Find Academic Supervisors

Andrew D QuinnView profile

Professor

• Climate Adaptation
• Infrastructure Resilience
• Transport Systems
• +4 more

Professor Andrew D Quinn is a Professor of Climate Adaptation at the University of Birmingham's Department of Civil Engineering, affiliated with the College of Engineering and Physical Sciences. He serves as Director of Education for the College, overseeing strategic educational initiatives including trans-national programs. His research bridges civil engineering and environmental science, focusing on infrastructure resilience to climate change, particularly in rail and transport systems. Quinn leads the Resilience Systems and Climate Action (RSCA) research group and has contributed to global frameworks like the International Union of Railways (UIC) climate adaptation guidelines. Education: BSc (Hons) Mathematical Physics, University of Nottingham (1992) PhD in Civil Engineering, University of Birmingham (1996) Research Interests: Climate adaptation, infrastructure resilience, wind engineering, transport systems, and environmental policy. His work emphasizes interdisciplinary approaches to global challenges like extreme weather impacts and sustainable development goals. Quinn’s publications (over 60 journal articles) span climate resilience, wind dynamics, and transport safety. His awards include the IMechE J F Alcock Memorial Prize and Principal Fellowship of the Higher Education Academy. He supervises PhD students in wind engineering, climate adaptation, and infrastructure resilience. Awards & Recognition: IMechE WA Agnew Meritorious Award (2014) EPSRC Peer Review College Member Fellow of the Institute of Mathematics and its Applications (FIMA, 2018) Education Leadership: Quinn champions pedagogical innovation, including feedback strategies to enhance student learning. His role in widening STEM participation includes outreach via the STEM Ambassadors program. Labs & Teams: Leads the RSCA group and collaborates on EU-funded projects like SIRMA (infrastructure risk management) and ASAP-East Africa (air quality and economic development).

• Computer Architecture
• Memory Systems
• Reconfigurable Computing
• +6 more

Ronald Dreslinski is a Professor in the Department of Computer Science and Engineering at the University of Michigan, College of Engineering. His work focuses on computer architecture, memory systems, and reconfigurable computing, with applications in machine learning, wireless communication, and autonomous systems. Research spans hybrid memory systems, fault-tolerant networks, and low-power processors Key technologies include PIM (Processing-in-Memory), systolic arrays, and Galois field accelerators His publications highlight trends in adapting reconfigurable architectures for sparse data, optimizing wireless communication decoders, and integrating neural networks with traditional circuit design. He mentors PhD students through weekly 1-on-1 meetings, project-specific sessions, and group presentations. The department emphasizes broadening participation in computing and student support through community initiatives.

• Virtual Reality
• Human-Computer Interaction
• Assistive Technologies
• +5 more

Dr. Howe Zhu is a Lecturer of Interactive Design at the University of Sydney's School of Architecture, Design and Planning. He holds a PhD in Computer Science from UTS (2022) and a BE in Biomedical Engineering from the University of Sydney (2017). His research focuses on human-centric technologies, including metaverse systems, assistive technologies for visually impaired individuals, and brain-computer interfaces. Education: PhD in Computer Science, UTS, 2022 BE in Biomedical Engineering (Mechatronics), University of Sydney, 2017 Research interests span virtual/augmented reality, spatial audio processing, and sensory augmentation systems. Recent work emphasizes auditory interfaces for navigation assistance and stress effects on neurotechnology. His publications explore metaverse infrastructure, binaural sound rendering, and human factors in assistive technologies. Notable contributions include studies on brain-computer interfaces in metaverse systems, acoustic touch for vision impairment, and spatial memory enhancement through auditory cues. His work bridges biomedical engineering with interactive design to create inclusive technologies.

Richard DewhurstView profile

Professor

• Ruminant Nutrition
• Dairy Science
• Milk Composition
• +4 more

Richard Dewhurst is Professor of Ruminant Nutrition & Production Systems at Scotland's Rural College (SRUC), where he serves as Head of the Dairy Research and Innovation Centre. His research bridges dairy nutrition, milk composition, and rumen function, with emphasis on forage modeling, feed efficiency, and methane emission reduction using metagenomic approaches. Research focuses include: developing proxies for digestive efficiency through gene-centric rumen metagenomics; nitrogen isotopic fractionation; and managing the long-term Langhill Dairy Cow breeding study. Current projects investigate microbiome-driven breeding strategies and precision livestock technologies for greenhouse gas mitigation. He has supervised 20+ PhD students including projects on rumen biohydrogenation, microbial biomarkers, and whole-farm modeling. Awards include the President's Prize (1987) and Sir John Hammond Memorial Award (2008). Recent publications explore microbiome stability in cattle, precision farming emissions, and in-utero effects on dairy resilience. As Principal Investigator for multiple EU Horizon and Innovate UK projects, he leads international consortia including HoloRuminant and SmartCow. He chairs committees for the Global Research Alliance and British Society of Animal Science.

