Find Academic Supervisors

Mauro PezzèView profile

Professor

• Software Engineering
• Software Testing and Analysis
• Self-Adaptive Systems
• +5 more

Mauro Pezzè is a Full Professor of Software Engineering at the Università della Svizzera italiana (USI) and Università di Milano Bicocca, leading the STAR research group since 2006. He holds a laurea from the University of Pisa and a PhD from Politecnico di Milano. His research focuses on software testing, analysis, self-adaptive systems, and cloud systems. He has held editorial roles, including Editor-in-Chief of ACM Transactions on Software Engineering and Methodologies (TOSEM), and served on numerous program committees. Education: Laurea (Pisa), PhD (Politecnico di Milano). Professional roles include Dean of the Faculty of Informatics at USI (2009-2013), visiting scientist at UC Irvine and Edinburgh, and technical lead for international projects. He co-authored a seminal book on software testing (Wiley, 2007), with over 670 citations. Research Interests: Software Testing, Self-Adaptive Systems, Cloud Computing, AI in SE, Sustainable Software. Projects include work on field-based testing, failure prediction in distributed systems, and neuro-symbolic approaches for test oracles. Grants and Advising: Led STAR Lab projects in self-healing systems, GUI testing, and semantic matching. Advised numerous PhD/postdoc students (e.g., Ciniselli, Di Grazia, Qiu). Collaborations with European tech firms on R&D initiatives. Labs/Teams: STAR Group at USI/Constructor Institute, Bicocca, and Politecnico di Milano. Current members include postdocs and PhD students working on AI-driven testing and cloud reliability.

Stephan RaveView profile

Researcher

• Numerical Analysis
• Scientific Computing
• Machine Learning
• +4 more

Dr. Stephan Rave is a Researcher in the Institute for Analysis and Numerics at the University of Münster. He is affiliated with the Applied Mathematics Münster cluster and serves as an Investigator in Mathematics Münster. His work focuses on numerical analysis, scientific computing, and machine learning, with a strong emphasis on model reduction techniques for complex systems. Education : PhD in Mathematics (2012), University of Münster, thesis on finitely summable K-homology. Master's and Bachelor's degrees in Mathematics from the University of Münster. Research Interests : Dr. Rave specializes in model order reduction (MOR) methods, including reduced basis techniques, localized orthogonal decomposition (LOD), and nonlinear approximation strategies. His work addresses challenges in multiscale modeling, domain decomposition, and parametrized partial differential equations. He also develops open-source software tools like pyMOR for MOR and contributes to initiatives like the MaRDI (Mathematical Research Data Initiative) to enhance interoperability in scientific computing. Projects : Key initiatives include the MaRDI project (2021–2026), EXC 2044 Cluster of Excellence (Geometry-based modeling), and MULTIBAT (lithium-ion battery simulation). His research bridges theoretical developments with practical applications in battery modeling, electrochemistry, and computational fluid dynamics. Grants & Awards : Funded by DFG, the German Federal Ministry of Research, and internal university grants, his work addresses strategic areas like sustainable research software and energy storage systems. He leads projects on distributed model reduction and communication-avoiding algorithms. Teaching : Dr. Rave teaches advanced numerical methods courses, including Model Order Reduction, Numerical Methods for PDEs, and Python-based computational labs. He co-organizes seminars and workshops on MOR and scientific software engineering.

Jens von WolfersdorfView profile

Professor

• Thermal Engineering
• Fluid Dynamics
• Aerospace Engineering
• +3 more

Jens von Wolfersdorf is a Professor at the University of Stuttgart's Faculty of Engineering, Department of Mechanical Engineering. His research focuses on advanced thermal management systems for high-speed aerospace applications, particularly in the areas of heat transfer, fluid dynamics, and combustion. He specializes in experimental and numerical methods for analyzing complex flows in rotating and stationary cooling channels, transpiration cooling for rocket engines, and turbulence modeling. His work integrates cutting-edge techniques such as thermochromic liquid crystal (TLC) measurements, particle image velocimetry (PIV), and computational fluid dynamics (CFD) to validate novel cooling configurations. Key projects include the COOREFLEX-Turbo initiative and contributions to the European ATLLAS-II program for high-speed vehicle materials. Recent studies emphasize rotational heat transfer effects in two-pass cooling channels, additive manufacturing of ribbed cooling structures, and validation of coupled FEM-CFD frameworks. His research addresses challenges in aerospace thermal protection, turbine blade cooling, and scramjet combustor efficiency. Publications span over 15 years, with a focus on transient heat transfer, flow visualization, and material characterization for transpiration-cooled systems. Collaborations involve experimental facilities for high-speed flows and advanced thermal measurement systems.

