Find Academic Supervisors

Mara NikolaidouView profile

Professor

• Distributed Systems
• System Modeling
• Digital Libraries
• +9 more

Mara Nikolaidou is a Professor in the Department of Informatics and Telematics at Harokopio University of Athens since 2007 and has served as the university's Rector since 2016. She represents Greek universities in the European University Association (EUA) for 2023-2024. Her research focuses on distributed systems, system modeling, and responsible computing, with a strong emphasis on IoT, cloud/edge computing, and cyber-physical systems. She leads projects funded by national, EU, and international agencies, exploring topics like autonomous systems, ethical requirements in design, and human-in-the-loop systems. Her educational background includes roles as a computer engineer and IT consultant before academia. She is a member of IEEE (SMC Society and Systems Council) and participates in the Object Management Group (OMG) working groups for SysML and responsible computing. She organizes international conferences in software and systems engineering. Research interests span distributed systems, IoT, and ethical computing. Recent work investigates cost analysis in cloud markets, human-AI collaboration, and smart city technologies. Over 200 publications highlight her contributions to model-based systems engineering, including SysML extensions for cost/QoS analysis and frameworks for autonomous fog nodes. Grants and projects include EU-funded initiatives on smart farming, cloud brokerage, and organizational interoperability. Her lab focuses on autonomous systems and context-aware middleware. She advises on e-Government compliance frameworks and collaborates with industry partners on IoT management platforms.

Yu ZhangView profile

Assistant Professor

• NLP and Data Mining for Science
• NLP with Graphs and Structural Knowledge
• NLP under Weak Supervision
• +6 more

Yu Zhang is an Assistant Professor at the Department of Computer Science & Engineering at Texas A&M University, leading the SKY Lab. He holds a Ph.D. and M.Sc. from the University of Illinois at Urbana-Champaign (UIUC), advised by Jiawei Han, and a B.Sc. from Peking University. His research focuses on NLP and data mining for scientific domains, graph-augmented NLP, and weakly supervised learning. He has been recognized with the ACM SIGKDD Dissertation Award Runner-Up and multiple outstanding reviewer awards. Education: Ph.D. and M.Sc. in Computer Science, UIUC (201X-201X) B.Sc. in Computer Science, Peking University (201X-201X) Professional Roles: PC Area Chair for KDD 2026, ACL 2025, NeurIPS 2025 Co-organizer of SKnowLLM and MLoG-GenAI workshops His research interests span NLP applications in biology, medicine, and mathematics; graph-based NLP techniques; and LLMs under weak supervision. He has published extensively in top venues like ACL, KDD, and EMNLP, focusing on scientific LLMs, knowledge graphs, and automated reasoning. Key awards include the ACM SIGKDD Dissertation Award Runner-Up (2025) and multiple best paper/poster awards. He teaches graduate courses on NLP for Science (CSCE 689) and Information Storage and Retrieval (CSCE 670).

• Electronic Design Automation
• Energy Efficient Electronic Systems
• Low Power Design
• +12 more

Andrea Calimera is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. He is actively involved in teaching and research, contributing to doctoral programs and undergraduate and graduate courses in computer engineering and data science. Full Professor (L.240), Polytechnic University of Turin Department of Control and Computer Science (DAUIN) Member, SmartData@PoliTO - Big Data and Data Science Laboratory Member, College of Computer, Film and Mechatronics Engineering His research interests center on electronic design automation, energy-efficient electronic systems, and low-power design, with strong connections to artificial intelligence, embedded systems, and IoT. His work bridges hardware and software optimization for intelligent edge devices. The recent publications (2023–2025) reflect a focused trend on federated learning, secure and efficient AI deployment on edge devices, and low-power embedded systems. Topics include robust evaluation in federated learning, resource management under label skew, homomorphic encryption for private tensor operations, pipeline optimization for keyword spotting, and side-channel attacks via DVFS for neural network fingerprinting—highlighting expertise in both performance and security of AI systems on constrained hardware. Andrea Calimera supervises PhD and master's students and leads research projects funded by competitive and commercial grants. He has contributed to national and international patents on low-power depth estimation and single-image signal processing. Scientific Director, SENSEI Project (2017–2019): Energy-efficient machine learning on chip for IoT Scientific Director, Commercial Project (2020–2022): Design tools for AI on energy-efficient embedded mobile devices Supervision of PhD student Erich Malan (ongoing, since 2022) on distributed and federated learning over IoT networks Supervision of Bachelor's student Chen Xie (2020–2024) on synthesis of smart sensors He teaches courses such as High-Level Synthesis (PhD), Synthesis and Optimization of Digital Systems, Machine Learning for IoT, and Efficient Computing for Artificial Intelligence across Computer Engineering and Data Science programs. His research group is EDA - Electronic Design Automation (DAUIN), which focuses on hardware-software co-design for intelligent systems.

