Find Academic Supervisors

Kevin John LomasView profile

Professor

• Building Physics
• Energy Efficiency
• Thermal Comfort
• +3 more

Professor Kevin John Lomas is a renowned academic at Loughborough University, holding the position of Professor of Building Simulation and serving as Division Lead for Architecture and Building. He directs the Loughborough Centre for Doctoral Training in Energy Resilience and the Built Environment. With over 35 years of expertise, his research focuses on building energy systems, thermal modeling, and climate-responsive design. He has secured £ millions in grants, supervised 40 PhD students, and authored over 140 publications. Trained as a civil engineer, his work bridges physics and architecture, addressing challenges like low-energy building design, indoor environmental quality, and overheating mitigation in residential and healthcare settings. Notable projects include the UK Energy Follow-up Survey, the Active Buildings Centre, and the REFIT initiative analyzing extreme heat impacts on urban populations. His research employs advanced methodologies such as synthetic occupancy testing in prototype homes, Bayesian calibration, and time-series forecasting to improve energy models. He collaborates with national agencies like BEIS and EPSRC, influencing policy through findings on building regulations, heat pump adoption, and climate resilience. Education: BSc, PhD, DSc (Doctor of Science), Chartered Engineer (CEng), Fellow of CIBSE (FCIBSE), Member of the Institution of Engineering and Technology (MEI) Key Projects: £2.4M EPSRC-SFI Energy Resilience CDT, £300k GCRF-funded REFIT study, £2.1M ERBE CDT Phase 2 Impact: Advised UK government on overheating risks, contributed to building regulation reforms, and developed operational rating systems for homes

Vito ScarolaView profile

Professor

• Theoretical Condensed Matter Physics
• Quantum Computing
• Quantum Simulation
• +3 more

Prof. Vito Scarola is a Professor in the Department of Physics at Virginia Tech's College of Science. His research focuses on theoretical quantum physics, particularly quantum simulation, quantum computing hardware, and topological states of matter. He holds a Ph.D. from Pennsylvania State University and has contributed extensively to foundational work in condensed matter physics and quantum information science. Education: Ph.D. in Physics from Pennsylvania State University. Research interests include: Algorithms for quantum simulation Quantum computing hardware (semiconductor and AMO systems) Topological states of matter (e.g., fractional quantum Hall effects) Quantum analogue simulation techniques His recent work explores hybrid quantum algorithms, error-resilient quantum gap estimation, and topological superfluid phases in optical lattices. He has advised numerous graduate students and postdocs, contributing to over 80 publications in top journals like Physical Review Letters and Science . Current research funding supports projects in quantum information theory, measurement-based quantum computing, and quantum simulation of molecular systems. His group actively collaborates with experimental teams in AMO physics and semiconductor nanotechnology.

Yukui LuoView profile

Assistant Professor

• Hardware-oriented Security
• FPGA Virtualization
• IoT Security
• +3 more

Yukui Luo is an Assistant Professor in the Department of Electrical and Computer Engineering at Binghamton University, SUNY. He earned his PhD in computer engineering (specializing in hardware-oriented security) from Northeastern University in 2023. His research focuses on advancing security in cloud and edge computing, with expertise in FPGA virtualization systems, IoT security, AI acceleration, and hardware accelerators. Education: Bachelor's: Shanghai University of Engineering Science Master's: Illinois Institute of Technology PhD: Northeastern University His research interests emphasize hardware trustworthiness, including FPGA-based virtualization, IoT security, AI acceleration defenses, and secure database systems. Recent work includes frameworks like TBNet for neural network protection in trusted environments and AdAPI for efficient private inference in edge computing. Notable contributions include publications at DAC 2024, ICCAD 2024, and IEEE conferences addressing FPGA vulnerabilities, privacy-preserving machine learning, and adversarial attack mitigation. He advises PhD students focusing on FPGA acceleration, hardware security, and machine learning. His lab explores cutting-edge solutions for secure computing in multi-tenant environments and edge devices. Dr. Luo actively recruits PhD students (starting Fall 2026) with strong technical backgrounds in computer architecture, FPGA design, cybersecurity, or related fields. He emphasizes rigorous application requirements, including academic records and critical engagement with his research papers.