Jessica SunshineView profile

Professor

• Planetary Science
• Asteroid Composition
• Comet Studies
• +3 more

Dr. Jessica Sunshine is a Professor in the Department of Geology at the University of Maryland. Her research focuses on planetary materials and processes, particularly using spectroscopy and morphological analysis to study comets, asteroids, meteorites, and lunar geology. She is a principal investigator on NASA missions such as the Double Asteroid Redirection Test (DART) and the Lucy Mission, contributing to breakthroughs in planetary defense and asteroid composition analysis. Dr. Sunshine holds a Ph.D. from Brown University (1994). Her work integrates field-based and remote sensing techniques, including thermal infrared spectroscopy, to explore topics like the origins of spinel-rich deposits on the Moon, the composition of Trojan asteroids, and the dynamics of impact ejecta. She leads the Lunar Vulkan Imaging and Spectroscopy Explorer (Lunar-VISE) mission to study non-mare volcanic regions on the Moon. Her recent studies include analyzing the DART mission's impact on Dimorphos, revealing insights into asteroid deflection mechanics and surface material responses. She has also contributed to understanding the geological history of Ceres and the compositional diversity of Jupiter Trojans through the Lucy mission's data.

Chen BinbinView profile

Associate Professor

• Wireless Networking
• Distributed Systems
• Cyber Security for Critical Infrastructures
• +3 more

Chen Binbin is an Associate Professor and Associate Head of Pillar (Innovation and Enterprise) in the Information Systems Technology and Design (ISTD) pillar at Singapore University of Technology and Design (SUTD). He serves as Deputy Director for the Future Communications Research and Development Programme (FCP), Singapore. Previously, he was a Principal Research Scientist at the Advanced Digital Sciences Center (now Illinois ARCS), affiliated with the University of Illinois. Education: PhD in Computer Science from National University of Singapore, and Bachelor's from Peking University. Research focuses on wireless networking, distributed systems, and cyber security for critical infrastructures like smart grids and industrial control systems. His work addresses secure communications, intrusion detection, and resilience against cyber-physical threats. Notable contributions include error-estimating coding, provenance verification in ICS, and AI-driven network security solutions. Key awards include the 2010 ACM SIGCOMM Best Paper Award for error-estimating coding research. His grants span agencies like Singapore's National Research Foundation (NRF), Cyber Security Agency (CSA), and Energy Market Authority (EMA). He leads projects on secure smart grid communication, industrial control system defense, and AI-enhanced cybersecurity tools. Technical leadership involves developing frameworks like CyberSAGE for security assessment and CMD for IoT malware detection. Active in collaborations with industry and government, his work bridges theory and practice in securing critical infrastructure systems.

Brett HarrisView profile

Professor

• Geophysics
• Hydrogeology
• Mineral Exploration
• +4 more

Professor Brett Harris is a faculty member at Curtin University, affiliated with the School of Earth and Planetary Sciences (EPS) within the Faculty of Science and Engineering. He holds a prominent role in the Office of the Provost. His research focuses on subsurface resource technologies, including mineral exploration, CO2 sequestration, and geothermal energy. He has led major initiatives like the DET CRC and MinEx CRC projects, advancing in-hole electromagnetic sensing and distributed acoustic sensing techniques. His expertise spans hydrogeology, geophysics, and environmental geoscience, with notable contributions to aquifer characterization, fault zone dynamics, and CO2 storage monitoring. He coordinates undergraduate courses in electromagnetism, potential fields, and environmental geophysics, while supervising multiple PhD students. Key collaborations include work with government agencies on fractured aquifer detection and geothermal systems. Recent research emphasizes innovative sensor technologies for subsurface imaging, CO2 leakage monitoring, and groundwater sustainability. His work bridges geophysics with applied engineering solutions for resource exploration and environmental stewardship.

• Malaria
• Implementation Science
• Epidemiology
• +2 more

Adam Bennett is an Associate Professor of Epidemiology & Biostatistics at the University of California, San Francisco School of Medicine. His primary research focuses on malaria epidemiology, global health equity, and implementation science, with extensive field work in Southeast Asia (Laos, Thailand, Vietnam) and Africa (Zambia, Namibia). He is affiliated with UCSF's Institute for Global Health Sciences. Dr. Bennett's research examines innovative malaria control strategies including: Targeted interventions for high-risk populations (forest-goers, miners, agricultural workers) Reactive drug administration strategies Genomic epidemiology of malaria transmission Cost-effectiveness of elimination approaches Implementation science in low-resource settings His recent publications demonstrate a strong focus on malaria elimination methodologies, spatial epidemiology, and intervention studies in endemic regions. Research consistently addresses diagnostic approaches, drug administration protocols, and vector control methods tailored to specific transmission contexts.