• Digital Forensics
• Cybersecurity
• IoT Authentication
• +9 more

Dr. Abdulghani A. Ahmed is a Senior Lecturer in Digital Forensics and Course Leader for MSc Cybersecurity at the School of Computer Science and Informatics, De Montfort University (DMU), UK. He is affiliated with the Cyber Technology Institute (CTI) and has a long-standing academic career since 2004, previously serving as a Senior Lecturer at University Malaysia Pahang. University: De Montfort University School: School of Computer Science and Informatics Role: Senior Lecturer, Course Leader (MSc Cybersecurity) Email: aa.ahmed@dmu.ac.uk ORCID: 0000-0001-9748-6067 Education: PhD in Network Security & Intrusion Detection Systems, Universiti Sains Malaysia (2014) MSc in Network Forensics & Identity Spoofing Investigation, Al-Neelain University (2006) BSc (Hons) in Computer Science, Sudan University of Science and Technology (2002) Dr. Ahmed’s research focuses on critical areas in cybersecurity, including digital forensics, IoT authentication, big data privacy, cloud and network security, malware analysis, incident response, and cybercrime investigation. His work integrates machine learning, bio-inspired algorithms, and proactive forensic models to enhance cyber resilience. He has led numerous research projects and published extensively in top-tier journals such as IEEE Access, Sensors, and Springer. The recent publications reflect a strong trend toward digital forensics in cloud and mobile environments, bio-inspired security frameworks, and machine learning applications in cybercrime detection. His work bridges theoretical innovation and practical deployment, particularly in real-time intrusion detection and evidence collection. Scientific Awards and Honors: Multiple Gold, Silver, and Bronze medals from international innovation exhibitions (MTE2018, Citrex, iCAN, ICE-CINNO) CENDEKIA BITARA AWARD 2016 for high-impact journal publication Nominated for Best PhD Thesis Award at USM (2015) Three-time High Impact Publication Award (2011–2013) at USM Dr. Ahmed actively supervises PhD students and has secured significant research funding as Principal Investigator from Innovate UK, COMSTECH-TWAS, and Malaysian government grants. His consultancy work includes cybercrime investigation and incident response for SysArmy Sdn Bhd and Golden Carousel Sdn. Bhd. He is a Senior Member of IEEE and IAENG, and holds professional certifications including SFHEA (UK), Cellebrite CCO, and digital forensics credentials from AccessData and Condition Zebra. He leads the Cyber Technology Institute research group at DMU, focusing on next-generation cybersecurity solutions. His projects include proactive forensic models, IoT security frameworks, and AI-driven botnet detection systems, positioning him at the forefront of applied cybersecurity research.

• Optimizing Compilers
• Runtime Systems
• Embedded Systems
• +5 more

Summary Role & Affiliation: Mahmut Taylan Kandemir is a Professor in the Department of Computer Science and Engineering at Pennsylvania State University. He is a member of the Microsystems Design Lab and has held roles such as Graduate Program Coordinator. His research focuses on optimizing compilers, runtime systems, embedded systems, and storage technologies. Education: B.S. and M.S. from Istanbul Technical University (Computer Engineering), Ph.D. from Syracuse University (Computer Science). Research Interests: Kandemir’s work spans compiler optimization, energy-efficient architectures, non-volatile memory systems, and cloud storage. His research has been funded by NSF, DARPA, and industry partners like Intel and Microsoft. Articles & Contributions: Over 150 journal papers and 650+ conference publications, covering topics like compiler-driven storage efficiency, 3D NAND SSD optimization, and approximate computing frameworks. Awards: NSF Career Award, Penn State Premier Research Award, IEEE Fellow, and multiple best paper awards. His contributions include compiler tools and storage systems for high-performance computing. Advising & Grants: Advised 32 Ph.D. and 20 M.S. students. Active in program committees for conferences like MICRO, ISCA, and HPCA. Current grants focus on cloud resource management and emerging memory technologies. Labs & Collaborations: Leads projects in collaboration with Argonne National Lab, NVIDIA, and Intel. His work bridges academia and industry, addressing challenges in multicore and embedded systems.

