Find Academic Supervisors

Christian ZilloberView profile

Lecturer

• Nonlinear Programming
• Structural Optimization
• Topology Optimization
• +5 more

Christian Zillober serves as a Lecturer at the Chair of Mathematics VII (Numerical Mathematics and Optimization) within the Faculty of Mathematics and Computer Science at the University of Würzburg. His academic career focuses on optimization methods with particular emphasis on solving complex engineering design problems through mathematical programming approaches. The department is housed in Building 30 (Mathematik West) at Emil-Fischer-Straße 30 in Würzburg. Dr. Zillober's research spans multiple areas of optimization including nonlinear programming, structural and topology optimization, interior point methods, and applications in data mining and machine learning. His work bridges theoretical mathematical methods with practical industrial applications, particularly in engineering design. He has developed specialized software tools like SCPIP for solving structural optimization problems, demonstrating his commitment to creating practical implementations of mathematical theories. Analysis of his publication record reveals a strong focus on sequential convex programming methods and their application to large-scale optimization problems. His research trajectory shows consistent development from theoretical foundations in the 1990s toward increasingly sophisticated implementations for industrial applications in the 2000s. His work frequently addresses the challenge of scaling optimization methods to handle real-world engineering problems with numerous variables and constraints. Dr. Zillober has maintained an active teaching schedule at the University of Würzburg, offering courses in numerical mathematics and optimization. His office is located in Room 02.009, and he can be reached at +49 931 31-85077 or via email at christian.zillober@uni-wuerzburg.de for academic inquiries and appointments.

Austen RainerView profile

Professor

• Research Software Engineering
• Software Engineering Research
• Story Thinking
• +5 more

Austen Rainer is a Professor in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. His research focuses on Research Software Engineering, Software Engineering Research, Story Thinking and Computational Thinking, and Case Study Methodology. He is actively involved in educational initiatives, including the delivery of online software development modules and promoting ethical practices in technology development. Rainer collaborates on projects such as the 'Mood Movement' initiative exploring mental health technologies and contributes to interdisciplinary discussions on the intersection of storytelling and computational models. His work emphasizes challenges in software engineering for scientific applications, cultural dynamics between software engineers and scientists, and improving research methodologies through rigorous case study reporting. Recent projects include analyzing ethical hazards in assistive robotics and evaluating the reproducibility of systematic literature reviews. Rainer also advocates for responsible innovation through initiatives like the 'Back to the Fortran Future' award and teaching workshops on agile methodologies. Rainer's contributions span over 50 publications, with a focus on software quality, education, and ethical considerations. His awards include the 2024 Agility+ Prize and the 2022 Innovation in Teaching Fund. He mentors doctoral students and participates in global research collaborations, emphasizing the importance of interdisciplinary approaches and evidence-based practices in software engineering.

Lala SenevirathnaView profile

Associate Professor

• Water Engineering
• Environmental Engineering
• Water Quality Monitoring
• +3 more

Lala Senevirathna serves as an Associate Professor in the School of Computing, Mathematics and Engineering at Charles Sturt University, Bathurst, Australia, where he applies 15+ years of field engineering, research, and teaching expertise to solve critical water and environmental challenges. His work bridges engineering principles with public health outcomes through practical applications in water resource management. His academic foundation includes: Undergraduate studies at the University of Peradeniya, Sri Lanka Postgraduate education at the Asian Institute of Technology, Thailand PhD in advanced wastewater treatment from Kyoto University, Japan Research focuses on tracer-level water pollutants, adsorption processes, disinfection technologies, and environmental health monitoring, with particular emphasis on climate resilience in water infrastructure. Current investigations examine extreme weather impacts on purification systems, fish passage engineering, and fluoride contamination pathways. His methodology integrates field data with computational modeling to develop actionable solutions for regional water security. Recent publications (2023-2025) reveal a strategic shift toward interdisciplinary climate adaptation research, combining hydrological engineering with machine learning for predictive modeling of algal blooms and rainfall impacts. Key themes include bushfire-affected water quality, sustainable rainwater harvesting, and international collaborations on Mekong River fisheries. No scientific awards were documented in available sources. As an educator, Senevirathna develops innovative engineering curricula focused on practical water resource training, though specific grant details remain unreported. His teaching philosophy emphasizes real-world problem-solving to prepare students for environmental challenges. He contributes to the Gulbali Institute's mission through the Charles Sturt Engineering team, supporting research in sustainable aquatic systems and biosecurity. Current projects address Mekong River fisheries, climate-proof viticulture, and soil salinity management in South/Southeast Asia.