Ruben MartinsView profile

Assistant Professor

• Constraint Programming
• Program Synthesis
• Formal Verification
• +3 more

Ruben Martins is an Assistant Professor at Carnegie Mellon University's School of Computer Science and serves as the program director of the Master of Science in Computer Science (MSCS) . His research focuses on the intersection of constraint programming, program synthesis, analysis, and verification, with recent work aiming to make formal methods tools more accessible through automated reasoning. Ruben earned his Ph.D. with honors from the Technical University of Lisbon, Portugal (2013) , followed by postdoctoral research at the University of Oxford (2014-2015) and UT Austin (2015-2017) . Research Interests : Ruben's work bridges constraint programming and program synthesis , with applications in software verification , optimization , and automated reasoning . He has developed award-winning tools like Open-WBO , a modular MaxSAT solver that has won gold medals in international competitions. His publications span top-tier venues such as POPL , PLDI , FSE , SAT , and CP , often addressing real-world challenges from program analysis to network security. Scientific Awards include: Distinguished Paper Award at PLDI 2018 Distinguished Paper Award at FSE 2021 Distinguished Paper Award at SAT 2022 Gold medals for Open-WBO in MaxSAT competitions Teaching & Advising : Ruben mentors Ph.D., Master’s, and undergraduate students in research projects related to program synthesis, formal methods, and constraint solving. He teaches courses such as Bug Catching: Automated Program Verification and Advanced Topics in Logic: Automated Reasoning and Satisfiability , emphasizing hands-on experience with tools like Why3. His advising spans topics from AI-driven program repair to network protocol verification , fostering collaboration across disciplines.

David G. DuffView profile

Professor

• Tax Law and Policy
• Corporate Taxation
• International Taxation
• +5 more

David G. Duff is a Professor of Law and Director of the Tax LLM program at the Peter A. Allard School of Law, University of British Columbia. He specializes in tax law and policy, corporate and international taxation, environmental taxation, and distributive justice. Prior to joining UBC in 2009, he was a faculty member at the University of Toronto Faculty of Law and held roles in tax policy analysis with the Ontario Ministry of Finance. He is affiliated with organizations such as the Canadian Tax Foundation and the International Fiscal Association, and has been a visiting scholar at institutions including Oxford University and the Max Planck Institute for Public Finance. Education: B.A., LL.B., M.A., LL.M. Research interests include tax avoidance, statutory interpretation, environmental taxation, and the intersection of tax law with social justice. He has been widely cited by the Supreme Court of Canada, notably in the 2011 SCC 63 decision on the Canadian GAAR. His work explores tax policy's role in addressing inequality and climate change, with a focus on international tax frameworks and Canadian tax law reforms. Publications span over 80 works, including seminal textbooks like *Canadian Income Tax Law* (7th ed., 2023) and *Taxation of Business Organizations in Canada*. His research trends emphasize GAAR interpretations, international tax treaty compliance, and environmental taxation strategies. Notable contributions include analyses of BEPS initiatives, cross-border income taxation, and the principal purpose test in treaty abuse prevention. Scientific Awards: Extensive citations in high-profile court decisions, though no explicit awards listed. Advising and grants: No specific student advisees listed, but his leadership in tax LLM programs suggests extensive teaching and mentorship. Grants and funding details are not detailed in the provided texts. Labs/Teams: Active in the Centre for Business Law at UBC and collaborates with global institutions like the Oxford University Centre for Business Taxation.

Niklas WahlbergView profile

Professor

• Lepidoptera Evolution
• Molecular Systematics
• Biogeography
• +5 more

Niklas Wahlberg is a Professor in Biological Systematics at Lund University, Sweden. He holds roles including Museum Director of the Biological Museum and Principal Investigator in the BECC biodiversity initiative. His primary affiliation is with the Department of Biology, focusing on evolutionary biology and systematics of Lepidoptera. Education & Career: PhD in Evolutionary Biology from University of Helsinki (2000) Postdoc at Stockholm University (2000–2002) Academy Research Fellowship at University of Turku (2006–2011) Professor in Genetics at Turku (2014) before moving to Lund in 2015 Research Interests: His work centers on the evolutionary history of Lepidoptera, particularly diversification patterns linked to angiosperm evolution and mass extinction events. He employs molecular systematic methods, next-gen sequencing, and museum specimens to study clade origins and biogeography. Key topics include Cretaceous diversification, post-mass extinction radiation, and genomic discordance in butterflies. Awards & Recognition: Web of Science Highly Cited Researcher (2017, 2018) Elected to Kungliga Fysiografiska Sällskapet (2016) Grants & Projects: Swedish Research Council: Testing gene-trait associations in genome modifications (2025–2029) Infrastructure leader for museum collections and holistic specimen projects Labs & Collaborations: Head of the Systematic Biology Group at Lund, managing the Biological Museum’s collections. Active in global entomology networks and co-organizes major conferences like the International Congress of Entomology.