Phillip RaffeckView profile

Researcher

• Real-Time Systems
• Embedded Systems
• Energy-Aware Computing
• +7 more

Phillip Raffeck is a researcher at the Department of Computer Science (INF) within the Chair of Computer Science 4 (System Software) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His work focuses on real-time systems, embedded systems, and energy-aware computing, with a particular emphasis on worst-case execution time (WCET) and energy consumption (WCEC) analysis. He has contributed to projects like the Invasive Run-Time Support System (iRTSS) and tools for energy-neutral system design. Department: Department of Computer Science (INF) University: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Position: Researcher His research spans real-time systems , multi-core optimization , and power-aware computing . Key contributions include migrative synchronization protocols , energy-neutral operating systems , and code metrics for timing analysis . Recent work explores carbon-aware co-design and predictable migration in embedded environments. Publications highlight collaborations with teams across Germany and international symposia like RTSS, WCET, and EMSOFT. His article trends reflect advancements in intermittent execution models , transactional networking , and static analysis toolchains . He serves as a secondary reviewer for conferences including RTAS and ISORC. Phillip supervises graduate theses on topics such as DMA-based OS offloading , dynamic migration , and interrupt latency analysis . He contributes to teaching courses like Betriebsystemtechnik and Systemnahe Programmierung in C at FAU.

Mian M. HamayunView profile

Associate Professor

• Computer Science
• Transaction Level Modeling (TLM)
• MPSoC Simulation
• +15 more

Mian M. Hamayun is an Associate Professor of Computer Science and Head of Subject Group at the University of Birmingham Dubai campus, part of the College of Engineering and Physical Sciences. He holds a PhD in System Modelling, Simulation & Virtualization from the University of Grenoble Alpes, France, and has academic qualifications from Joseph Fourier University and COMSATS Institute of Information Technology, Pakistan. PhD in System Modelling, Simulation & Virtualization, University of Grenoble Alpes, 2013 MS in Informatics (Parallel & Distributed Systems), Joseph Fourier University, 2009 MSE in Software Engineering (Gold Medalist), COMSATS, 2005 PGCHE, University of Birmingham, 2021 FHEA and SFHEA, University of Birmingham (2021, 2024) His research spans Transaction Level Modeling (TLM) , MPSoC simulation , cloud computing , virtualization , Internet of Things/Vehicles , edge AI , and TinyML . He focuses on performance estimation, binary translation, and system-level simulation for embedded and distributed systems. The recent publications reflect a strong trend in IoT and vehicular networks , secure telemedicine , cloud orchestration , and embedded system simulation . His work integrates virtualization with security, real-time constraints, and machine learning on edge devices. Senior Fellow of the Higher Education Academy (SFHEA), 2024 Fellow of the Higher Education Academy (FHEA), 2021 Dr. Hamayun has supervised multiple research students and contributed to projects involving fatigue detection, person re-identification, retinal image analysis, and secure surgery frameworks. He has taught core computer science courses including Operating Systems, Networks, Data Structures, Algorithms, and Functional Programming at both undergraduate and postgraduate levels. His prior roles include Assistant Professor at NUST SEECS, R&D Engineer in France, and Lecturer at IUT1. He leads research in virtual prototyping and edge intelligence at the Dubai campus, contributing to smart city and cognitive systems initiatives. His lab work involves hybrid simulation environments, secure automotive platforms, and distributed IoT systems.

