Find Academic Supervisors

Avi GoldfarbView profile

Professor

• Digital Economics
• Economics of Artificial Intelligence
• Information and Communications Technology
• +4 more

Avi Goldfarb is Professor of Marketing at the Joseph L. Rotman School of Management, University of Toronto, where he holds the Rotman Chair in Artificial Intelligence and Healthcare. He serves as Chief Data Scientist at the Creative Destruction Lab and Research Associate at the National Bureau of Economic Research (NBER). His academic career spans 2002-2012 as Assistant and Associate Professor, becoming Professor of Marketing in 2012. Rotman Chair in Artificial Intelligence and Healthcare (2018-present) Professor of Marketing (2012-present) Research Associate, NBER (2014-present) Chief Data Scientist, Creative Destruction Lab (2015-present) Research Interests : Specializing in digital economics and the economics of artificial intelligence, his work bridges technology, marketing, and public policy. Key focus areas include: Digital economics and platform behavior AI adoption in healthcare systems Quantum computing economic implications Privacy regulation and data markets AI's impact on labor and inequality General purpose technology frameworks Publication Trends : His recent work spans AI implementation strategies across industries, digital behavior economics, and emerging technology commercialization. Key subfields include AI adoption patterns, digital privacy frameworks, quantum computing applications, and workplace health safety analytics. Scientific Recognition : INFORMS Society of Marketing Science Long Term Impact Award (2018) Roger Martin Award for Excellence in Teaching (2017) Leadership Roles : Former Senior Editor at Marketing Science (2016-2021), with editorial board memberships at Management Science, Journal of Marketing Research, and Journal of Economics and Management Strategy. He contributes to the Acceleration Consortium and Schwartz Reisman Institute for Technology and Society.

Vincent RocaView profile

Researcher

• Privacy
• Robust Content Distribution
• Transport Protocols
• +6 more

Vincent Roca is a permanent researcher at Inria , a French national research institute for digital science and technology. Since 2019, he leads the Privatics research team focusing on privacy, previously part of the Planete team (2000-2012) for Internet protocols and applications. His work spans Privacy in smartphones, IoT, and web browsers Design of the ROBERT and CLEA protocols for the French TousAntiCovid app Standardization in IETF working groups, notably on FEC and network coding Co-author of Inria's cybersecurity white book (2019) Instructor of the popular Privacy in the digital world MOOC (14,006 participants) Research Interests include privacy risks in digital technologies, robust content distribution via FLUTE/ALC transport protocols and LDPC-Staircase FEC codes, and network coding for scalable services. His articles focus on privacy in LoRaWAN, contact tracing protocols, GDPR compliance, and FEC optimization. Scientific Awards include the Third Applied Research Price from FIEEC (2014) Knight Medal of the French Order of Merit (2020) Students supervised include PhD candidates in privacy-preserving IoT, secure authentication, and alumni like Samuel Pelissier (LoRaWAN privacy) and Michael Toth (GDPR compliance). Software Contributions include openfec.org (AL-FEC codes) and FLUTE/ALC implementations .

• Network and Service Management
• Cybersecurity
• Distributed Systems
• +5 more

Aiko Pras is a Professor at the University of Twente in Enschede, Netherlands. His research spans network and service management, cybersecurity, and distributed systems, with a focus on DNS security, DDoS mitigation, IPv6, and software-defined networking. Research Interests: Network and Service Management Cybersecurity and DDoS Mitigation DNS Security and IPv6 Software-Defined Networking (SDN) Internet Measurement and Performance Critical Infrastructure Protection (ICS/SCADA) Article Trends: Pras's recent work emphasizes collaborative DDoS defense, DNS security, and IPv6 vulnerabilities. His studies often involve large-scale measurements and propose practical solutions for internet resilience and security. Collaborations: He frequently collaborates with Anna Sperotto, Roland van Rijswijk-Deij, and other experts in network security and measurement.