Smaranda MuresanView profile

Associate Professor

• Natural Language Processing
• Social Good
• Responsible Computing
• +9 more

Smaranda Muresan is an Associate Professor in the Department of Computer Science at Barnard College, Columbia University. She is also an Affiliate Faculty in Columbia's Department of Computer Science and a member of the Data Science Institute (DSI). Her research focuses on human-centric Natural Language Processing (NLP) for social good and responsible computing, emphasizing theory-guided and knowledge-aware computational models for understanding and generating language in diverse contexts. Key research areas include argument mining, fact-checking, figurative language processing, multilingual NLP for low-resource languages, and explainable AI. Before joining Barnard in 2024, she was a Research Scientist at Columbia's Data Science Institute and a faculty member at Rutgers University's School of Communication and Information, where she co-founded the Laboratory for the Study of Applied Language Technologies and Society. She earned a Distinguished Achievements in Research Award during her time at Rutgers. Muresan has led significant grants, including NSF-funded projects on fine-grained visual classification with text and images, and reducing STEM achievement gaps using NLP. She is also a Technical Lead in DARPA's DEFT Program for detecting contradictions in text and speech. Her teaching includes undergraduate and graduate courses in NLP, multilingual technologies, and computational models of social meaning. She actively contributes to professional activities, including workshops on figurative language processing and argument mining.

Long ChenView profile

Lecturer

• Digital Twin Technology
• Systems Engineering
• Design Change Management
• +2 more

Dr. Long Chen is a Lecturer at the School of Architecture, Building and Civil Engineering, Loughborough University. He holds a PhD and BEng, with professional affiliations including MCIOB and A.M.ASCE. Previously, he was a Postdoctoral Research Associate at Imperial College London's Centre for Systems Engineering and Innovation (CSEI), where he contributed to the CDBB-funded project 'Analysing Systems Interdependencies using a Digital Twin' and the Alan Turing Institute/Lloyd’s Register Foundation's 'Grand Challenge III: Data-Driven Design Under Uncertainty'. His research focuses on digital twin-driven approaches for design change management in complex systems and image-based digital twinning for as-built buildings. Key research areas include Systems Engineering, Data-Centric Engineering, and Building Information Modeling. Dr. Chen's publications primarily explore machine learning fairness, Bayesian computation, and computer vision techniques, with recent works addressing algorithmic bias mitigation, transformer calibration, and semantic segmentation robustness. His research demonstrates consistent applications in probabilistic modeling and adaptive systems. He maintains active collaborations with Imperial College London and the Alan Turing Institute, leveraging his expertise in systems interdependencies and digital twin implementations.

• Cybersecurity
• Leadership
• Behavioral Psychology
• +6 more

Marc Toledo is a doctoral candidate in Strategy and Organisational Behaviour at Imperial College Business School, specializing as the resident cybersecurity expert within the Department of Management and Entrepreneurship. He holds advanced degrees from institutions including Duke University’s Fuqua School of Business (MBA) and Imperial College London (MRes). His career spans 15+ years in cybersecurity strategy, public service, and private sector innovation roles at firms like EY, Apple, and the World Bank. Education highlights include a B.A. in Translation from the Autonomous University of Barcelona/UCLA, a Computer Engineering degree from the Polytechnic University of Catalonia, and certifications like CISSP (Certified Information Systems Security Professional). He is a licensed investigator and Fellow at FASPE and Duke University’s Coach K Center on Leadership and Ethics. Research focuses on leadership in disruptive technologies, cybersecurity ethics, and behavioral psychology. Key interests include cybercrime forensics, privacy law, hacker culture analysis, and gender equity in tech. He advises global organizations on digital transformation and coaches executives on strategic leadership. Awards include prestigious fellowships in professional ethics and cybersecurity leadership. His articles span cybersecurity policy, blockchain applications, and pandemic-era digital behavior studies, published in outlets like Harvard Business Review.

P Taylor WebbView profile

Professor

• Education Policy
• Racial Biopolitics
• Neoliberalism
• +3 more

P Taylor Webb is a Professor in the Department of Educational Studies at the Faculty of Education, University of British Columbia (Vancouver campus). His research focuses on education policy's intersections with neoliberalism, racial biopolitics, and computational governance. He critically examines how algorithms, datafication, and corporate partnerships reshape educational systems through policy frameworks, emphasizing resistance and decolonial perspectives. Key research areas include postdigital governance, racialized policy enactments, and the biopolitical dimensions of education. His work interrogates how technologies like AI and data analytics create new forms of governance, while also exploring institutional racism through case studies like Islamic and Afrocentric schools. Publications highlight policy mobilities, prolepsis (anticipatory governance), and event-based policy analysis. Recent works critique Big Tech's influence in universities and analyze pandemic-era educational contagion metaphors. Webb's research outputs consistently address policy's affective dimensions, spatial geographies, and ethical implications, proposing inventive methodologies to counteract neoliberal and proto-fascist tendencies in education systems.

