, and smart agriculture. Recent publications highlight trends in TinyML for smart cities, predictive maintenance integration, hybrid energy storage for EVs, and digital twin applications across agriculture and automotive sectors. His work also extends to emergency communication systems, biomedical sensors, and blockchain-enabled energy gateways. Industry Collaboration : Field Application Engineer and Technical Consultant for multinational semiconductor companies. Teaching : Platforms for AI and Python programming, autonomous vehicles and drones.

Marcus HandteView profile

Researcher

• Computer Science
• Pervasive Computing
• Sustainable Mobility
• +3 more

Dr. Marcus Handte is a Senior Researcher at the University of Duisburg-Essen, focusing on networked embedded systems, context-aware computing, and sustainable mobility. His academic journey includes a Habilitation in Computer Science (2013) and a PhD in Natural Sciences (2009) from Universität Stuttgart, alongside a Master's degree from Georgia Institute of Technology (2002). Research Interests Context-aware applications Localization and location-based systems Sustainable mobility solutions Internet of Things (IoT) Smart city infrastructure Privacy-preserving technologies His recent work involves developing platforms for multimodal mobility analysis (MOBYDEX), wireless EV charging systems (TALAKO, FAIR), and innovative approaches to indoor localization. Publications span journals like Machine Vision and Applications and conferences in pervasive computing. Scientific Recognition Best Poster Award at ACM KMIS 2023 Dr. Handte has contributed to projects such as ATMo2, INNAMORUHR, and GAMBAS, and maintains active collaborations across institutions. His expertise in adaptive middleware and distributed systems continues to shape research in smart mobility and ambient intelligence.

Charlie GarrodView profile

Academic

• distributed database systems
• computer science education
• teaching assistant mentorship
• +6 more

Charlie Garrod is an Associate Teaching Professor in the Software and Societal Systems Department within Carnegie Mellon University's School of Computer Science. His academic career focuses primarily on undergraduate computer science education and related areas such as teaching assistant and faculty mentorship. Institution: Carnegie Mellon University School: School of Computer Science Department: Software and Societal Systems Department Position: Associate Teaching Professor Dr. Garrod received his B.S. in Computer Science from Harvey Mudd College in 2001 and completed both his M.S. and Ph.D. in Computer Science at Carnegie Mellon University in 2006 and 2008, respectively. His educational background laid the foundation for his expertise in distributed database systems and software engineering education. His research interests center around computer data management systems, with particular emphasis on the performance, scalability, and power management of highly scalable distributed systems. As a teaching professor, his research program is intentionally focused on undergraduate and Master's student research projects rather than large-scale independent research. His work bridges theoretical computer science with practical applications in transportation information systems, mobile location services, and database scalability. Dr. Garrod's publication history reveals a strong trajectory in distributed systems and database technologies, with recent work shifting toward educational topics such as mentoring teaching assistants. His publications span prestigious venues including ACM Transactions on Algorithms, VLDB, ICDE, and SIGCHI, with his work on the Tiramisu transportation system earning a CHI 2011 Honorable Mention. His research demonstrates consistent contributions to database caching, query optimization, and consistency management for web applications. CHI 2011 Honorable Mention for 'Field Trial of Tiramisu: Crowd-Sourcing Bus Arrival Times to Spur Co-Design' As an educator, Dr. Garrod has mentored numerous students through formal courses and undergraduate research projects. He has developed and taught a wide range of courses including software design and engineering, algorithms and data structures, theoretical computer science, distributed systems, and databases. His teaching philosophy emphasizes practical application of theoretical concepts, with a focus on preparing students for real-world software engineering challenges. He has been actively involved in developing pedagogical approaches for computer science education, particularly in the mentorship of teaching assistants. Dr. Garrod maintains an active teaching schedule, currently instructing courses such as 15-210 Parallel and Sequential Data Structures and Algorithms, 17-480/17-780 API Design, and 07-070 Teaching Techniques for Computer Science. His extensive teaching portfolio demonstrates deep commitment to computer science education across multiple institutions and course levels.

Peter DanielisView profile

Professor

• Parallel Systems
• Distributed Computing
• Time-Sensitive Networking
• +4 more

Prof. Dr.-Ing. habil. Peter Danielis holds an Extraordinary Professorship in Parallel Systems at the Institute of Computer Science, University of Rostock. His research focuses on parallel and distributed systems with applications in time-sensitive networking, autonomous underwater vehicles, and industrial IoT. He serves as Deputy Director of the Institute of Computer Science (IFI) and participates in editorial boards for multiple conferences and journals. His primary research interests span Parallel Systems , Distributed Computing , and Time-Sensitive Networking , with significant contributions to mobile opportunistic networks and real-time communication in industrial settings. Current projects include cooperative navigation of autonomous underwater vehicles (AUVs) and distributed communication networks for IoT applications. His work bridges theoretical research with industrial implementation, particularly in deterministic networking for critical infrastructure. Analysis of his recent publications (2020-2025) reveals strong emphasis on Time-Sensitive Networking (TSN) for industrial automation, with 7 of 15 recent papers directly addressing TSN scheduling, reliability, and traffic management. Secondary focus areas include Autonomous Underwater Vehicle coordination (3 papers) and Mobile Opportunistic Networks for urban sensing. His methodology combines simulation, protocol design, and real-world validation. Professional affiliations include membership in the Institute of Electrical and Electronics Engineers (IEEE). He serves as TPC member and editorial board member for various conferences and journals. His teaching portfolio covers High Performance Computing, Operating Systems, and Complex Software Systems. As Deputy Director of the Institute of Computer Science, he oversees academic operations while maintaining active research leadership. His laboratory work focuses on real-time communication systems and underwater vehicle networks, utilizing simulation frameworks like OMNeT++ for protocol validation. Current research directions include adaptive TSN scheduling and cooperative AUV navigation in dynamic environments.

