Find Academic Supervisors

• Software Engineering
• Machine Learning Operations (MLOps)
• Cyber-Physical Systems
• +4 more

Prof. Dr. Klaus Schmid is a Professor in the Department of Software Systems Engineering at the University of Hildesheim, part of the Faculty of Mathematics, Natural Sciences, Economics, and Computer Science. His research focuses on Machine Learning Operations (MLOps), software product lines, adaptive systems, and variability modeling. He leads projects such as EXPLAIN and ReGaP, emphasizing explainable AI and industrial MLOps integration. His work addresses challenges in Cyber-Physical Production Systems (CPPS), including data management, model calibration, and domain knowledge integration. Key research interests include MLOps architecture design, variability modeling transformations (e.g., UVL to IVML), and incremental verification techniques for software product lines. He has published extensively in venues like IEEE ETFA, IEEE Software, and SPLC conferences. Notable achievements include a Best Paper Award for work on control patterns in self-adaptive systems. Collaborations with industry partners highlight his focus on bridging academic research and practical industrial applications. Prof. Schmid’s contributions extend to tool development, such as EASy-Producer for variability-aware software ecosystems, and frameworks for environment modeling in adaptive systems. His research addresses both foundational challenges (e.g., syntax-preserving slicing) and applied topics like MLOps platform comparisons and industrial case studies in Industry 4.0.

Giorgio C. ButtazzoView profile

Professor

• Real-Time Systems
• Heterogeneous Computing
• Robotics
• +4 more

Giorgio C. Buttazzo is a Full Professor of Computer Engineering at the Scuola Superiore Sant'Anna in Pisa, Italy, and founder/director of the RETIS Lab. His career includes roles at the University of Pavia and co-founding Evidence s.r.l. (a real-time embedded systems company). He holds an IEEE Fellowship (2012) and the IEEE TC RTS Outstanding Technical Contributions Award (2013). Education: Electronic Engineering (University of Pisa, 1985), Master in Computer Science (University of Pennsylvania, 1987), PhD in Computer Engineering (Scuola Superiore Sant'Anna, 1991). Affiliations: TeCIP Institute, RETIS Lab, and leadership roles in IEEE Technical Committees. Research focuses on real-time systems, robotics, and AI integration. He has authored 10 books, over 300 papers, and pioneered frameworks like the ERIKA/SHARK kernels. Current projects include RETICULATE, OPERAND, and NANCY (5G networks). Teaching includes Real-Time Systems, Neural Networks, and Jazz Guitar Improvisation. Advised over 150 master and PhD students. Active in conferences like ECRTS, RTSS, and RTAS.

Christian HaubeltView profile

Professor

• Embedded Systems
• Cyber-Physical Systems
• Smart Sensors
• +9 more

Christian Haubelt is a Professor at the Institute of Computer and Network Engineering, School of Engineering, University of Rostock, Germany. He is actively engaged in research and teaching in the areas of embedded and cyber-physical systems, smart implants, and IoT. His work is supported by multiple national and international projects including ELAINE (SFB 1270), SmILE (EU), 6G-Health (BMBF), and GenerIoT (BMBF). His research interests include: Embedded and Cyber-Physical Systems Smart Sensors and Smart Implants System-Level Design Methodologies SystemC-based Modeling and Verification Design Space Exploration and Multi-Objective Optimization Industrial Internet of Things and 6G for Healthcare His recent publications focus on real-time communication protocols, 5G/6G localization, smart implants, and secure IoT systems. Trends show a strong emphasis on integrating embedded systems with medical and industrial applications, particularly leveraging TSN, MQTT-SN, and OPC UA for reliable and secure communication. His work bridges theoretical modeling with practical implementation in safety-critical domains. Christian Haubelt has supervised multiple researchers including Michael Nast, Benjamin Rother, Nico Kalis, and Nico Graumüller. He leads several funded research projects such as ELAINE, SmILE, 6G-Health, and SUSTAIN, which focus on smart implants, secure IoT, and next-generation medical systems. These projects involve collaboration with DFG, EU, and BMBF. He is involved in the following research labs and teams: Embedded Systems and Cyber-Physical Systems Group Smart Implants Research Team (SmILE, ELAINE) 6G-Health Localization Team Industrial IoT Security (SUSTAIN, CargoAssist)