Francis YanView profile

Assistant Professor

• Networked Systems
• Computer Networks
• Machine Learning for Systems
• +3 more

Francis Yan is an Assistant Professor of Computer Science at the University of Illinois Urbana-Champaign (UIUC), affiliated with the Siebel School of Computing and Data Science and the Electrical & Computer Engineering department. He leads the Illinois Networked Systems and AI (NSAI) Lab, focusing on integrating practical machine learning into networked systems. Previously, he was a Senior Researcher at Microsoft Research Redmond, working on systems and networking research. His work emphasizes deployable ML solutions, validated through large-scale platforms like Puffer and Pantheon. Education: Ph.D. in Computer Science (Stanford University, 2020); B.S. in Computer Science (Tsinghua University, 2015) and B.A. in Economics (Tsinghua University, 2015). Research Interests: Networked systems, machine learning for systems and networking, intelligent video systems, and cloud resource management. His lab develops frameworks like DeDe, Mowgli, and Autothrottle to enhance system performance and robustness. Awards: USENIX NSDI Outstanding Paper Award (2024), Applied Networking Research Prize (2021), and USENIX ATC Best Paper Award (2018). He serves on program committees for NSDI, SIGCOMM, and ACM workshops. Grants & Service: Co-chair of SIGCOMM 2024 Artifact Evaluation. Active in open-source projects and research platforms supporting reproducible networking experiments. Labs/Teams: Directs the NSAI Lab, collaborating on projects such as Puffer (400k-user video service), Teal (WAN optimization), and Genet (curriculum learning for networking).

• Coding Theory
• Telecommunications
• Signal Processing
• +4 more

Dr. Vladimir Sidorenko is a Senior Researcher at the Institute for Communications Engineering, Technical University of Munich (TUM), since January 2015, on leave from the Institute for Information Transmission Problems (IITP), Russian Academy of Sciences. His academic career includes roles at Ulm University (2003–2014) and the Computer Center of the Russian Health Ministry (1975–1983). He holds an M.S. in Electrical Engineering (1972) and a Ph.D. in Mathematics (1975) from the Moscow Institute for Physics and Technology. Research Interests: Coding theory, telecommunications, signal processing, cryptology, and applications. His work focuses on error correction, network security, quantum computing, and cryptographic protocols. He has authored over 140 papers in these areas. Recent Research Trends: Dr. Sidorenko’s recent work emphasizes quantum stabilizer codes decoding , network coding security , and PUF-based key agreement systems . His publications in 2023–2024 highlight advancements in polymorphic Gabidulin codes , data protection in networks , and minimal trellis structures for quantum codes . Awards: Recipient of the In-centi Award for Best Lecturing (Ulm University, 2003–2014). Collaborations: Invited researcher at institutions including Lund University (Sweden), Darmstadt TU (Germany), and Southwest Jiaotong University (China). Active in projects like Secure Key Agreement with PUFs and Concatenated Convolutional Codes .

Alex SchwarzmannView profile

Professor

• Cyber Security
• Distributed Computing
• Election Integrity
• +3 more

Alex Schwarzmann is a Professor and Dean in the Department of Computer Science at Augusta University's School of Computer and Cyber Sciences. He holds a Ph.D. and MS in Computer Science from Brown University (1992, 1989) and an MS from Cornell University (1981). His research focuses on distributed computing systems, cyber security, election integrity, and cryptographic protocols. He has led initiatives in secure distributed storage systems, fault-tolerant algorithms, and voting system security. Notably, he received the 2022 and 2010 Edsger W. Dijkstra Prizes in Distributed Computing for foundational contributions to the field. His work integrates theoretical rigor with practical applications, such as developing robust frameworks for election-day voter check-in and securing atomic memory operations. He has served as Committee Chair for the 5th International Symposium on Cyber Security Cryptology and Machine Learning (CSCML 2021). His research spans distributed consensus algorithms, intrusion detection mechanisms, and privacy-preserving technologies in networked systems. Recent publications highlight advancements in atomic storage systems, low-latency distributed memory, and mitigating vulnerabilities in multi-source transfer learning. His grants include NSF funding for secure voting systems and resilient distributed frameworks.