• Accessibility Research
• Web Accessibility
• Human-Computer Interaction
• +7 more

Chieko Asakawa is an IBM Fellow at T. J. Watson Research Center and IBM Distinguished Service Professor at Carnegie Mellon University's School of Computer Science. She concurrently serves as Chief Executive Director of the Japanese National Museum of Emerging Science and Innovation (Miraikan). With over three decades of experience in accessibility research, Dr. Asakawa has pioneered numerous technologies that have significantly advanced web accessibility for the visually impaired, including groundbreaking work in digital Braille and voice browser technology. Dr. Asakawa's research interests focus on developing cognitive assistant technologies that help blind individuals regain information by augmenting missing or weakened abilities through artificial intelligence. Her current work centers on practical applications for real-world navigation, including indoor navigation systems deployed at locations like Pittsburgh airport and shopping malls in Japan. She is leading the development of an innovative AI suitcase that enables blind users to navigate crowded or changing environments independently, enhancing their ability to enjoy urban spaces. Her research spans human-computer interaction, assistive robotics, computer vision, and AI applications for accessibility. Dr. Asakawa's recent publications demonstrate a clear trajectory toward increasingly sophisticated AI-powered navigation and assistance systems for the visually impaired. Her work has evolved from foundational web accessibility research to cutting-edge applications that bridge digital and physical worlds. Current projects integrate large language models, computer vision, and robotics to create comprehensive assistance systems that address complex real-world challenges faced by blind individuals in various environments including museums, shopping malls, and urban settings. Dr. Asakawa has received numerous professional honors, most notably: IBM Fellow - one of IBM's highest technical honors IBM Distinguished Service Professor at Carnegie Mellon University Dr. Asakawa leads the Cognitive Assistance Laboratory at Carnegie Mellon University, where she directs a team of researchers focused on advancing accessibility technologies. Her lab has secured significant research funding to develop practical navigation systems and other assistive technologies. She has mentored numerous researchers in the field of accessibility and has fostered collaborations between IBM Research, Carnegie Mellon University, and various institutions worldwide. The Cognitive Assistance Laboratory, under Dr. Asakawa's leadership, has developed several notable projects including the AI Suitcase initiative, which helps visually-impaired users independently navigate urban environments. The lab has also deployed practical navigation systems at Pittsburgh airport and in Japanese shopping malls, demonstrating the real-world impact of their research. Current team projects focus on integrating advanced AI techniques with practical navigation assistance to create seamless experiences for blind users in complex environments.

Feng WangView profile

Associate Professor

• Computer Networking
• Wireless Sensor Networks
• Peer-to-Peer Networks
• +7 more

Feng Wang is an Associate Professor in the Department of Computer and Information Science at the University of Mississippi, College of Engineering, specializing in computer networking, wireless sensor networks, and edge computing. He holds a PhD in Computing Science from Simon Fraser University (2012), and BEng and MEng degrees in Computer Science from Tsinghua University (2002, 2005). As an IEEE Senior Member, he has received multiple accolades, including the IEEE INFOCOM Distinguished TPC Member Award (2020) and ACM BuildSys Best Paper Award (2018). Research Interests: His work focuses on Wireless mesh and sensor networks Peer-to-Peer systems Internet of Things (IoT) and edge computing Big data and deep learning in networking Crowdsourcing for smart cities Cyber-physical systems Selected Scientific Awards: IEEE ICME Quality Reviewer Award (2011) ACM BuildSys Best Paper Award (2018) IEEE INFOCOM Distinguished TPC Member Award (2020) Chinese Government Scholarship (2009-2010) Simon Fraser University Fellowships (2005-2011) Professional Service: He served as Program Vice Chair for the International Conference on Internet of Vehicles (IOV’14) and TPC Co-Chair for IEEE CloudCom 2017 (IoT and Mobile on Cloud track). He is a Technical Committee Member for Elsevier Computer Communications and reviews for top-tier journals like IEEE/ACM Transactions on Networking.

Vinod AhujaView profile

Assistant Professor

• Open Source Software
• Citizen Science
• Data Science
• +3 more

Dr. Vinod Ahuja is an Assistant Professor in the Department of Computing & Software Engineering at U.A. Whitaker College of Engineering, Florida Gulf Coast University. He holds a Ph.D. in Information Technology and an MS in Management Information Systems from the University of Nebraska-Omaha, along with an MBA and Computer Science Diploma from Quaid-i-Azam University Islamabad, and additional certifications in banking from Institute of Bankers Pakistan. Research Interests: His work emphasizes open collaboration , particularly in open source software and citizen science , focusing on organizational engagement in open source development and volunteer performance in citizen science projects. His research spans interdisciplinary domains such as cybersecurity, automotive software, agricultural technology, and digital innovation. Publication Trends: His recent work (2025-2018) covers AI integration in open source, corporate boundaries in collaborative development, financial gains from open source, and methodologies for crowdsourced classification, with a focus on metrics for software impact and community engagement models. Professional Involvement: He actively contributes to the Linux Foundation Project CHAOSS as a maintainer and participates in peer review at major conferences including ICIS, AMCIS, and CSCW.