Matthew OttenView profile

Assistant Professor

• Quantum Information Science
• Open Quantum Systems
• Quantum Computing
• +3 more

Matthew Otten is an Assistant Professor in the Department of Physics at the University of Wisconsin–Madison. His research focuses on advancing quantum technologies through theoretical work on quantum information science, open quantum systems, and quantum computing. He leads the Otten Group, which aims to develop scalable quantum algorithms, error mitigation techniques, and resource estimation frameworks for utility-scale quantum applications. Education and Background: Otten's research bridges theory and experiment, with a focus on simulating quantum hardware performance and optimizing quantum error correction protocols. His group collaborates with experimentalists to study semiconductor qubits, superconducting qubits, and neutral atom systems. Research Interests: Key areas include quantum algorithms for chemistry and machine learning, quantum characterization/verification/validation (QCVV), and high-performance computing simulations of open quantum systems. His lab develops tools like QREChem for estimating quantum resource requirements and improving algorithm scalability. Team: Current advisees include graduate students Zachary Jerzyk and Colin Stewart, as well as undergraduates Sofiia Lauten and William Leitch. The group emphasizes interdisciplinary approaches combining physics, computer science, and materials science. Labs & Infrastructure: Utilizes advanced simulation capabilities and collaborates with institutions like Argonne National Lab and Lawrence Livermore National Lab on quantum-centric supercomputing initiatives.

Dishita TurakhiaView profile

Research Fellow

• Human-Computer Interaction
• Learning Sciences
• Ubiquitous Sensing
• +5 more

Dishita Turakhia is a Faculty Fellow at NYU's Tandon School of Engineering, specializing in the intersection of Human-Computer Interaction and Learning Sciences. She holds a Ph.D. in Electrical Engineering and Computer Science from MIT, with a minor in Brain and Cognitive Science. Her research focuses on designing systems for learning physical skills using technologies like AR/VR, generative AI, and ubiquitous sensing. Education: Ph.D. (MIT EECS 2024), M.S. (MIT EECS 2017), S.M.ArchS (MIT Architecture 2017), M.Sc. (AA School of Architecture EmTech 2011). Research interests include adaptive learning tools, open-ended VR training systems, and reflection-based learning. She has secured $2.2M in grants, including NSF Career and MIT grants. Notable awards include the EECS Rising Stars (2023) and Meta Ph.D. Fellowship. Her work spans postdoctoral research at MIT's LEAP Group, internships at Meta Reality Labs, and industry experience as a computational designer. She leads the VIDA group and teaches HCI courses at NYU Tandon.

• High Performance Computing
• Computer Architecture
• Hardware-Software Co-design
• +3 more

Shuaiwen Song is a SOAR Associate Professor (tenured) at the School of Computer Science , University of Sydney, and directs the Future System Architecture (FSA) Lab . He holds affiliated professor positions at the University of Washington's Electrical Engineering department and serves as a Visiting Professor at Microsoft. Key research areas: High Performance Computing (HPC), Hardware-Software Co-design, Emerging Architectures (heterogeneous, quantum), and System ML Current projects: Large-Scale Sparse Model Design (Google), Tiered Memory Systems (Google), Compiler Optimizations for Heterogeneous Computing (Microsoft/Alibaba), Planet-Scale XR Systems (Meta), Quantum System Architecture (Australian Research Council) His work bridges system software and hardware, focusing on holistic design for complex many-accelerator systems and futuristic architectures like VR/AR and quantum accelerators. Recent publications highlight advancements in temporal graph processing, VR rendering, and ReRAM-based CNN training. He has received prestigious awards including IEEE Mid-Career Award for Scalable Computing , Alibaba AIR Faculty Award , and Australia's Most Innovative Engineers recognition.

• Quantum Computing
• Quantum Algorithms
• Quantum Error Correction
• +3 more

Gokul Ravi is a Professor in the Department of Computer Science and Engineering at the University of Michigan. His research focuses on quantum computing, quantum algorithms, compiler optimization for quantum systems, and computer architecture. He leads a research group emphasizing impactful research in quantum domains, with weekly one-on-one and group meetings fostering collaboration and community. Students benefit from lab lunches where they discuss projects, papers, and potential collaborations. He prioritizes clear communication, with expectations including 5-6 years of PhD tenure and 3+ top-tier publications. Research interests span variational quantum algorithms, error mitigation, quantum cloud computing, and hardware-software co-design. His work addresses challenges in fault-tolerant quantum computing, compiler passes for NISQ applications, and quantum-centric supercomputing for materials science. Recent publications highlight innovations in quantum algorithm design, error correction, and hybrid systems. Students receive weekly progress updates and yearly feedback. He supports internships (up to 2) aligned with research and facilitates conference attendance via travel grants. Vacation planning is flexible but avoids deadlines. His mentoring style adapts to individual student needs, balancing independence with mentorship, particularly in early PhD stages.

