Find Academic Supervisors

• Applied Cryptography
• Secure Distributed Algorithms
• Blockchain Technology
• +3 more

Ling Ren is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois at Urbana-Champaign. He earned his Ph.D. in Computer Science from MIT in 2018 and held a postdoctoral position at VMware Research Group before joining UIUC. His research bridges theoretical and practical aspects of applied cryptography and secure distributed algorithms. University: University of Illinois at Urbana-Champaign School: Siebel School of Computing and Data Science Department: Department of Computer Science Academic Rank: Assistant Professor Research Interests: Ling Ren focuses on designing algorithms that combine practical efficiency with provable security. His work spans threshold/distributed cryptography, fault-tolerant consensus (blockchain), and privacy-preserving protocols like Private Information Retrieval (PIR). Recent projects include Granular Synchrony for unified network timing models and Practical Asynchronous Distributed Key Generation for blockchain infrastructure. Selected Publications (2025-2023): Recent works cover verifiable secret sharing, BLS threshold signatures, batch PIR protocols, and asynchronous consensus algorithms. These publications address foundational challenges in cryptographic security and distributed systems, with applications to blockchain scalability and privacy. 2025: Verifiable Secret Sharing Simplified, Single-Server Client Preprocessing PIR 2024: S3PIR Protocol, Adaptively Secure BLS Threshold Signatures 2023: Threshold Signatures from Inner Product Argument Scientific Awards: NSF CAREER (2022) Google Research Scholar Award (2023) Chaincode Lab Bitcoin Research Prize (2023) Best Paper Runner-up at CCS (2021) Top Picks in Hardware and Embedded Security (2018) Teaching & Advising: Ling Ren teaches graduate courses such as CS 539 (Distributed Algorithms) and CS 461 (Computer Security I). He advises current students like Sourav Das and Ananya Appan, while past advisees include Zhuolun Xiang (PhD 2022) and Muhammad Haris Mughees (PhD 2024).

Arne SchmitzView profile

Researcher

• Radio Wave Propagation
• Computer Graphics
• Wireless Network Simulation
• +3 more

Dr. Arne Schmitz is a researcher at the Department of Computer Science, RWTH Aachen University, specializing in computational methods for wireless communications and computer graphics. His work bridges radio wave propagation physics with advanced visualization techniques, focusing on practical applications for mobile network planning and mobile device interfaces. His primary research domains include: Radio wave propagation modeling in urban environments GPU-accelerated beam/ray tracing algorithms Antenna pattern compression using spherical harmonics Real-time 3D visualization for resource-constrained mobile devices Ad-hoc multi-display systems for collaborative mobile applications Analysis of his publication timeline reveals an evolution from foundational radio propagation models (2006) toward increasingly sophisticated urban simulation frameworks (2011-2012), with consistent emphasis on computational efficiency. His most impactful contributions integrate computer graphics rendering techniques with telecommunications engineering, particularly in adapting beam tracing for radio wave simulation and developing novel mobile visualization paradigms that overcome hardware limitations through client-server architectures. Dr. Schmitz maintains a strong collaborative relationship with Professor Leif Kobbelt and colleagues at RWTH Aachen, with co-authorship appearing in 9 of his 10 documented publications. His research demonstrates consistent funding support through participation in IEEE and ACM conferences, though specific grant details are not disclosed in the available materials.

Juho VepsäläinenView profile

Lecturer

• Web Development
• JavaScript
• Static Site Generation
• +7 more

Juho Vepsäläinen is a Lecturer in the Department of Computer Science at Aalto University, specializing in web development, JavaScript, and hybrid rendering models. His research bridges traditional content management systems (CMS) with modern static site generation (SSG) techniques while exploring serverless edge computing and developer experience. Education: Master of Science in Information Technology, University of Jyväskylä (2005-2011) Doctoral Thesis on hybrid rendering models in web application development (2025) Research Focus: Vepsäläinen’s work centers on optimizing web application performance through edge computing, serverless architectures, and disappearing frameworks. He investigates how to retain the benefits of CMS and SSG while reducing complexity and enhancing resumability in development workflows. Publication Trends: Recent articles emphasize serverless edge-powered solutions, hybrid rendering models, and the evolution of disappearing frameworks. Keywords span Web Development , Edge Computing , and Performance Optimization , with subfields including distributed networks, content delivery systems, and framework-less architectures. Collaborations: Collaborated with Antti Hellas and Petri Vuorimaa on edge computing and web performance, contributing to conferences like WEBIST and journals such as IEEE Access .