• Environmental Engineering
• Water Quality
• Plumbing Systems
• +3 more

Andrew J Whelton is a Professor of Civil and Construction Engineering at Purdue University's College of Engineering, with concurrent appointments in Sustainability Engineering and Environmental Engineering. He serves as Director of the Healthy Plumbing Consortium and Lead for the Center for Plumbing Safety, focusing on water quality, chemical contamination, and public health in building plumbing systems. Professor, Civil and Construction Engineering Professor, Sustainability Engineering Professor, Environmental Engineering Director, Healthy Plumbing Consortium Lead, Center for Plumbing Safety His research spans environmental engineering and public health, with key themes including chemical contamination from plastic pipe degradation, post-disaster water system recovery, wildfire-related water quality impacts, and microbial risks in premise plumbing. Recent work addresses crises like the East Palestine chemical spill and Maui wildfires, while also developing predictive models for water quality and evaluating sustainable infrastructure materials. Scientific awards and recognitions include: Rapid Response Research (RAPID) Grants from NSF for disaster-related studies Environmental Protection Agency (EPA) support for building water quality programs Leadership in interdisciplinary consortia focused on plumbing safety Development of novel tools for water quality monitoring and remediation His publications reveal trends in: Chemical leaching from plastic piping materials Environmental justice in water contamination crises Integration of machine learning for water quality prediction Microbial ecology in stagnant plumbing systems Policy recommendations for disaster response Sustainable material innovation for infrastructure

Raffi KhatchadourianView profile

Associate Professor

• Software Engineering
• Programming Languages
• Software Evolution
• +5 more

Raffi Khatchadourian is an Associate Professor in the Department of Computer Science at Hunter College and the Graduate Center of the City University of New York (CUNY). His research focuses on techniques for automated software evolution, particularly automated refactoring and source code recommendation systems, with the goal of easing the burden associated with evolving large and complex software through automated tools. He also conducts research on the automated analysis of Object-Oriented programs. Ph.D., Computer Science & Engineering, Ohio State University (2011) MS, Computer Science & Engineering, Ohio State University (2010) BS, Computer Science, Monmouth University (2004) Khatchadourian's research spans multiple areas of software engineering and programming languages, with particular emphasis on automated software evolution techniques. His work addresses critical challenges in refactoring legacy systems to modern language constructs, optimizing parallel processing in Java 8 streams, and addressing technical debt in machine learning systems. His recent research has expanded into deep learning program transformation, where he develops techniques to convert imperative deep learning code to more efficient graph execution models while ensuring safety. His approach combines static analysis, program transformation, and empirical validation to create practical tools that developers can integrate into their workflows. Analysis of Khatchadourian's recent publications reveals a strong focus on bridging the gap between theoretical program analysis and practical software engineering challenges. His work increasingly intersects with machine learning systems, examining both how to improve ML code through refactoring and how to ensure safety in deep learning frameworks. The research demonstrates consistent evolution from foundational work on Java language features toward more complex systems involving concurrency, deep learning, and automated program transformation. Distinguished Paper Award at SCAM '18 for work on Java 8 stream optimization EAPLS Best Paper Award at FASE '20 for study on Java 8 stream usage EAPLS Distinguished Paper Award at FASE '25 for Deep Learning refactoring work Best Paper Award nominee at IJCAI '24 for AI safety framework Khatchadourian actively mentors graduate and undergraduate students, with several advisees going on to successful academic and industry positions. His former Ph.D. student Tatiana Castro Vélez accepted a tenure-track Assistant Professor position at the University of Puerto Rico. He has supervised numerous master's theses and undergraduate research projects, often resulting in co-authored publications at top software engineering venues. His research has been supported by various grants, though specific funding details are not prominently featured in the available information. Through his work on tools like Fraglight for aspect-oriented programming and Hybridize Functions for deep learning refactoring, Khatchadourian has established a research group focused on practical program analysis and transformation. His lab develops Eclipse plugins and other IDE-integrated tools that help developers with automated refactoring, bug detection, and code optimization. The group maintains active collaborations with researchers at other institutions and contributes to open-source projects on GitHub.

Daniel GermanView profile

Professor

• Software Engineering
• Software Evolution
• Open Source Software Development
• +4 more

Dr. Daniel German is a Professor in the Department of Computer Science at the University of Victoria, part of the Faculty of Engineering and Computer Science. He holds a PhD from the University of Waterloo, specializing in software engineering and open source ecosystems. His research focuses on software evolution, open source development practices, intellectual property issues in software systems, and licensing compliance challenges in modern AI/ML environments. German has contributed extensively to understanding dependency management, developer workflows, and legal aspects of software development. His work includes seminal studies on code provenance tracking (e.g., Cregit), library dependency management, and the sociotechnical dynamics of open source communities like the Linux kernel and GitHub ecosystems. German has explored critical topics such as licensing inconsistencies in software projects, ethical implications of AI-generated code, and the integration of open source components into proprietary systems. He is actively involved in software engineering education, examining how students engage with open source projects and the challenges of maintaining code quality in large-scale distributed systems. German’s research has practical implications for both academic and industrial software development practices, addressing real-world issues like security vulnerabilities in dependency chains and the legal risks of AI training data usage.