Zhiyuan YanView profile

Professor

• Coding Theory
• Wireless Communications
• VLSI Design
• +4 more

Zhiyuan Yan is a Professor and Associate Chair in the Department of Electrical and Computer Engineering at Lehigh University. He holds a B.E. from Tsinghua University and M.S./Ph.D. degrees from the University of Illinois at Urbana-Champaign. His research focuses on coding theory, VLSI design, wireless communications, and embedded systems. He is a Senior Member of the IEEE and received the NSF CAREER Award in 2011. Educational Background: B.E., Electrical Engineering, Tsinghua University M.S., Electrical Engineering, University of Illinois at Urbana-Champaign Ph.D., Electrical Engineering, University of Illinois at Urbana-Champaign Research Interests: His work spans coding theory (including polar codes and LDPC codes), VLSI implementations for communication systems, and cybersecurity through physical unclonable functions (PUF). He explores neuromorphic computing, memristive neural networks, and hardware-efficient error correction techniques. His contributions include efficient decoder architectures and distributed storage solutions. Scientific Awards: 2011: NSF CAREER Award Advising & Grants: While specific student names aren't listed, his research has been supported by multiple grants. His lab focuses on collaborative projects between academia and industry, emphasizing practical implementations of theoretical advancements. Lab & Teams: His research team develops cutting-edge VLSI systems, neural network accelerators, and secure communication protocols. Collaborations include work on memristive hardware and neuromorphic computing architectures.

Hausi A. MüllerView profile

Professor

• Quantum Computing
• Self-Adaptive Systems
• Cyber-Physical Systems
• +3 more

Hausi A. Müller is a Professor at the Department of Computer Science , University of Victoria , and serves as Associate Dean of Research in the Faculty of Engineering. He holds leadership roles in IEEE, including Vice President of the IEEE Computer Society Technical & Conferences Activities Board (T&C) and 2024-25 Chair of the IEEE Quantum Technical Community (QTC) . Research focuses on Quantum Computing , Self-Adaptive Systems , and Cyber-Physical Systems Key projects include NSERC CREATE grants for Quantum Computing and Dependable IoT systems Developed foundational frameworks like DYNAMICO and SmarterContext for context-aware systems Scientific Awards include: 2011 IBM Canada CAS Research Project of the Year Award CASCON 2012 Best Paper Award ACM Senior Member (2016) Fellow of the Canadian Academy of Engineering (FCAE) and IEEE (LMIEEE) His quantum computing research explores hybrid quantum-classical algorithms, educational frameworks like QNotation , and bioinformatics applications such as RNA folding via QUBO models. Current work emphasizes practical quantum applications and proactive AIOps using digital twins.

Jia JiaView profile

Lecturer

• Cybersecurity
• Cryptography
• Blockchain Technology
• +5 more

Dr. Jia Jia is a Lecturer in International Business and Strategy at Plymouth Business School (Faculty of Arts, Humanities and Business), University of Plymouth. Her research focuses on cybersecurity, cryptography, blockchain technology, and federated learning. She has held previous academic roles at UCL School of Management and Royal Holloway University of London. Her work bridges business strategy with technological advancements, particularly in secure digital systems and AI-driven cybersecurity solutions. Teaching Responsibilities include courses such as International Business Strategy, Asia-Pacific Business Management, and Capstone/Honours Project supervision. She actively contributes to research in e-voting security, identity-based identification systems, and distributed PKI frameworks. Recent publications address challenges in Byzantine-robust federated learning, blockchain-based e-auctions, and post-quantum cryptographic systems. Research interests span interdisciplinary areas including: Cybersecurity in pervasive computing environments Blockchain and smart contract applications Secure data transfer protocols in cloud computing Adaptive adversary resistance in distributed systems Her articles highlight contributions to e-voting security, federated learning resilience, and AI-driven hazard simulation for driver education. Current doctoral supervision includes Tonari Arikekpar’s work on Nigerian international students’ experiences. No academic awards are listed.

• Computational Thinking
• Game Design
• Computer Science Education
• +3 more

Alexander Repenning is an Adjunct Professor at the University of Colorado Boulder, specializing in computational thinking and game design for education. His research focuses on developing tools like RULER to teach programming through creative projects. Research Focus: Computational thinking integration in K-12 curricula Game design as a pedagogical tool AI-assisted learning environments Publications: Recent works explore scaffolding techniques, error culture in education, pandemic-related learning shifts, and novel programming paradigms. Contact: ralex@colorado.edu

Chris WinsteadView profile

Associate Professor

• Error Correction Algorithms
• Probabilistic Logic
• Neuromorphic Circuits
• +3 more

Chris Winstead is an Associate Professor in the Department of Electrical and Computer Engineering at Utah State University. His research focuses on error correction algorithms, probabilistic logic systems, and neuromorphic hardware design. He has mentored over 15 graduate students and received significant recognition including an NSF Career Award. Dr. Winstead's research spans hardware security, stochastic computing, and communication systems. His work integrates theoretical frameworks with practical implementations for low-power and fault-tolerant systems. Recent publications demonstrate applications in autonomous vehicle security, biological circuit modeling, and probabilistic computing architectures. Honors include the 2014 Fulbright Research Scholarship and 2010 NSF Career Award. He leads research on noise-enhanced computing methods and maintains collaborations in stochastic algorithm development. Current projects investigate adversarial resilience in cyber-physical systems and hardware acceleration for probabilistic decoders.