• Computer Science
• Network Security
• Malware Detection
• +4 more

Engin Kirda is a researcher at the Department of Distributed Systems , Vienna University of Technology . His work focuses on Network Security , Malware Detection , and Web Security , with a particular emphasis on Malware Analysis , XSS Prevention , and Botnet Detection . He has led and contributed to projects such as WOMBAT , SECoverer , and SysSec , funded by entities like the Austrian Research Promotion Agency (FFG) and the European Commission . Research Areas : Network Security, Malware Analysis, Web Application Vulnerabilities Key Projects : WOMBAT (2008–2011), SECoverer (2008–2011), SysSec (2010–2014) His publications highlight advancements in automated malware analysis , phishing detection , and web spam mitigation . He has mentored students in topics including Android security , CSV Attack Prevention , and Malware Threat Landscapes .

Haris VolosView profile

Assistant Professor

• Computer Architecture
• Operating Systems
• Data Storage and Processing
• +4 more

Haris Volos is an Assistant Professor in the Department of Informatics at the University of Cyprus . He holds a Ph.D. in Computer Science from the University of Wisconsin-Madison (2012), following B.E.E. degrees from the National Technical University of Athens (2005). Before academia, he worked at Hewlett Packard Labs (2013–2018) and Google (2018–2019). His research focuses on Computer Architecture , Operating Systems , and Data Storage and Processing , with recent work on energy-efficient CPU architectures, disaggregated memory systems, and persistent memory frameworks. Education: B.E.E. (2005), National Technical University of Athens M.Sc. (2007), University of Wisconsin-Madison Ph.D. (2012), University of Wisconsin-Madison Key Research Themes: Energy-efficient CPU core idle-state architectures Disaggregated memory protection and replication Persistent memory systems and transactional memory Big data processing over hybrid memory tiers Recent Contributions: His work includes frameworks like Panthera for holistic memory management and AgileWatts for energy-proportional servers. He also pioneered systems like HOPS (Hands-off Persistence System) for persistent memory. Labs/Teams: Active in the university's informatics research clusters, focusing on hardware-software co-design and scalable data systems.

Daniel O'KeeffeView profile

Senior Lecturer

• distributed systems
• security
• databases
• +7 more

Daniel O'Keeffe is a Senior Lecturer in Computer Science at the Department of Computer Science, Royal Holloway University of London (RHUL). He is affiliated with the Centre for Programming Languages and Systems (CPLS) and the Systems and Software Security Lab (S3Lab). PhD from University of Cambridge Computer Laboratory Post-doctoral research at Imperial College London Industry experience in financial software engineering His research spans distributed systems, security, databases, and networking, with a focus on cloud computing security and blockchain security. Recent work explores performance-security trade-offs in proof-of-stake blockchains under the Revoke project. Key research projects include SecureCloud (cloud security for critical infrastructure), ITA-DSM (edge computing stream processing), SeReCa (secure hardware for cloud protection), and CloudSafetyNet (data leakage monitoring). Current projects receive funding from the Engineering and Physical Sciences Research Council (EPSRC) and the Ethereum Foundation. Scientific Awards : ERA Track - Best Paper Award at SANER 2024 Grants : REDONDA: EPSRC-funded project on Byzantine State-Machine Replication for blockchain (2024-2027) Consensus-layer mitigations for validator ransomware attacks: Ethereum Foundation grant (2022-2023) Labs & Groups : Centre for Programming Languages and Systems (CPLS) Systems and Software Security Lab (S3Lab) OPERA group (University of Cambridge) LSDS group (Imperial College London)

Mariano CeccatoView profile

Associate Professor

• Security Testing
• Penetration Testing
• Code Hardening
• +5 more

Mariano Ceccato is an Associate Professor in the Department of Computer Science at the University of Verona, Italy. With a PhD in Computer Science from the University of Trento (2006), he has led numerous publicly funded and industrial research projects. His expertise includes security testing, penetration testing, code hardening, and empirical studies. Principal Investigator in multiple research initiatives Visiting Research Scientist at the University of Luxembourg Author/co-author of over 100 peer-reviewed papers Research Focus His work spans Android security, Ethereum smart contracts, REST APIs, and software protection techniques. Key contributions include: Security testing frameworks using reinforcement learning Advanced static analysis for Ethereum bytecode Novel obfuscation strategies for Java/Android Empirical studies on security report usability Comparative analysis of malware detection techniques Scientific Contributions He has received multiple awards including the Best Paper at IEEE ICST 2022, Best Research Paper at IEEE/ACM ICSE 2023, and ACM Distinguished Paper awards.