• Cyber-physical systems
• Green and sustainable computing
• Mobile and pervasive computing
• +7 more

Sandeep Gupta is a Professor and Director of the School of Computing and Augmented Intelligence at Arizona State University's Ira A. Fulton Schools of Engineering. He also serves as a Senior Global Futures Scientist. His work bridges computer science, engineering, and healthcare applications with a focus on creating reliable cyber-physical systems that interact safely with humans. Education: Ph.D. from The Ohio State University (1995) Research Interests: Professor Gupta's research spans cyber-physical systems, green and sustainable computing, mobile and pervasive computing, and parallel and distributed computing. His work increasingly focuses on human-in-the-loop systems where AI and humans collaborate safely, particularly in healthcare contexts. Recent research integrates large language models with cyber-physical systems to enhance safety and operational effectiveness in critical applications like medical monitoring and industrial automation. Research Trends: Analysis of Professor Gupta's recent publications reveals a strong focus on operational safety in human-AI collaborative systems, particularly in healthcare applications. His work combines physics-guided models with machine learning to detect "unknown-unknowns" in safety-critical systems, develops LLM-based approaches for medical image classification, and creates frameworks for ethical human-AI collaboration. The research increasingly addresses real-world challenges in diabetes management, epilepsy diagnosis, and industrial automation. Professional Service: IEEE Communication Letters Editorial Board, Area Editor (2008-Present) IEEE Journal on Special Areas in Communications - Issue on Body Area Network, Co-editor (2006-Present) Elsevier COMNET - Computer Network Journal, Reviewer (2008-Present) Technical Advisory Committee Chair for Networks (2005-Present) Advising and Grants: Professor Gupta has secured numerous research grants from NSF, NIH, Intel, Raytheon, and other organizations, totaling millions of dollars. His research portfolio includes projects on smart stadiums, mobile ECG sensing, power-aware scheduling, medical device verification, and sustainable data center management. He actively advises PhD and Master's students through thesis courses and research supervision, focusing on cyber-physical systems and healthcare applications. Labs and Research Groups: Professor Gupta leads research in cyber-physical systems with applications in healthcare, sustainable computing, and mobile networks. His work involves interdisciplinary collaboration across engineering, computer science, and medical domains, particularly through ASU's Global Futures initiatives.

Lorenzo SaniView profile

Researcher

• Federated Learning
• Edge Computing
• Privacy-Preserving Machine Learning
• +3 more

Lorenzo Sani is a PhD student in the Department of Computer Science and Technology at the University of Cambridge, supervised by Prof. Nicholas D. Lane and part of the CaMLSys research group. His work focuses on federated learning, edge computing, and privacy-preserving machine learning algorithms for large-scale distributed systems. Education: He holds a Bachelor's Degree in Physics from the University of Bologna (2019) and a Master's Degree in Applied Physics from the same institution (2021), with a thesis on unsupervised clustering of MDS data using federated learning. During his studies, he contributed to the GenoMed4All project and collaborated with the CaMLSys group on the Flower Framework. Research Interests: Sani's research emphasizes optimizing federated learning efficiency, privacy in distributed machine learning, and the application of federated techniques to large language models. His work addresses challenges in communication efficiency, client collaboration, and ethical data usage in decentralized systems. Teaching: He serves as a Teaching Assistant for the Principles of Machine Learning Systems (L46) and Federated Learning: Theory and Practice (L361) courses, and supervises students at Jesus College for Algorithm and Artificial Intelligence modules. Publications: His recent work includes innovations in federated optimization (DES-LOC, SparsyFed), LLM unlearning (LUNAR), and global federated training systems (Photon, Worldwide federated training). The 2020 Flower Framework paper established a foundational research tool for federated learning experimentation.