• Quantum Physics
• Optical Physics
• Theoretical Chemistry
• +5 more

Professor Florian Mintert is a Professor of Physics at the Department of Physics within the Faculty of Natural Sciences at Imperial College London. His research focuses on quantum physics, optical physics, and theoretical chemistry, with notable contributions to quantum control, photon condensation, and quantum computing. He is affiliated with several research groups including the Quantum Optics and Laser Science Group and the Quantum Engineering, Science and Technology (QuEST) initiative. Key research interests include quantum many-body systems, quantum error correction via surface code defects, and the exploration of non-classical optical phenomena such as Bose-Einstein condensation of light. His work bridges theoretical and experimental quantum mechanics, often employing advanced techniques like Bayesian optimization and optimal control theory. Recent publications highlight advancements in noise-resilient quantum gates for trapped ions, prethermalization in superconducting processors, and the dynamics of photon condensates in microcavities. These studies emphasize interdisciplinary approaches, combining quantum optics with engineering and computational methods to address fundamental challenges in quantum technologies. Professor Mintert’s research is supported by affiliations with Imperial’s Blackett Laboratory and the broader Light Community initiative, fostering collaborations across disciplines. His work contributes to foundational knowledge in quantum science while advancing practical applications in quantum computing and quantum communication systems.

• Software Reliability
• Software Security
• Symbolic Execution
• +6 more

Cristian Cadar is a Professor in the Department of Computing at Imperial College London, leading the Software Reliability Group. He holds an ERC Consolidator Grant and is an EPSRC Early-Career Fellow. His research focuses on enhancing software reliability and security through techniques like symbolic execution and dynamic analysis. Education: PhD in Computer Science (Stanford University), M.Eng. and B.S. in Computer Science and Mathematics (MIT). Research interests include software engineering, computer systems, and security, with a focus on practical tools for testing and verification. His work has led to advancements in symbolic execution, compiler testing, and dynamic software updates. Key publications span topics like KLEE, symbolic execution optimization, and compiler fuzzing. Awards include the BCS Roger Needham Award, Humboldt Research Award, and SIGOPS Hall of Fame recognition. He advises PhD students and postdocs, focusing on systems programming and compilers. His lab develops tools like KLEE and explores multi-version execution and greybox fuzzing.

Michael MaireView profile

Associate Professor

• Computer Vision
• Machine Learning
• Deep Learning
• +5 more

Michael Maire is an Associate Professor in the Department of Computer Science at the University of Chicago, with a courtesy appointment at the Toyota Technological Institute at Chicago (TTIC). His research focuses on computer vision, machine learning, and deep learning, particularly in neural network architectures, optimization, and self-supervised learning. Prior to UChicago, he held roles at TTIC and Caltech, and earned his Ph.D. from UC Berkeley in 2009. His work spans perceptual organization, object recognition, and representation learning. Key contributions include the Microsoft COCO dataset, fractalnet architectures, and spectral embedding techniques for segmentation and figure/ground organization. He advises students on topics like efficient network growth, sparsification, and contrastive learning. He co-leads the Machine Learning Group at UChicago and contributes to the CERES Center for Unstoppable Computing. His research has been published in top venues like CVPR, ICCV, and NeurIPS, with over 30 peer-reviewed articles since 2004. Teaching includes courses on computer vision and deep learning fundamentals.

• Computer Science Education
• Programming Pedagogy
• Visual Programming
• +3 more

Dr. Sverrir Thorgeirsson is a Professor of Computer Science at ETH Zürich, affiliated with the Department of Computer Science under the School of Computer and Communication Sciences. His work focuses on innovative educational technologies and pedagogical frameworks to enhance programming education. His research interests include visual programming languages (e.g., Algot), cognitive aspects of learning (e.g., cognitive load measurement via EEG), and strategies to improve abstraction skills and software testing comprehension in students. He emphasizes bridging the syntax-semantics gap in programming through hands-on, interactive tools. Recent publications highlight his contributions to visual programming environments, failure-based learning, and the design of pedagogical frameworks. He actively explores how cognitive science principles can optimize educational outcomes in introductory and advanced CS courses. No scientific awards were explicitly listed. His advising and grants sections remain under development, pending additional data.