Raghav SampangiView profile

Senior Lecturer

• Usable Security and Privacy
• Computer Science Education
• Context-Aware Authentication
• +9 more

Raghav Sampangi is a Senior Instructor in the Faculty of Computer Science at Dalhousie University, where he teaches courses in web development, server-side scripting, and usable security and privacy. He is also a Faculty Associate at the Centre for Learning and Teaching and actively contributes to pedagogical innovation and inclusive academic practices. Education: PhD, Dalhousie University, Canada (2015) M.Tech, University of Mysore, India (2011) B.Engg, VTU, Belgaum, India (2007) Raghav's research focuses on usable security and privacy , context-aware authentication , and innovations in computer science education , particularly compassionate teaching, ungrading, and student support. He is deeply committed to equity, diversity, and inclusion in computing and advocates for mental health and belonging in academia. His recent publications center on security in resource-constrained systems, including IoT, RFID, and wireless body area networks, often using bio-inspired cryptographic techniques. The work demonstrates a strong trend toward lightweight, adaptive, and context-sensitive security solutions. Scientific Awards: The Srini Award for Teaching Excellence (2021, 2018) Best Paper Award at Q2SWinet 2014 Best Paper in General Conference Program at SoftCOM 2014 Dalhousie Impact Leadership Award (2014) Faculty Appreciation Award (2015) Parvathamma Subbaraya Gold Medal (University of Mysore) Raghav advises students through community outreach courses and research projects. He leads multiple educational initiatives, including ungrading research and first-year student support. He is co-lead of the D-LITE Belong Cluster and the Halifax Chapter of Canada Learning Code, and is a Cultural Competence in Computing (3C) Fellow at Duke University. His service includes advocacy with Dragonfly Mental Health and the READI Group, promoting compassionate and inclusive academia. He is actively involved in lab and team-based research on usable security and CS education, collaborating with industry, alumni, and students to revise curricula and develop inclusive learning environments.

• Cybersecurity
• Internet of Things (IoT)
• Artificial Intelligence (AI)
• +12 more

Jawad Ahmad is a Lecturer in the School of Computing, Engineering and the Built Environment at Edinburgh Napier University . His work is closely associated with the Centre for Cybersecurity, IoT and Cyberphysical Systems and the Centre for Distributed Computing, Networking and Security , where he contributes to cutting-edge research in secure and intelligent systems. His research interests are centered on cybersecurity , artificial intelligence , and Internet of Things (IoT) technologies. He focuses on developing advanced intrusion detection systems, privacy-preserving frameworks using federated learning and homomorphic encryption, and secure data transmission mechanisms leveraging chaos-based and quantum-inspired encryption. His interdisciplinary work extends to healthcare, smart agriculture, and environmental monitoring, demonstrating the broad applicability of his research. The analysis of his recent publications reveals a strong trend toward AI-driven security solutions, particularly using deep learning models like transformers and attention mechanisms for network intrusion detection. He also explores the integration of machine learning with blockchain and distributed ledgers for trusted threat intelligence sharing. His work consistently emphasizes real-world deployment, performance optimization, and resilience against cyber threats in industrial and healthcare settings. Funded Research Projects: Data Sharing in Highly Secure Environments (Innovate UK, £273,181) PhD Studentship on Homomorphic Encryption (6G Health Institute GmbH, £35,082) TrustShare: Privacy-Preserving Threat Intelligence Sharing (Innovate UK, £31,386) Cyber Hunt: Automated Cyberthreat Hunting (Norway Research Council, £37,500) AI Dashboard for COVID-19 Sentiment Analysis (Chief Scientists Office, £135,104) Dr Ahmad actively supervises postgraduate research, currently serving as Director of Studies for Hisham Ali and as second supervisor for other PhD candidates. He is involved in multiple collaborative research teams focusing on cybersecurity, AI, and IoT, often working with Prof Bill Buchanan and other leading researchers in the field. His research is published in high-impact journals such as IEEE Access , Frontiers in Computational Neuroscience , and Sensors , and presented at international conferences.