• Edge Computing
• Fog Computing
• Cloud Computing
• +7 more

Riccardo Lancellotti is an Associate Professor at the Department of Engineering 'Enzo Ferrari' of the University of Modena and Reggio Emilia. His research focuses on Edge/Fog/Cloud Computing, Cyber Security, and Resource Management in distributed systems. He has extensive contributions in optimizing infrastructure performance, load balancing, and energy efficiency in cloud and fog environments. His work often combines theoretical models with practical simulations, addressing challenges like stale information in edge systems and heterogeneous resource allocation in smart cities. Key research areas include: Fog/Edge computing infrastructure design and optimization Cloud resource provisioning and SLA compliance Security for Industry 4.0 and automotive systems Genetic algorithms for service placement Scalable VM clustering and resource allocation Publications highlight trends in cloud/fog integration, robust game theory for microservices, and distributed load balancing under dynamic conditions. His work emphasizes practical applications, such as pharmaceutical distribution routing and smart city sensor management. No awards are explicitly listed, but his extensive publication record reflects recognition in the field.

• Cybersecurity
• Privacy
• Industrial Networks
• +7 more

Martin Henze is a tenure-track Assistant Professor at RWTH Aachen University's Department of Computer Science, where he leads the Security and Privacy in Industrial Cooperation (SPICe) research group. Additionally, he co-leads the Secure Production & Energy Networks research group at the Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE in Bonn, Germany. His work bridges academic research with practical industrial security applications, focusing on critical infrastructure protection. Dr. Henze's research interests center on technical security and privacy aspects of industrial networks and data sharing, with special emphasis on energy and production sectors. His work spans industrial intrusion detection, 5G security for industrial applications, IoT security in constrained environments, and blockchain security. He develops practical security solutions that balance protection needs with the resource constraints and operational requirements of industrial systems, particularly focusing on making security both effective and comprehensible for operators. His recent publications demonstrate a strong focus on industrial security challenges, with particular emphasis on intrusion detection systems that maintain operator control, TLS optimization for resource-constrained industrial IoT, 5G security for production systems, and novel approaches to securing legacy industrial protocols. His work consistently addresses the tension between security requirements and operational constraints in industrial settings. Nachwuchsförderpreis Verbraucherforschung NRW Borchers-Plakette ICT Young Researcher Award Dr. Henze actively contributes to the academic community through service on numerous prestigious program committees including ACM CCS, IEEE S&P, NDSS, and USENIX Security. His teaching portfolio includes graduate courses on Industrial Data Security, Industrial Network Security, and specialized seminars on 5G/6G Security and IoT Security. His research is highly collaborative, frequently involving partnerships across institutions and with industry to address real-world security challenges in critical infrastructure. He heads the SPICe research group at RWTH Aachen, which focuses on developing practical security and privacy solutions for industrial cooperation scenarios. The group's work emphasizes creating security mechanisms that are not only technically sound but also comprehensible and usable by industrial operators, recognizing that the human element is critical in maintaining security in complex industrial environments.

• Water Security
• Climate Change
• Public Health
• +11 more

Corinne Wallace is an Adjunct Assistant Professor in the Department of Civil Engineering at McMaster University , with research expertise at the intersection of water security, climate change, public health, and gender equity. Her work spans both technical engineering analysis and community-engaged studies, particularly focusing on marginalized populations in Canada, East Africa, and South America. Dr. Wallace's research interests include: Water-Health Nexus Climate Change Impacts on Disease Gender Equity in Water Access Indigenous Water Governance Mosquito-Borne Disease Modeling Rainwater Harvesting Systems Her publication trends show increasing focus on climate-health interactions (2025), gender-water linkages (2024), and machine learning applications for water quality analysis (2025). She employs mixed-methods approaches and works closely with First Nations communities and international development organizations. Dr. Wallace utilizes art-science communication strategies like the Virtual Water Gallery to transform water and climate knowledge dissemination. Her recent work explores EDI (Equity, Diversity, Inclusion) implementation in large research networks and conceptual frameworks for climate-water equity.

Patrick LamView profile

Associate Professor

• Static Program Analysis
• Verifiable Software Specifications
• Software Engineering
• +8 more