Yanjun ZhangView profile

Research Fellow

• Cybersecurity
• Privacy-Preserving Technologies
• Federated Learning
• +3 more

Dr. Yanjun Zhang is an Honorary Research Fellow at the School of Electrical Engineering and Computer Science, The University of Queensland. His research focuses on privacy-preserving technologies, federated learning, cybersecurity in IoT systems, and machine learning security. He holds a PhD in Privacy-Preserving Sharing for Genome-Wide Analysis from The University of Queensland (2021). Education: PhD in Information Technology, School of Information Technology and Electrical Engineering, The University of Queensland (2021) Research Interests: Designing secure collaborative machine learning frameworks Defending against adversarial attacks in cyber-physical systems Privacy preservation in distributed genomic and medical data analysis Compliance and ethics in virtual personal assistant applications Key Contributions: Developed privacy-preserving federated learning frameworks (AgrAmplifier, PrivColl) Conducted foundational studies on evasion attacks in IoT systems Created datasets for analyzing malicious browser extensions and Alexa skills Labs/Teams: Active contributor to UQ Cyber initiatives, including the 2021-2022 Seed Funding project on federated deep learning for medical imaging.

John WrightView profile

Assistant Professor

• Quantum Computing
• Theoretical Computer Science
• Quantum Complexity Theory
• +3 more

John Wright is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research centers on theoretical computer science with a focus on quantum computing, specifically quantum state learning, quantum complexity theory, property testing, and approximation algorithms. He is affiliated with the Simons Institute for the Theory of Computing. Education includes a Ph.D. in Computer Science from Carnegie Mellon University (2016), advised by Ryan O'Donnell, and a B.Sc. in Computer Science from the University of Texas at Austin. Research interests span quantum complexity, interactive proofs (e.g., MIP* = RE), quantum algorithms, and foundational aspects of quantum computation. His work bridges computer science, physics, and mathematics, with emphasis on understanding computational limits through quantum paradigms. Publications primarily explore quantum complexity, algorithms, and verification, with recent trends including quantum cryptography, tomography, and hardness proofs. Articles frequently involve collaborations with researchers like Thomas Vidick, Henry Yuen, and Ryan O'Donnell. Awards include the IEEE CS TCPAMI Young Researcher Award (2015). Teaching covers graduate and undergraduate courses such as CS 170 (Efficient Algorithms and Intractable Problems) and CS 294 (Quantum Complexity Theory). He advises students in quantum computing research and collaborates extensively across institutions. Labs/teams include the Quantum Computing group at UC Berkeley, with ties to the Simons Institute. Research support is managed by Amy Frithsen.

Lisa YanView profile

Teaching Professor

• Computer Science Education
• Computing Ethics
• Teaching Assistant Training
• +2 more

Lisa Yan serves as a Teaching Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, appointed in Spring 2022. She teaches core computer science education courses including CS 195 (Social Implications of Computer Technology), CS H195 (Honors variant), CS 294-189 (Teaching Process Design), and CS 375 (Teaching Techniques), holding regular office hours in Soda Hall for student engagement. Her academic credentials include: PhD in Electrical Engineering from Stanford University (2019) MS in Electrical Engineering from Stanford University (2015) BS in Electrical Engineering and Computer Science from UC Berkeley (2013) Dr. Yan's research centers on data-driven analysis of student learning in large-scale computer science courses, with significant contributions to computing ethics pedagogy and teaching assistant development programs. Her work develops innovative methodologies for assessing student earnestness in interactive lectures, creating flexible learning extensions, and designing integrity-focused assessments. Earlier research focused on software-defined networking and network switch performance optimization, demonstrating technical depth before her pivot to educational innovation. Current projects emphasize scalable teaching techniques and mastery learning frameworks that address challenges in modern CS education. Analysis of her 14 publications (2013-2024) reveals a strategic shift from computer networking (pre-2018) to computer science education research (2018-present). Recent work (2020-2024) dominates in venues like SIGCSE, featuring tools such as Otter-Grader for Jupyter notebook grading and the Earnest Insight Toolkit for lecture participation analysis. This evolution highlights her commitment to solving practical educational challenges through data analysis and tool development, particularly for large undergraduate courses. She received recognition through: The Faculty Award for Outstanding Mentorship of GSIs (2024) Lisa actively mentors Graduate Student Instructors and collaborates with educational technology initiatives. Her research team includes dedicated support staff like Taylor Kaserman (taylor.kase@berkeley.edu), reflecting structured collaboration in developing teaching innovations. She contributes to curriculum design committees within EECS, focusing on assessment integrity and scalable pedagogical methods for growing student populations. Her work operates through the EECS department's educational infrastructure, utilizing Soda Hall resources for both teaching coordination and research development, with strong connections to Berkeley's broader computing education ecosystem.