Lihong ZhengView profile

Associate Professor

• Artificial Intelligence
• Computer Vision
• Data Analytics
• +6 more

**Dr. Lihong Zheng** is an Associate Professor in the School of Computing, Maths and Engineering at Charles Sturt University (CSU), specializing in Data Science and Engineering. Her research focuses on applying Artificial Intelligence, Computer Vision, and Machine Learning to solve real-world problems in agriculture, viticulture, and environmental management. She has secured over $7.4 million in industry grants since 2018, leading projects such as IoT-based agricultural solutions, cyber security for farms, and robotic systems for highway monitoring. Dr. Zheng is a recipient of prestigious awards including the Cisco Women in IT Academia Award (2019) and two Charles Sturt Research Awards. She actively contributes to IEEE committees, organizes international conferences, and serves on editorial boards. Her work emphasizes translating research into practical applications, such as the IoT Spartans Challenge 2017 (Runner-up with a global team of 250 universities) and developing the Vitidoc smartphone app for vine health assessment. Key research areas include intrusion detection in robotics, livestock data management, and precision agriculture through AI-driven systems. She collaborates with industry partners to enhance STEM awareness and mentors students in national/international competitions.

José Orlando PereiraView profile

Associate Professor

• Dependable Distributed Systems
• Data Management
• Database Replication
• +7 more

José Orlando Pereira is an Associate Professor at the Department of Informatics, University of Minho, and Research Coordinator at INESC TEC (INESC Technology and Science). His primary research interests lie in dependable distributed systems, with a focus on data management, group communication protocols, and tools for distributed system evaluation. He leads the High-Assurance Software Laboratory (HASLab) , part of INESC TEC and the University of Minho. Roles: Academic supervisor, conference committee member (e.g., SRDS 2025 General Co-Chair), and grant recipient (e.g., ADAPQO funding from CMU Portugal 2024). Key Projects: Includes CYBERACTIONING (cybersecurity education), EUMaster4HPC (European HPC master's program), and AIDA (adaptive assurance platform). Research Themes: Database replication, georeplicated systems, consensus protocols, edge computing, and fault injection tools like LAZYFS. His work emphasizes practical applications, such as improving transactional performance in hybrid workloads (TiQuE) and designing scalable NoSQL middleware (CloudMdsQL). He has authored over 200 publications, including seminal contributions to gossip protocols (HyParView) and consensus algorithms. Awards: Honorable Mention at ACM SIGMOD 2025 for CRDV research. Active in organizing conferences such as SRDS, DSN, and EuroSys. Teaching: Offers advanced courses on distributed systems, database administration, and large-scale data replication at both undergraduate and graduate levels.

Anton DignösView profile

Associate Professor

• Temporal Databases
• Time Series Data
• Data Analytics
• +3 more

Anton Dignös is a tenured Associate Professor at the Free University of Bozen-Bolzano, Faculty of Engineering, where he leads the Database Systems Research Group. He holds a PhD from the University of Zurich (2014) and has been a faculty member since 2014. His research focuses on temporal databases, time series data, and data analytics, with contributions to indexing, query optimization, and benchmarking tools like TSM-Bench and SEER. Education : BSc and MSc (Computer Science) - Free University of Bozen-Bolzano (2008, 2010) PhD (Dr. sc. in Computer Science) - University of Zurich (2014) Research Interests : Dignös specializes in temporal database systems, time series management, and efficient query processing. He develops novel indexing techniques (e.g., RD-INDEX) and tools for benchmarking time series systems (SEER, TSM-Bench). His work addresses challenges like anomaly detection, sparse data summarization, and parallel join algorithms. Awards : Best Paper Award at SSDBM 2023 Best Paper Award at ADBIS 2022 ACM Computing Reviews Best of Computing (2017) Teaching & Advising : Teaches Data Management and Applied Informatics courses at both BSc and MSc levels. Advises ~25 students (PhD/MSc/BSc) on topics like temporal databases and machine learning applications. Active in thesis supervision and course development. Labs/Teams : Leads the Database Systems Research Group, collaborating on projects like the Period Index for temporal data and VISOR for data visualization tools.