Tomka Yuriy YaroslavovychView profile

Associate Professor

• Software architectures
• enterprise application development
• .NET platform
• +3 more

Yuriy Yaroslavovych Tomka is an Associate Professor in the Department of Computer Science at Yuriy Fedkovych Chernivtsi National University. He holds a Candidate of Physical and Mathematical Sciences degree and has been serving as an Associate Professor since April 15, 2021. His academic work spans software engineering, neural networks, and biomedical image processing, with numerous publications in these fields. Dr. Tomka's educational background includes: Bachelor's degree in Laser and Optoelectronic Engineering from Yuriy Fedkovych Chernivtsi National University (2005), with honors Candidate of Physical and Mathematical Sciences degree (2009) in specialty 01.04.05 – Optics, Laser Physics Dr. Tomka's research interests focus on software architectures, enterprise application development on the .NET platform, pattern recognition, digital image processing, and neural networks. His work bridges theoretical computer science with practical applications in biomedical diagnostics, financial technology, and e-commerce systems. He has made significant contributions to the development of information systems, machine learning applications, and educational methodologies in computer science. Analysis of Dr. Tomka's recent publications reveals a strong focus on practical applications of software engineering principles, particularly in the .NET ecosystem. His work spans from fundamental software architecture to specialized applications in biomedical imaging and financial forecasting. There's a clear trend toward interdisciplinary research, combining computer science with fields like medicine and finance, demonstrating the versatility and applicability of his technical expertise. Dr. Tomka has received recognition for his mentorship, guiding student research that won second-degree diplomas in national competitions. His professional development includes numerous certifications in modern software technologies from institutions like Sigma Software University. As an active member of the Bukovina Information Technology Cluster named after Joseph Schumpeter since 2019, Dr. Tomka contributes to regional IT development initiatives. He also provides scientific consulting to the Limited Liability Company "Buknanotech" and has managed research projects including "Development of new methods and biomedical systems for polarization-holographic fractalmetry of crystallites of tissues and fluids of human organs" (2019-2021).

• Actuarial Science
• Mathematical Finance
• Longevity Risk
• +7 more

Dr. Petar Jevtic is a Tenured Associate Professor at the School of Mathematical and Statistical Sciences of Arizona State University (ASU), with affiliations at the Center for Biodiversity Outcomes and Watts College of Public Service and Community Solutions . He also holds an Adjunct Assistant Professor position at McMaster University's Department of Mathematics and Statistics. Ph.D. in Economics (Statistics and Applied Mathematics), University of Turin, Italy (2013) M.Sc. in Economics, University of Belgrade, Serbia (joint with HEC Paris) Dipl. Ing. in Computer Science and Engineering, University of Belgrade, Serbia His research focuses on actuarial science and mathematical finance with emphasis on longevity risk , cyber risk , climate risk , and smart contract vulnerabilities . He employs advanced stochastic modeling techniques including Lévy processes , marked point processes , and random graph theory to address contemporary risk challenges. Recent publications demonstrate expertise in cyber risk modeling for emerging technologies, spatial mortality analysis , and pandemic risk frameworks . Key methodologies include percolation theory , stochastic Petri nets , and geographically weighted regression . He has secured research funding from prestigious institutions including the Society of Actuaries , Casualty Actuarial Society , and federal agencies NSF , NIH , and DHS . His work combines theoretical mathematics with practical risk management applications , particularly in insurance and technology sectors. Dr. Jevtic actively supervises Ph.D. candidates and occasionally mentors MSc and undergraduate researchers . His affiliations span ASU's interdisciplinary risk research centers and McMaster University's mathematical finance initiatives.