Somali ChaterjiView profile

Associate Professor

• Data Science
• Digital Agriculture
• Computational Biology
• +6 more

Dr. Somali Chaterji is an Associate Professor in the Department of Agricultural & Biological Engineering at Purdue University, with a courtesy appointment in the Elmore Family School of Electrical and Computer Engineering. Her research bridges data science, digital agriculture, and computational genomics, focusing on machine learning for IoT, edge computing, and scalable genomics analysis. She leads the Innovatory for Cells and Neural Machines (ICAN), developing algorithms for efficient data analytics in resource-constrained environments. Education: PhD in Biomedical Engineering (Purdue University), Postdoctoral Fellowship at University of Texas at Austin. Awards include the NSF CAREER Award (2022), ACM BCB Best Paper (2015), and Purdue Seed-for-Success Award (2016). She founded KeyByte LLC, a cloud computing startup optimizing ML workloads. Research spans IoT edge analytics (e.g., drone surveillance, embedded systems) and genomics (single-cell clustering, error correction in sequencing). She is Co-PI of the NSF CHORUS Center and A2I2 Army Institute. Over 20 students are advised, with active projects on serverless computing, federated learning, and genome engineering. Labs/Teams: ICAN Lab, WHIN project (Lilly Endowment), Purdue ABE Extension. Collaborations with Microsoft, Amazon, and Adobe Research. Active in teaching, including courses on applied ML and computational genomics with innovative pedagogy.

Shixun HuangView profile

Lecturer

• Data Mining
• Machine Learning
• Algorithm Design
• +3 more

Dr. Shixun Huang is a Lecturer in the School of Computing and Information Technology at the University of Wollongong, Australia. He holds a PhD from RMIT University and specializes in data mining, machine learning, and optimization algorithms for high-dimensional data problems. His research develops efficient algorithms for data discovery, similarity search, and network analysis. Current projects focus on optimized data acquisition strategies for machine learning, cost-effective labeling for graph neural networks, and cardinality estimation in high-dimensional databases. Methodologically, he combines combinatorial optimization with machine learning techniques. Dr. Huang supervises graduate research on diffusion models for medical imaging, graph prompt learning, and image captioning systems. His honors include multiple best paper awards at top database conferences and recognition for teaching excellence (College Top Course Award at RMIT). Recent publications address dataset distinctiveness maximization (WWW 2025), high-dimensional similarity search (VLDB 2025), and edge computing optimization (2024). Earlier foundational work established new approaches for influence maximization in social networks and temporal graph representation learning.

CHANG Ee ChienView profile

Associate Professor

• Information Security
• Cloud Security
• Adversarial Machine Learning
• +6 more

CHANG Ee-Chien is an Associate Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). He serves as the Lead Principal Investigator of the National Cybersecurity R&D Laboratory (NCL) and previously served as Deputy Director of the Center for Technology, Robotics, Artificial Intelligence and the Law (TRAIL) from 2019 to 2022. He also chaired the Joint Academic Committee for the Bachelor of Computing in Information Security program from 2016 until April 2023. Dr. Chang received his Ph.D. in Computer Science from New York University in 1998, following his M.Sc. and B.Sc. in Mathematics from the National University of Singapore in 1993 and 1991 respectively. He completed postdoctoral work with DIMACS at Rutgers University and NEC Labs America. His research focuses on information security, multimedia security, and their intersection. His work spans from foundational research in cryptographic techniques for noisy data and image watermarking to contemporary challenges in data privacy, cloud security, and adversarial machine learning. Dr. Chang has published extensively in top-tier security and computer science venues including CCS, EUROCRYPT, USENIX Security, and ACM Multimedia. Analysis of his recent publications reveals a strong emphasis on practical security solutions using hardware features like Trusted Execution Environments, innovative approaches to watermarking using generative models, and addressing emerging threats in machine learning systems. His work bridges theoretical cryptography with real-world security challenges, particularly in cloud infrastructure and privacy-preserving technologies. Active leadership in National Cybersecurity R&D Laboratory Extensive service on program committees for major security conferences Consultancy roles with Huawei, i-Sprint, and Singapore Accreditation Council Media commentary on cybersecurity issues for major Singaporean outlets Dr. Chang has mentored numerous research fellows and students who have gone on to academic and industry positions worldwide. His educational contributions include developing cybersecurity curriculum and innovative teaching methods such as penetration testing using real-world university applications. He has taught core security courses including CS2107 Introduction to Information Security continuously since 2014.