Changhee JungView profile

Associate Professor

• Compilers
• Computer Architecture
• Performance Optimization
• +8 more

Changhee Jung is the Samuel D. Conte Associate Professor in the Department of Computer Science at Purdue University. His research focuses on compilers and computer architecture with an emphasis on performance, reliability, and security. His educational background includes a Ph.D. from Georgia Tech (2013) under the supervision of Prof. Santosh Pande. Professor Jung's research spans compilers and computer architecture with a focus on performance, reliability, and security. He has developed program analysis and microarchitecture optimization techniques for soft error resilience, concurrency bug detection, and system security such as memory safety and Linux kernel permission check. Currently, he is working on energy-efficient intermittent computation and nonvolatile memory crash consistency. He often leverages compiler-architecture codesign and repurposes existing hardware features to develop cost-effective solutions for complex computing challenges. His recent publications demonstrate a clear trajectory toward intermittent computing systems, nonvolatile memory architectures, and security mechanisms for energy-constrained environments. His work shows innovative approaches to power failure recovery, capacitor vulnerability exploitation, and EMI attack defense in intermittent systems, with significant contributions to whole-system persistence, cache design, and prefetching techniques for low-power computing. His notable scientific achievements include: NSF CAREER Award (2018) Inducted into MICRO Hall of Fame (2021) Best Paper Honorable Mention in ISCA 2025 Memorable Paper Award Finalist in NVMW 2024 Dissertation Advisor of 2023 ACM SIGBED Paul Caspi Memorial Dissertation Award winner Jongouk Choi 2017 AMD Faculty Research Award Professor Jung has successfully advised numerous graduate students, many of whom have secured prominent positions at leading technology companies including Google, Intel, and Samsung Electronics. His lab, the CompArch (Compiler and Architecture) research group, was formed in 2013 at Virginia Tech and continues at Purdue, focusing on compiler-architecture cooperation to address cross-cutting concerns involving performance, reliability, and security. The lab has received significant research funding, including an NSF CAREER Award in 2018 and an AMD Faculty Research Award in 2017.

Philipp TuertscherView profile

Professor

• Collaborative Innovation
• Open Innovation
• Innovation Processes
• +6 more

Philipp Tuertscher serves as Full Professor of Collaborative Innovation at Vrije Universiteit Amsterdam's School of Business and Economics, where he leads research within the Knowledge, Information and Innovation department and the KIN Center for Digital Innovation since 2013. His work bridges organizational theory with digital innovation practices across scientific, corporate, and community settings. Education: PhD in Management, University of St. Gallen (awarded 2009; research period 2003-2007) Tuertscher's research investigates how collaborative innovation emerges through social practices and organizational mechanisms. His fingerprint reveals dominant expertise in Open Innovation (spanning Computer Science and Social Sciences), Innovation Processes, and Digital Product Platforms, with significant contributions to understanding knowledge integration in complex systems like CERN and community-driven innovation in Wikipedia/Linux ecosystems. Recent work increasingly addresses sustainability challenges through crowdsourcing and multi-stakeholder problem-solving. His publication trajectory demonstrates consistent focus on collaborative innovation architectures, showing evolution from foundational studies of scientific collaborations (2014) to contemporary examinations of digital platform ecosystems (2021) and sustainable impact scaling (2020-2023). The work integrates management theory with practical applications in technology-intensive environments. Scientific Awards: Distinguished Winner of the Award for Responsible Research in Management (2022) JMS Best Paper Award (2020) AOM Best Paper Award (2020) SBE Education Award (2021) Professor Tuertscher actively mentors doctoral researchers including Diriker and Porter, and leads major initiatives like The Impact Lab: SBE Future of Learning Challenge. His funded projects include the €750,000 NWO Open Competition OPEN-QUAL grant (2022) focused on innovation management. He maintains strong international collaborations evidenced by co-authored work with institutions like Pennsylvania State University. As a core member of the KIN Center for Digital Innovation, he contributes to interdisciplinary teams advancing digital transformation research, with recent activities targeting data commons for biodiversity and climate impact initiatives through relational infrastructures.