Istemi Ekin AkkusView profile

Researcher

• Serverless Computing
• Confidential Computing
• Distributed Systems
• +2 more

Istemi Ekin Akkus is a researcher at the Max Planck Institute for Software Systems focusing on distributed systems and cloud computing technologies. His work advances serverless computing architectures with emphasis on privacy-preserving machine learning and verifiable data processing. Research areas include confidential computing for collaborative learning, secure data sampling methods, and adaptive machine learning training in cloud environments. He develops systems that address security challenges in distributed computing while maintaining performance efficiency.

Frank J PenedoView profile

Professor

• Behavioral and Psychosocial Processes in Health
• Patient Reported Outcomes (PROs)
• Sociocultural Determinants of Health
• +5 more

Frank J Penedo is a tenured Professor in the Department of Psychology at the University of Miami's College of Arts and Sciences . He serves as Director of the Cancer Survivorship and Supportive Care at Sylvester Comprehensive Cancer Center, while also leading the Biopsychosocial Mechanisms and Health Outcomes (BMHO) Lab and holding the Living Proof Endowed Chair in Cancer Survivorship . His work spans behavioral oncology, sociocultural health determinants, and eHealth interventions. Director, Biopsychosocial Mechanisms and Health Outcomes Lab Principal Investigator in NIH-funded studies Co-developer of EHR-integrated supportive care programs Dr. Penedo's research focuses on biopsychosocial pathways influencing cancer survivorship, with emphasis on Hispanic/Latino populations , technology-enabled interventions (e.g., TOGETHER, Fit2Thrive), and supportive care disparities . Current projects examine: Wearable activity monitor validation in lung cancer CBT for fear of recurrence in breast cancer Geographic cardiometabolic risk variation in Latino youth Primary care integration for cancer survivors His recent publications demonstrate interdisciplinary approaches combining prospective cohort studies (HCHS/SOL), biobehavioral assessments , and machine learning to address: Cancer screening disparities Psychosocial intervention efficacy Emergency care utilization patterns Neurocognitive aging biomarkers As a leader in cancer survivorship research , he advocates for precision health psychology frameworks through electronic health record integration and culturally tailored programs.

• Cryptography
• Cybersecurity
• Machine Learning
• +2 more

Nadav Voloch is an Assistant Professor at the IMT School for Advanced Studies Lucca. His research focuses on cryptography, cybersecurity, and machine learning applications in network security and traffic optimization. Key areas include developing encryption schemes, trust models for online social networks, and algorithmic solutions for robotic navigation. Research interests span cryptographic algorithms, privacy frameworks aligned with GDPR, and machine learning techniques for traffic management and misinformation detection. His work integrates mathematical foundations with practical applications in data security and social network analysis. Article analysis reveals a strong emphasis on cybersecurity innovations, including privacy-preserving trust models and traffic optimization algorithms. Recent publications focus on real-time applications, regulatory compliance, and combating misinformation through advanced computational methods. No awards, students, or lab affiliations are documented in the provided information.