Shad RoundyView profile

Associate Professor

• Energy Harvesting
• Wireless Power Transfer
• MEMS
• +5 more

Shad Roundy is an Associate Professor at the University of Utah , holding dual appointments in the Department of Mechanical Engineering and Department of Electrical and Computer Engineering within the College of Engineering . He directs the Integrated Self-Powered Sensing Lab , focusing on energy harvesting, wireless power transfer, and ubiquitous sensing systems. PhD in Mechanical Engineering, University of California, Berkeley (2003) Senior Lecturer, Australian National University (postdoctoral) His research bridges mechanical design , smart materials , and sensor networks , with significant contributions to: Self-powered biomedical implants Wearable health-monitoring devices Underground agricultural sensor networks MEMS sensor development His 15 most recent publications demonstrate interdisciplinary work spanning wireless power transfer for soil sensors, flexoelectric materials, and disease severity assessment via wearables. Articles emphasize energy efficiency , novel transducer designs , and environmental sensor applications . Scientific recognition includes: NSF CAREER Award for magnetoelectric implant powering Associate Editor, Smart Materials and Structures and International Journal of Precision Engineering and Manufacturing-Green Technology Research funded by National Science Foundation , NASA , and industry partners through the ASSIST Engineering Research Center . Publications highlight collaborations across biomedical, agricultural, and wearable technology domains.

Carl Ho (Ngai Man)View profile

Professor

• Power Electronics
• Heavy-Duty Electric Vehicles
• Renewable Energy Technologies
• +5 more

Dr. Carl Ho (Ngai Man) is a Full Professor and Canada Research Chair in Efficient Utilization of Electric Power at the University of Manitoba's Price Faculty of Engineering, Department of Electrical and Computer Engineering. Appointed Associate Head (Electrical Engineering) in July 2021, he leads the Renewable-energy Interface and Grid Automation (RIGA) Lab established with CFI funding in 2014. His educational background includes: PhD in Electronic Engineering (2007), City University of Hong Kong MEng in Electronic Engineering (2002), City University of Hong Kong BEng in Electronic Engineering (2002), City University of Hong Kong Dr. Ho's research focuses on power electronics applications for sustainable energy systems, with particular expertise in power conversion technologies for electric vehicles, renewable integration, and smart grid infrastructure. His work bridges industrial application and academic innovation, evidenced by over 40 IEEE journal publications, 80 conference papers, and 20+ patents. Current research emphasizes wide-bandgap semiconductor applications, power hardware-in-loop validation, and DC microgrid architectures for remote communities. Analysis of his recent publications reveals a strong trend toward practical implementation of power electronics solutions, with increasing focus on GaN/SiC devices, grid-forming converters, and modular architectures for microgrids. His work consistently addresses real-world challenges in efficiency, reliability, and cost-effectiveness across renewable integration, electric transportation, and power quality domains. Notable awards include: Second Place Winner for 2018 IEEE Transactions on Power Electronics Prize Paper Multiple IEEE JESTPE Star Associate Editor Awards (2022-2023) IEEE TPEL AE Excellence Award (2023) Best Student Team Regional Award in IEEE Empower a Billion Lives 2019 As an active mentor, Dr. Ho supervises numerous graduate students across multiple cohorts and leads significant research initiatives including NSERC Discovery Grants, MITACS collaborations with Power Integrations Inc., Research Manitoba Innovation Proof-of-Concept Grants, and Natural Resources Canada projects on zero-emission heavy vehicles. His RIGA Lab serves as a hub for industry-academic collaboration with Manitoba Hydro and transportation sector partners. The RIGA Lab, completed in 2016 and renovated in 2019, houses specialized equipment for power electronics prototyping, real-time simulation, and hardware-in-loop testing. Current projects include advanced wireless EV charging, GaN-based controller development, and DC microgrid solutions for remote communities, with recent recognition including a visit from Prime Minister Justin Trudeau in April 2023.