Jeffrey K. HollingsworthView profile

Professor

• High Performance Computing (HPC)
• Parallel Programming
• Operating Systems
• +5 more

Jeffrey K. Hollingsworth is a Professor in the Computer Science Department at the University of Maryland and serves as Vice President for Information Technology and Chief Information Officer (CIO) for the university. He holds appointments in CS, UMIACS (University of Maryland Institute for Advanced Computer Studies), and ECE (Electrical and Computer Engineering). His research focuses on High Performance Computing (HPC), parallel programming environments, and system architecture. He received a Ph.D. from the University of Wisconsin at Madison (1994) and a B.S. in Electrical Engineering from UC Berkeley. Hollingsworth leads the university’s IT infrastructure, overseeing critical services like networking, cybersecurity, and support for research and teaching. He has held leadership roles in professional organizations, including past chair of the ACM Special Interest Group on HPC (SIGARCH) and board positions with Internet2 and the Computing Research Association. His awards include IBM Faculty Partnership Awards (2016, 2001), an NSF CAREER Award (1997), and IEEE Senior Member status (2003). Key contributions include advancing HPC education through programs like the SC Student Cluster Competition and developing tools for performance analysis (e.g., PIPER, Chapel profilers). He has authored over 150 papers and has been cited for innovations in auto-tuning, parallel algorithms, and system optimization.

• Cybersecurity
• Computer Security
• Hardware Security
• +6 more

Herbert Bos is a Full Professor at Vrije Universiteit Amsterdam, holding positions in the Faculty of Science (Computer Systems department), the Network Institute, and the Systems and Network Security group. His research focuses on hardware and software security, including transient execution attacks, memory exploitation, and vulnerability detection. He has authored over 229 research outputs, including influential papers on Spectre mitigation, Rowhammer attacks, and fuzzing techniques. Notable contributions include frameworks like PANDAcap and BinRec. Bos teaches courses such as Binary and Malware Analysis and Operating Systems. His work aligns with UN Sustainable Development Goals related to innovation and infrastructure security. Education details are not explicitly provided, but his academic titles (prof. dr. ir.) suggest advanced degrees in computer science and engineering. Ancillary activities include roles as an author for Pearson textbooks and a member of the Kiesraad in The Hague. Research interests emphasize cutting-edge hardware vulnerabilities (e.g., Spectre, Rowhammer), memory safety, and automated testing (fuzzing). Recent work highlights practical defenses against transient data leaks (Phantom Trails) and data-only attacks. Collaborations span international institutions, reflecting his global influence in cybersecurity. Publications since 2016 showcase advancements in CPU architecture security, kernel exploitation, and embedded device defenses. His datasets (e.g., PANDAcap SSH Honeypot) provide foundational resources for the security community. Grants and lab affiliations are inferred through his research outputs and teaching roles.

Sherief RedaView profile

Professor

• Machine Learning
• Computer Architecture
• Energy Efficiency
• +5 more

Sherief Reda is a Professor of Engineering and Computer Science at Brown University's School of Engineering. He leads the SCALE lab, focusing on energy-efficient computing, digital chip design, embedded systems, and machine learning applications. His research bridges hardware design and combinatorial optimization, with over 130 publications and five US patents. Reda has secured $21M+ in research funding from NSF, DoD, DARPA, and industry partners like Samsung and Intel. Education: PhD in Computer Science & Engineering, UC San Diego (2006) MS in Computer Science, Ain Shams University (2000) BS in Computer Science, Ain Shams University (1998) Research Interests: His work spans resource-efficient AI, approximate computing, and interdisciplinary applications in social sciences. Recent projects include chemical-based computing and thermal management for high-performance chips. Reda's lab explores machine learning for combinatorial optimization, with practical applications in logistics and hardware design. Publications & Awards: Over 130 articles in top venues like IEEE Transactions and Nature Communications. Recipient of the NSF CAREER Award (2021) and IEEE Fellow (2020). His work on energy-efficient computing earned him the AAIA Fellowship. Grants & Collaborations: Principal Investigator on NSF, DoD, and industry-funded projects. Collaborators include Prof. Kim (Chemistry) and Prof. Rose (Engineering). Reda also serves as an Amazon Scholar and expert witness in patent litigation. Labs & Teams: Directs the SCALE lab, which develops open-source EDA tools and novel thermal simulation frameworks like PACT. His team pioneered techniques like ABACUS for approximate circuit synthesis and LoCool for energy efficiency in servers.