Binoy RavindranView profile

Professor

• Computer Systems
• Software Verification
• Concurrency
• +7 more

Binoy Ravindran is a Professor at Virginia Tech’s College of Engineering, Department of Electrical and Computer Engineering, leading the Systems Software Research Group (SSRG). His research focuses on computer systems, emphasizing security, performance, concurrency, distributed systems, and real-time computing, with recent work in software verification and heterogeneous-ISA platforms. Key projects: Low-level Reasoning Machine (LLRM), Popcorn Linux, LibrettOS, Hyflow, HermiTux, SlimGuard, HydraVM, KairosVM. He has co-authored 15+ papers from 2025 to 2022, spanning venues like ASPLOS, POPL, PLDI, VEE, PPoPP, and MIDDLEWARE, with awards including ACM Distinguished Scientist and eight Best Paper Awards. Service roles: Editorial Boards (IEEE Transactions on Cloud Computing, ACM TECS), Program Co-Chair (ACM Systor 2025), Committee memberships across ASPLOS, PLDI, and more.

Gustavo Adolfo Junipero Rodriguez-RiveraView profile

Academic

• Operating Systems
• Computer Networks
• Memory Management
• +11 more

Gustavo Rodriguez-Rivera is an Associate Teaching Professor in the Department of Computer Science at Purdue University, part of the School of Science. He joined the department in 2000 and holds a Ph.D. in Computer Science from Purdue University (1998), an M.S. in Electrical Engineering from ITESM Campus Monterrey (1990), and a B.S. in Electrical Engineering from the same institution (1985). His research focuses on Operating Systems, Computer Networks, Memory Management, Embedded Systems, Real-Time Systems, and broader areas like Numerical Analysis and Artificial Intelligence. Dr. Rodriguez-Rivera has received multiple teaching awards, including the ACM Faculty Award in Computer Science (2020, 2023) and Best Teacher in the School of Science (2014, 2016). His work spans software engineering education, structural health monitoring for wind turbines, and memory management algorithms. Notable publications include studies on garbage collection techniques, real-time project tracking in programming courses, and vibro-acoustic modulation for turbine blade inspection. He has advised numerous projects and contributed to grants such as the NSF-funded work on wind turbine blade monitoring. His academic contributions also include developing secure programming course modules and tools for interactive debugging systems.

Benjamin Mako HillView profile

Associate Professor

• Online Communities
• Peer Production
• Social Dynamics
• +4 more

Benjamin Mako Hill is an Associate Professor in the Department of Communication at the University of Washington, with adjunct roles in Human-Centered Design & Engineering, Computer Science & Engineering, and the Information School. He is also a Faculty Associate at Harvard’s Berkman Klein Center and a Fellow at Princeton’s Center for Information Technology Policy (2023–2024). His research focuses on online communities, peer production (e.g., Wikipedia, Linux), and how technology design influences social outcomes. He holds a PhD from MIT in Management and Media Arts & Science. Education: PhD (2013) and MS (2007) from MIT, BA (2003) from Hampshire College. Awards include the Dordick Award for Best Dissertation (2013) and multiple best paper honors at CHI and CSCW conferences. Research interests span digital public goods, collaborative knowledge systems, and socio-technical dynamics. His work has been supported by grants from the National Science Foundation (e.g., $549,959 CAREER grant for digital knowledge commons research) and the Alfred P. Sloan Foundation. Publications span journals like Proceedings of the ACM on Human-Computer Interaction and Journal of Computer-Mediated Communication , with over 50 peer-reviewed articles. He co-founded the Community Data Science Collective and leads projects on open source sustainability, governance of digital communities, and computational social science.

Xing XinyuView profile

Associate Professor

• Kernel Security
• Reverse Engineering
• AI Security
• +3 more

Xing Xinyu is an Associate Professor of Computer Science at Northwestern University's McCormick School of Engineering. Their research focuses on kernel security, reverse engineering, and AI security, with a strong emphasis on fuzzing techniques, adversarial machine learning, and vulnerability discovery. They hold a PhD from Georgia Institute of Technology, an MS from the University of Colorado Boulder, and a BASc from Beihang University. Research interests include advanced cybersecurity methodologies such as heap memory protection, automated exploit generation, and defense mechanisms against adversarial attacks on large language models. Their work bridges theoretical computer science with practical applications in system security and AI ethics. Publications span topics like LLM jailbreak assessments, reinforcement learning optimization, and blockchain anomaly detection. Notable contributions include frameworks like BandFuzz for collaborative fuzzing and SeaK for secure kernel allocators.