Michael GeneserethView profile

Professor

• Computational Logic
• Enterprise Management
• Computational Law
• +4 more

Michael Genesereth is a Professor of Computer Science at Stanford University and a professor by courtesy in the Stanford Law School. He serves as director of the Logic Group at Stanford and is the founder and research director of CodeX - the Stanford Center for Legal Informatics. Genesereth is renowned for his groundbreaking work on Computational Logic and its diverse applications in Enterprise Management, Computational Law, and General Game Playing. His academic journey includes an Sc.B. in Physics from M.I.T. and a Ph.D. in Applied Mathematics from Harvard University (1978). These foundational studies paved the way for his influential career at the intersection of logic, computer science, and law. Genesereth's research program spans from theoretical foundations of logic programming to practical implementations across multiple domains. His work on General Game Playing has established frameworks enabling AI systems to understand and play games based purely on logical descriptions of rules. In Computational Law, he pioneers approaches for representing legal rules in machine-processable formats to automate compliance checking and legal reasoning. His Logic For All initiative has successfully introduced logic education to high schools across the United States, with teachers reporting significant improvements in students' preparedness for college-level coursework. The publication pattern reveals a sustained research trajectory focused on logic foundations, with recent work expanding into practical applications in computational law, insurance portfolio management, and knowledge representation systems. His 2022-2025 publications demonstrate continued innovation in logic programming frameworks and their real-world implementations. Genesereth has founded multiple technology companies including Teknowledge, CommerceNet, Mergent Systems, and Symbium, translating theoretical work into practical solutions. His educational impact extends through widely adopted textbooks and his free massive open online course (MOOC) on Introduction to Logic, which has enrolled hundreds of thousands of students globally. His current initiatives include the International Logic Olympiad, launched in 2024, which engages high school students worldwide in logic problem-solving competitions. This effort builds on his observation that high school students consistently perform well in his university-level logic courses, demonstrating the readiness of secondary students for formal logic education.

Ronghui GuView profile

Associate Professor

• Programming Languages
• Operating Systems
• Blockchain
• +7 more

Ronghui Gu is the Tang Family Associate Professor of Computer Science at Columbia University , where he leads the Columbia Lab in systems verification and proof automation. His work bridges academia and industry as co-founder of CertiK , a $2B Web3 cybersecurity startup. Education: Ph.D. in Computer Science, Yale University (2016) B.S. in Computer Science, Tsinghua University (2011) Gu's research focuses on Programming Languages , Operating Systems , Blockchain , and Formal Verification . His work emphasizes verified systems software, including quantum virtual machines, confidential computing, and smart contract security. Scientific Awards: NSF CAREER Award VMware Systems Research Award Amazon Research Awards OSDI Jay Lepreau Best Paper Award SOSP Best Paper Award CACM Research Highlights Distinguished Dissertation Award (Yale) Goldman Sachs Builders and Innovators Columbia’s Packard Fellowship Nominee The Top 100 Yale Alumni In Technology Gu's articles reveal trends in systems verification across quantum computing , blockchain security , and concurrent systems . His work increasingly integrates machine learning for invariant generation and formal methods for critical infrastructure. Advising & Grants: Advises current and former Ph.D. students including Runzhou Tao and Jianan Yao Received grants from NSF , DARPA , VMware , and Amazon Labs & Collaborations: Leads the Columbia Lab in verified systems software, co-developing tools like Serval , G-CLN , and DuoAI for blockchain and quantum verification.

Aaron PotechinView profile

Associate Professor

• Computational Complexity Theory
• Discrete Mathematics
• Algorithm Design
• +4 more

Aaron Potechin is an Associate Professor in the Department of Computer Science at the University of Chicago. His research focuses on computational complexity theory, discrete mathematics, and the sum-of-squares (SoS) hierarchy. He has contributed to areas such as constraint satisfaction problems (CSPs), space complexity via switching networks, and the analysis of random matrices. Potechin’s work bridges theoretical computer science with mathematical foundations, including algorithm design and logic. He holds an NSF grant for investigating the SoS hierarchy (CCF 2008920) and has been affiliated with the Theoretical Computer Science Group at UChicago. His academic journey includes a postdoctoral fellowship at KTH Royal Institute of Technology and notable awards like the Churchill Scholarship and NSF Graduate Research Fellowship. His research interests span: (1) the SoS hierarchy’s applications in combinatorial optimization, (2) approximability of CSPs, and (3) switching networks for space complexity. Recent work includes lower bounds for non-Gaussian component analysis and densest k-subgraph problems. Education Highlights: Recipient of the Barry M. Goldwater Scholarship (2008), Churchill Scholarship (2008), and NSF Graduate Research Fellowship. Grants: NSF Grant CCF 2008920 for SoS research. Awards: 2010 Machtey Award, 2009 George B. Covington Prize. Potechin teaches graduate courses on the SoS hierarchy, communication complexity, and statistical physics methods, alongside undergraduate courses in discrete mathematics and algorithms. His lab focuses on advancing theoretical computer science through rigorous mathematical frameworks.