Thomas DaggettView profile

Adjunct Professor

• Computer Architecture
• Distributed Systems
• Web Technologies
• +4 more

Thomas Daggett is an Adjunct Professor of Computer Science at Connecticut College, holding this position since 2016. His educational background includes: B.S. in Engineering from the University of Connecticut M.S. from Rensselaer Polytechnic Institute Ph.D. from the University of Connecticut Professor Daggett specializes in computer architecture, distributed processing, web and collaboration technologies, and software engineering. His expertise extends to client/server computing, parallel algorithm development, and enterprise-scale software solutions. With over 18 years of industry experience, his work bridges theoretical computer science with large-scale pharmaceutical and defense applications. Professor Daggett's professional career spans leadership roles at major corporations and government institutions. He currently serves as director of Pfizer Inc's Advancing Content & Transactions (ACT) Group. Previously, he directed Pfizer's Content and Collaborations Team, acting as service delivery lead and platform architect for the Document Management Facility (DMF) Platform while serving as SharePoint and Enterprise Search architect. His industry experience includes positions at General Dynamics' Advanced Technologies Group (Electric Boat Division), Sapient in Cambridge, Massachusetts, Computer Sciences Corporation, and the Naval Undersea Warfare Center in Newport, Rhode Island.

Kai WarendorfView profile

Professor

• Intelligent Tutoring Systems
• Hypermedia Systems
• Fuzzy Logic
• +5 more

Kai Warendorf serves as a Professor at Esslingen University of Applied Sciences within the School of Engineering, Department of Computer Science and Engineering. He holds multiple administrative roles including Director of Internship Offices for four distinct Bachelor programs: Business Information Systems, Computer Engineering, Engineering Education Information Technology - Electrical Engineering, and Software Engineering and Media Computing. His research spans intelligent tutoring systems, hypermedia navigation, and educational technology. Key interests include constraint-based student modeling, fuzzy logic applications in education, algorithm animation techniques, and spatial hypermedia interfaces. His work bridges theoretical computer science with practical educational implementations, particularly through Java-based web technologies and multimedia systems. Publications reveal consistent focus on enhancing STEM education through visualization tools, with notable contributions in atomic reaction modeling (ARMVLS), data structure tutoring (ADIS), and spatial navigation (HyperMap). His research integrates cognitive principles with software engineering to create adaptive learning environments that address common student misconceptions. Professor Warendorf maintains active collaboration with international researchers, particularly in Singapore and Germany, focusing on practical implementations of educational technology in engineering curricula. His administrative leadership in internship coordination demonstrates commitment to industry-academia integration for undergraduate students.

Trifon Anchev TrifonovView profile

Associate Professor

• Computer Science
• Mathematical Logic
• Artificial Intelligence
• +3 more

Trifon Anchev Trifonov is an Associate Professor in the Department of Computer Informatics at the Faculty of Mathematics and Informatics, Sofia University 'St. Kliment Ohridski'. His academic work focuses on mathematical logic, computational mathematics, and generalized net modeling. Current affiliation: Sofia University Research areas: Proof theory, fuzzy logic, neural networks Email: triffon@fmi.uni-sofia.bg Trifonov's research explores the intersection of mathematical logic and computational systems through Dialectica interpretations and generalized net frameworks. He contributes to formal verification, intuitionistic fuzzy logic, and adaptive neural architectures. His publications demonstrate expertise in algorithmic analysis, proof mining, and computational modeling. Key collaborations include work with K. Atanassov, K. Georgiev, and G. Mengov in generalized net systems and neural signal processing. Trifonov's work spans multiple subfields including: Proof theory and constructive mathematics Intuitionistic fuzzy logic Adaptive resonance neural networks Generalized net modeling Computational complexity Formal verification techniques

Louiqa RaschidView profile

Professor

• Database Systems
• Data Integration
• Data Mining
• +8 more

Louiqa Raschid is a Professor at the University of Maryland, holding appointments in the Robert H. Smith School of Business, the Institute for Advanced Computer Studies (UMIACS), and the Department of Computer Science. Her research bridges computer science and business information systems, focusing on data integration, management, and mining in non-traditional domains. Education: B.Tech (IIT Madras, 1980), PhD (University of Florida, 1987) Research Interests include: Data integration and mining across life sciences, health sciences, and financial ecosystems Humanitarian IT solutions for disaster management Semantic query optimization and data delivery techniques Grid and wide-area data management Article Trends reflect interdisciplinary efforts combining bioinformatics, database systems, and social behavior modeling. Key themes include ontology-driven data analysis, network-aware query optimization, and disaster relief systems development. Scientific Awards include: ACM Distinguished Member (2016) ACM Fellow (2016) IEEE Fellow (2000) DILS 2008 Best Paper Award Grants from NSF and DARPA have funded her work on biological data integration and financial cyberinfrastructure. She co-directs the Computational Linguistics and Information Processing (CLIP) Lab and collaborates with institutions worldwide.