Patrick Lam is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, with a cross-appointment to the Cheriton School of Computer Science. His research focuses on applications of programming languages and static analysis to software engineering challenges, emphasizing verifiable software specifications and program understanding. Dr. Lam has held significant grants from NSERC and is recognized for his impactful work, including the First Decade High Impact Paper award for his Soot framework. Education: Doctorate in Computer Science, Massachusetts Institute of Technology, 2007 Master's in Computer Science, McGill University, 2000 Bachelor's in Joint Honours Mathematics and Computer Science, McGill University, 1999 Research Interests: His primary areas include static program analysis, verifiable software specifications, and compiler design, with a focus on linking high-level software designs to low-level implementations. He explores techniques like lightweight specifications and domain-specific languages to enhance software reliability and efficiency. Recent work also addresses empirical studies of programming practices and security through modularization. Publications: Dr. Lam's recent publications span advancements in static analysis tools (e.g., WasmWalker for WebAssembly), formal verification of code generated by AI tools like GitHub Copilot, and empirical studies on C++ immutability usage. His work bridges theoretical programming language research with practical software engineering applications, emphasizing tools for developer productivity and code reliability. Awards and Recognition: First Decade High Impact Paper recognition for "Soot – A Java Optimization Framework" (2010) Teaching and Grants: He has taught courses such as CS 447, ECE 453, and ECE 459 on software testing and performance programming. Active in grant-funded research, he secured NSERC Engage Grant (2013) and an ongoing NSERC Discovery Grant (2013–2018). Lam has also advised graduate students and contributed to the Software Engineering Program at Waterloo as its Director (2016–2019). Labs and Teams: His research group explores topics in program analysis and software engineering, with collaborations on projects like abstract debugging tools (GobPie) and static analysis frameworks (Soot). He maintains an open-source repository on GitHub, contributing to educational materials and research tools.

Hamid ZargariaslView profile

Researcher

• Computer Networks
• IoT and Sensor Technology
• RFID Systems
• +3 more

Dr. Hamid Zargariasl is a Researcher in the Computer Engineering Department at BTU Cottbus-Senftenberg. His work focuses on IoT systems, RFID technology, social network analysis, and distributed computing. He leads the UBICO Team and contributes to the Computer Engineering Group, exploring interdisciplinary applications of telecommunications and sensor networks. His research integrates theoretical frameworks with practical implementations, addressing challenges in smart city infrastructure, healthcare systems, and educational technology. Key research areas include optimizing RFID and sensor performance, analyzing social object interactions in IoT networks, and developing protocols for distributed computing. His experimental studies bridge academic performance metrics with mobile social network dynamics, and he has pioneered methodologies for network integration and centrality analysis in evolving systems. Publications span 15 years (2009–2024), emphasizing real-world data analysis and system optimization. Notable work includes enhancing digital thread functionality in aerospace engineering and evaluating smart parking sensor technologies. His contributions inform both technical systems and socio-economic policy recommendations. Dr. Zargariasl collaborates within interdisciplinary teams, contributing to the BTU's research initiatives while maintaining active engagement in the academic community through lectures and student mentorship.

Alex C. SnoerenView profile

Professor

• Computer Networks
• Distributed Systems
• Networking Security
• +5 more

Alex C. Snoeren is a Professor in the Department of Computer Science and Engineering at the University of California, San Diego (UCSD). He is affiliated with the Systems and Networking Research Group, the Security and Cryptography Research Group, and the Center for Networked Systems. His work focuses on distributed systems, networking, and security, with notable contributions to data center networking, optical systems, and network measurement. He has advised numerous PhD students and has been actively involved in teaching courses such as CSE 120 (Principles of Computer Operating Systems), CSE 123 (Computer Networks), and graduate-level systems and networking courses. His research has led to innovations in network architecture, including projects like RotorNet (optical data center networking) and Eden (far memory integration). Key awards include the Best Paper at ACM SIGCOMM 2023 and multiple best student paper recognitions. His work spans both theoretical and applied domains, addressing challenges in network scalability, security, and efficiency.

Michael K. ReiterView profile

Professor

• Computer Security
• Distributed Systems
• Applied Cryptography
• +3 more

Michael K. Reiter is a Professor at Duke University in the Department of Computer Science and Department of Electrical & Computer Engineering . He received his Ph.D. in Computer Science from Cornell University (1993) and held academic positions at Carnegie Mellon University and UNC Chapel Hill. Research Focus: Computer and network security, distributed systems, and applied cryptography. Notable Contributions: Pioneering work in Byzantine fault tolerance, malware detection, privacy-preserving protocols, and human-verifiable authentication. Leadership: Founding Technical Director of CyLab at Carnegie Mellon, program committee roles at top security conferences. Recent Publications emphasize: Machine learning security (adversarial training, backdoor detection) Blockchain consensus mechanisms (asynchronous BFT, random beacons) Privacy-enhancing technologies (differential privacy, private set intersection) Side-channel mitigation in cloud environments Awards & Recognition: ACM Fellow (2008) James B. Duke Distinguished Professor