Yoshimichi NakatsukaView profile

Researcher

• Web Security
• Privacy
• Trusted Computing
• +3 more

Yoshimichi Nakatsuka is a postdoctoral researcher at ETH Zurich's Department of Computer Science, affiliated with the Systems Security Group. He holds a PhD from the University of California, Irvine (advised by Prof. Gene Tsudik) and a Bachelor's degree from Keio University (advised by Prof. Hiroaki Nishi). His research focuses on the intersection of web security/privacy and trusted computing, addressing challenges in CAPTCHA evaluation, privacy compliance frameworks, and DNS security. Research Highlights Developed Scrappy for adversarial CAPTCHA analysis Created VICEROY for GDPR/CCPA-compliant privacy requests, earning a Best Poster Award at NDSS 2023 Pioneered PDoT : a trusted computing-based DNS-over-TLS solution Awards Best Poster Presentation Award at NDSS 2023 for VICEROY Professional Activities Active contributor to open-source security projects on GitHub, focusing on cryptographic protocols and privacy-preserving systems. Collaborates with industry leaders like Cloudflare on DAP implementations and DNS security enhancements.

• Vehicular Networks
• Cybersecurity
• Distributed Systems
• +3 more

Mohamed Mosbah is a Professor at the University of Bordeaux, affiliated with Bordeaux INP, France. His research focuses on distributed systems, vehicular networks, cybersecurity, and IoT security. He has co-authored over 200 publications, including works on VANET security, network slicing, and reinforcement learning applications. Education & Roles: Editor of journals/conferences like IEEE Communications Surveys & Tutorials, IEEE Transactions on Network and Service Management. Organizer of workshops such as DiCES-N (Distributed Computing for Emerging Smart Networks) and FPS (Foundations and Practice of Security). Research Interests: Develops protocols for vehicular safety messaging and cooperative perception. Explores network slicing for 5G/IoV environments and hybrid communication systems. Applies formal verification to distributed algorithms and machine learning for intrusion detection. Recent Work Trends: 2023-2024: Focus on DRL-based RAT selection, edge computing for micro-mobility, and resilient service chain provisioning. 2022-2023: Prioritization of ITS-G5 messages and energy-efficient geofencing models. 2020-2021: Hybrid vehicular networks and formal verification of distributed algorithms. Grants & Labs: Leading projects on vehicular cybersecurity and smart mobility optimization. Member of research groups in distributed systems and network security at Bordeaux INP.

• Partial Differential Equations
• PDEs Methods in Networks Analysis
• Actuarial Sciences
• +5 more

Nasreddine Megrez is an Associate Professor of Mathematics and Actuarial Sciences at the Dubai Campus of Heriot Watt University. He holds a MSc and PhD in Applied Mathematics from Toulouse University, France, and a Professional Master in Finance/Economics from the University of Quebec in Outaouais, Canada. His teaching roles include coordinating Year 4 programs and previously directing the MSc IT for Business program. His research focuses on Partial Differential Equations, PDEs in network analysis, Actuarial Sciences, and Mathematical Finance, with notable work on credit card fraud detection algorithms and Bayesian network methodologies. Key research contributions include applying PDE methods to network analysis and developing statistical models for dependence in financial data. He has taught extensively across North American systems at institutions like the University of Alberta and Alfaisal University (MIT-affiliated programs). Administrative experience includes Chair of Mathematics at Alfaisal University and Director roles at Heriot Watt. His work aligns with UN Sustainable Development Goals related to financial inclusion and crime prevention through innovations in fraud detection systems. No scientific awards are explicitly mentioned. He is currently accepting PhD students for 2024, focusing on statistical data science and actuarial applications. His research network spans collaborations in mathematical finance, computational biology, and cybersecurity, reflecting his interdisciplinary approach to solving complex analytical problems.