• Machine Learning
• Artificial Intelligence
• Federated Learning
• +3 more

Dr. Jing Jiang is an Associate Professor in the School of Computer Science and a core member of the Australian Artificial Intelligence Institute (AAII) at the University of Technology Sydney (UTS). As an ARC DECRA Fellow, she has secured over AU$2 million in research funding through multiple ARC grants, CSIRO/Data61 projects, and industry collaborations. Her work bridges theoretical advances in machine learning with practical applications across various domains. Dr. Jiang's research focuses on machine learning, particularly federated learning, reinforcement learning, and foundation models. She explores how to make these technologies work effectively in heterogeneous environments, addressing challenges like data privacy, non-IID data distributions, and efficient communication. Her work spans both theoretical foundations and practical implementations for real-world applications. Her publications demonstrate a strong trend toward personalized federated learning approaches, with significant contributions to recommender systems, time series analysis, and weather forecasting. She has developed novel techniques like variational autoencoder approaches for federated collaborative filtering and adaptive prompt learning for foundation models on devices. Dr. Jiang has received several notable recognitions: ARC DECRA Fellow Awardee of the Australian International Postgraduate Research Scholarship (IPRS) Dr. Jiang has successfully led multiple major research projects, including two ARC Discovery Projects, one ARC Linkage Project, and a CSIRO/Data61 CRP project where she served as lead Chief Investigator. She has supervised numerous PhD and Master's students and actively collaborates with industry partners on applied research. As a core member of the Australian Artificial Intelligence Institute (AAII) at UTS, Dr. Jiang contributes to a vibrant research ecosystem focused on cutting-edge AI research. She collaborates closely with Professor Guodong Long and other researchers on various machine learning projects, and serves in leadership roles including program co-chair for major conferences like ADMA2023.

Drew DavidsonView profile

Associate Professor

• Security
• Privacy
• Mobile Security
• +6 more

Drew Davidson serves as Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Kansas, where he joined the faculty in August 2018 as Assistant Professor. His research program centers on computer security and privacy, with current projects focused on automatic security policy generation for web applications and privilege separation architectures for modern server environments. Davidson maintains active industry engagement through co-founding Tala Security, a security startup addressing DevOps security challenges. Davidson completed his PhD in December 2016 with dissertation research titled "Enhancing Mobile Security through App Splitting" under advisor Somesh Jha. His doctoral committee included Thomas Reps, Aws Albarghouthi, Mihai Christodorescu, and Xinyu Zhang. This foundational work established his expertise in mobile security mechanisms and application isolation techniques. His research spans critical security domains including mobile platform security, web application vulnerabilities, UAV sensor spoofing, and software ecosystem risks. Davidson's work bridges theoretical security models with practical system implementations, particularly in containerization, microservice architectures, and package manager ecosystems. He has made significant contributions to understanding language-based software security issues and developing deployable countermeasures against supply chain attacks. Analysis of his recent publications reveals concentrated focus on emerging threats in modern software development practices. His 2020-2024 work demonstrates deep investigation into npm package vulnerabilities (typosquatting, package confusion, install-time attacks), microservice security challenges (service mesh vulnerabilities, multi-hop network enforcement), and practical UAV defense mechanisms. This research trajectory shows consistent evolution from mobile security foundations toward contemporary cloud-native and software supply chain security challenges. Scientific recognition includes: NSF SBIR Phase I award (2017) for Tala Security's "Automated Security for the DevOps World" proposal Davidson contributes to academic training through courses including EECS 665 (Compiler Construction) and EECS 700 (Mobile Security). His research program integrates teaching with practical security solutions development, evidenced by student-involved projects in mobile security and compiler techniques. The NSF-funded Tala Security initiative represents significant industry-academia technology transfer. As co-founder of Tala Security, Davidson leads research translating academic insights into commercial security products. The startup focuses on automated security policy generation for DevOps environments, building directly on his publication record in application splitting and container security. Current work explores scan-impeding delays for web deployments and multi-hop network connection enforcement in microservice architectures.