Albrecht SchmidtView profile

Professor

• Human-Computer Interaction
• Ubiquitous Computing
• Media Technology
• +5 more

Prof. Albrecht Schmidt holds the Chair of Human-Centered Ubiquitous Media at Ludwig Maximilian University of Munich (LMU), part of the Faculty of Mathematics, Informatics and Statistics. His academic career spans roles at leading institutions including the University of Stuttgart, University of Duisburg-Essen, and Bonn University. He specializes in human-computer interaction, focusing on enhancing human capabilities through digital technologies. His research bridges cognitive science, AI, and ubiquitous computing, with notable projects on AR/VR interfaces, robot interaction, and smart home privacy solutions. Education: PhD in Computer Science (Lancaster University, 2003), Diplom in Informatik (University of Ulm, 1999). Recognized as a Leopoldina member (2020) and ACM SIGCHI Academy member (2018). Research interests include AI-driven human augmentation, privacy-aware smart systems, and ethical implications of generative AI. Key projects include ERC-funded AMPLIFY (2016) exploring perception enhancement, DFG's SFB-TRR161 on visual computing, and EU's HumaneAI on human-centric AI. Publications span over 600 works in top venues like CHI, UbiComp, and IEEE Pervasive Computing. Current initiatives focus on LLM integration in HCI, tangible privacy controls, and AI bias mitigation in data annotation.

Shih-Hsi LiuView profile

Professor

• Software Engineering
• Meta-heuristics
• Evolutionary Algorithms
• +5 more

Shih-Hsi (Alex) Liu is a Professor in the Department of Computer Science at Fresno State. He holds a Ph.D. from the University of Alabama at Birmingham (2007), an M.S. from the University of Houston (2002), and a B.S. from National Chiao-Tung University, Taiwan (2000). His research focuses on software engineering, meta-heuristics, evolutionary algorithms, and service-oriented architectures. Dr. Liu leads the Cloud Agility Lab and has published over 30 articles with 3,000+ citations. He serves on the editorial board of Applied Soft Computing (impact factor 7.2) and has mentored over 30 student projects. His work explores algorithmic optimization, QoS-driven systems, and domain-specific languages implementation through service-oriented technologies. Education: Ph.D., Computer Science, University of Alabama at Birmingham, 2007 M.S., Computer Science, University of Houston, 2002 B.S., Computer Science, National Chiao-Tung University, 2000 Research emphasizes balancing exploration/exploitation in evolutionary algorithms, improving compiler generation for DSLs, and addressing challenges in swarm intelligence. Recent work critiques algorithm stopping criteria and proposes memory-assisted optimization techniques. His articles address topics like MIoT applications, artificial bee colony parameter tuning, and QoS-aware service composition. Grant and advising activities remain centralized through student project supervision, with no specific grants mentioned in the text. The Cloud Agility Lab focuses on advancing cloud computing and software agility in distributed systems.

Pelin Dursun ÇebiView profile

Professor

• Architectural Design
• Architecture
• Theory in Urban Planning and Design
• +6 more

Prof. Dr. Pelin Dursun Çebi is a Professor at the Department of Architecture, Faculty of Architecture, Istanbul Technical University. She holds a PhD in Building Science from the same university. Her research focuses on architectural design, theory in urban planning, critical analysis of spatial narratives, and design methodology. She has led significant projects such as the 'Mekan Dizimi Tasarım Uygulaması' and contributed to studies on urban breccia and spatial syntax. Her work bridges architectural practice with theoretical frameworks, emphasizing the interplay between body, space, and technology. Education: PhD in Building Science (Istanbul Technical University, 2002), MSc in Building Science (1996), BSc in Architecture (1993). Research Interests: Urban spatial analysis, architectural representation, digital tools in design, bodily experience in urban spaces, and gender studies in academia. Her recent articles explore urban breccia, memory-centred space analysis, and virtual architectural representations. She has supervised over 30 graduate theses, focusing on topics like urban narratives, spatial syntax, and critical design practices. Her projects include developing dynamic design tools (e.g., SpaceChase) and investigating gender dynamics in higher education. She contributes to editorial boards and international conferences, emphasizing interdisciplinary approaches in architecture and urban studies.