Mark StockmanView profile

Associate Professor

• Cybersecurity
• Cloud Computing
• Virtualization
• +6 more

Mark A. Stockman is an Associate Professor at the University of Cincinnati, specializing in cybersecurity, cloud computing, and system administration. He holds a BS in Industrial and Systems Engineering from Ohio University's Russ College of Engineering and Technology (1992) and an MBA in Management from Ohio University's College of Business (1994). His research focuses on integrating social science principles into cybersecurity education, developing cloud-based educational infrastructure, and analyzing cybercrime prevention strategies. Notable contributions include pioneering work on honeynet systems for hacker behavior analysis and organizational cybersecurity victimology frameworks. Stockman has published extensively on topics like insider threat mitigation, IT curriculum design, and virtualization technologies. His work bridges technical cybersecurity practices with organizational risk management, emphasizing interdisciplinary approaches to modern IT challenges. He has advised on multiple educational initiatives including cloud lab development and remote-access systems for computing disciplines. His publications reflect a commitment to advancing both technical and pedagogical innovations in information technology.

Djamel E. KhelladiView profile

Researcher

• Software Engineering
• Model-Driven Engineering
• Software Evolution
• +6 more

Djamel E. Khelladi is a CNRS researcher affiliated with the IRISA research lab and the DIVERSE team at University of Rennes 1 , France. Previously, he held postdoctoral and PhD positions at Johannes Kepler University (JKU) Linz, Austria, and Université Pierre et Marie Curie (UPMC), France. Research interests include: Model-Driven Engineering Software Evolution & Co-evolution AI and Generative AI Applications Polyglot Programming Digital Twins Recent article trends focus on integrating Large Language Models (LLMs) for code-metamodel co-evolution, polyglot programming challenges, incremental build optimization in configurable systems, and empirical studies on software evolution. His work often bridges theoretical modeling with practical implementation in industrial contexts. Academic service roles include: Proceedings Co-Chair @MODELS 2025 Co-Organizer of Models and Evolution (ME) workshops (2023-2025) Co-Editor for special issue on Model Driven Engineering for Digital Twins (SoSym 2024/25) PC member in top venues: ICSE , ASE , MODELS , ECMFA , MSR , FSE

Maha ShaikhView profile

Associate Professor

• Open Source Software
• Public Sector Digital Transformation
• Information Systems Governance
• +3 more

Maha Shaikh is an Associate Professor at the Department of Operations, Innovation and Data Sciences within Esade Business School , Ramon Llull University. She holds an ORCID identifier 0000-0001-5110-1619 and maintains an active research agenda across multiple domains of information systems and open technology.

• Music Composition
• Electronic Music
• Laptop Orchestras
• +7 more

Bruno Tucunduva Ruviaro is an Associate Professor in the Department of Music within the College of Arts and Sciences at Santa Clara University, where he has taught since Fall 2012. Originally from Brazil, Ruviaro is a composer and performer with a specialization in electronic music. Prior to joining Santa Clara, he studied and worked at the Center for Computer Research in Music and Acoustics (CCRMA) at Stanford University. Ruviaro's primary research focus is Music Composition with a strong emphasis on Electronic Music. His specific interests include electronic music composition, laptop orchestras, live-electronics, acousmatic music, and sampling & musical borrowing. He also explores secondary interests spanning theater, dance, linguistics, speech, radio art, Linux, intellectual (im)property issues, and the intersection of music & politics. His work demonstrates a consistent exploration of how technology transforms musical creation and performance. Ruviaro's scholarly output reveals a strong trajectory in electronic and computer music composition, with particular attention to laptop orchestras and musical borrowing practices. His recent works like Pós-Tudos and Mozart and the Elections demonstrate his continued innovation in contemporary composition, while publications such as From Schaeffer to* lorks and Intellectual Improperty reveal his theoretical engagement with the evolving nature of musical instruments and copyright in digital contexts. His compositions frequently incorporate technology in innovative performance setups, as seen in works utilizing smartphones and unconventional sound production methods. Ruviaro is the director of SCLOrk (Santa Clara Laptop Orchestra), continuing a tradition from his time at Stanford where he was part of SLOrk (Stanford Laptop Orchestra). He teaches courses including Intro to Electronic Music (MUSC 9), SCLOrk - Santa Clara Laptop Orchestra (MUSC 157), Music Theory III (MUSC 3), Experimental Sound Design (MUSC 115), Form and Analysis (MUSC 113), and Beginning Composition (MUSC 37), along with private composition lessons. His educational contributions include A Gentle Introduction to SuperCollider , making complex music programming more accessible to students.

• Software Reusability
• Reverse Inheritance
• E-Learning
• +5 more

Ciprian Bogdan Chirila is a Senior Lecturer at the University Politehnica of Timisoara (Faculty of Automation and Computer Science, Computing and Information Technology Department) and also teaches at Ioan Slavici University . His career spans over two decades, with roles in teaching, research, and software development. Education : PhD in Computer Science (2010, University Politehnica Timisoara & University Nice-Sophia Antipolis) Master's in Computer Science & Software Engineering (2002) Engineer Diploma in Automation & Computer Science (2001) Analyst-Programmer Diploma (1996) Research Interests : His work focuses on reverse inheritance for software reusability, generative learning objects for education, and software quality assessment using code metrics. He explores interdisciplinary applications in healthcare, mathematics education, and industrial IT services. Article Trends : Recent publications emphasize adaptive e-learning frameworks , gamification in education , and model-driven development . Key themes include automated assessment , dynamic content generation , and integration of standards like SCORM and xAPI . Scientific Awards : Microsoft Award, Student Scientific Communications Session (2001) Award, Student Scientific Communications Session (2002) Third Place, Mechanics and Robotics Contest (1998) Fourth Place, Traian Lalescu Mathematics Contest (1998) Teaching & Development : He has led laboratory sessions and lectures in Data Structures , Compiler Design , Operating Systems , and Heuristic Methods . He organizes programming contests and develops centralized materials management software as a volunteer engineer.

Marwa KeshkView profile

Lecturer

• Cyber Security
• Artificial Intelligence
• Privacy Preservation
• +5 more

Dr. Marwa Keshk is a Lecturer in Cyber Security at the School of Professional Studies, University of New South Wales (UNSW) Canberra. Her academic career focuses on the intersection of cybersecurity and artificial intelligence, with particular expertise in privacy preservation, anomaly detection, and threat intelligence. Her educational background includes: PhD in Cyber Security and Privacy Preservation (2021) from UNSW Master's degree in Evolutionary Computation (2017) from UNSW Bachelor's degree in Computer Science (2012) from the Faculty of Computers and Information at Helwan University, Egypt Dr. Keshk's research interests primarily center around the application of artificial intelligence and machine learning techniques to enhance cybersecurity measures. Her work explores how computational intelligence, statistical methods, and emerging technologies can be leveraged for privacy preservation, anomaly detection, and threat intelligence. She has made significant contributions to the security of Internet of Things (IoT) networks, cyber-physical systems, and critical infrastructure protection. Her research often combines theoretical advancements with practical applications, addressing real-world security challenges in increasingly connected digital environments. Analysis of Dr. Keshk's publication history reveals a strong focus on applying AI and machine learning to cybersecurity challenges, particularly in IoT environments. Her work demonstrates a progression from foundational research in evolutionary computation to specialized applications in cybersecurity. Recent publications show increasing emphasis on explainable AI for security applications, reflecting the growing need for transparency in security decision-making processes. Her research spans multiple domains including smart cities, industrial control systems, and power networks, demonstrating the versatility and wide applicability of her security frameworks. Dr. Keshk has received notable recognition for her academic work: UNSW Tuition Fee Scholarship for PhD Research (2018-2021) Data61/CSIRO Scholarship (2019-2021) During her PhD studies, Dr. Keshk was a research candidate at Data61-CSIRO in Australia, providing her with valuable industry experience alongside her academic pursuits. Her collaborative approach to research is evident in her extensive co-authorship with colleagues across various institutions, particularly with researchers from UNSW and other Australian universities. Dr. Keshk's work contributes significantly to several research teams and initiatives focused on cybersecurity and AI at UNSW Canberra. Her expertise complements broader efforts in secure systems development, particularly in the context of increasingly connected environments where traditional security boundaries are challenged by new technologies.