Dr. Andrew Blake is a Lecturer in Experimental Neutrino Physics at the Department of Physics, Lancaster University. His research focuses on experimental neutrino physics, particularly neutrino event reconstruction and oscillation analysis using Liquid Argon Time Projection Chamber (LAr-TPC) technology. He collaborates on major international experiments including MINOS, MicroBooNE, SBND, and the future DUNE project at Fermilab. His primary research interests include: Precision measurements of neutrino oscillations Development of LAr-TPC detection technology Search for new physics beyond the Standard Model Neutrino interaction cross-section measurements CP symmetry violation in the neutrino sector Blake's recent publications (2025) demonstrate strong focus on: Advanced neutrino interaction measurements using MicroBooNE data Development of reconstruction algorithms for LAr-TPCs DUNE experiment capabilities for supernova detection and CP violation studies Validation methods for neutrino-nucleus interaction models He currently advises three PhD students: Krittika Adhikari (Experimental Particle Physics) Rachel Coackley (Experimental Particle Physics) Bethany McCusker (Experimental Particle Physics)
Seth Frey is an Associate Professor in the Department of Communication at the University of California, Davis, with affiliate status at Indiana University's Ostrom Workshop and as Research Director at Metagov. His research focuses on computational social science approaches to understanding self-governance in complex social systems, particularly through the lens of online communities as model institutions. Education: Ph.D. in Cognitive Science and Informatics (complex systems), Indiana University, 2013 B.A. in Cognitive Science, UC Berkeley, 2004 Research Interests: Frey specializes in computational approaches to institutional analysis and the cognitive science of strategic behavior . His work examines how communities design governance systems to overcome collective action problems, with emphasis on: Emergent institutional structures in digital commons Policy-as-data through NLP and institutional grammar frameworks Cognitive mechanisms underlying cooperative behavior Design principles for participatory change in online platforms His methodology integrates large-scale data analysis, web-based experiments, and computational modeling across diverse contexts including Minecraft, Reddit, and professional sports ecosystems. Publication Trends: Recent publications (2023-2025) demonstrate a cohesive trajectory toward computational institutional analysis, with increasing focus on NLP-driven policy analysis (e.g., NLP4Gov), decentralized governance architectures (DAOs, multi-level platform governance), and the cognitive foundations of collective action. His work consistently bridges theoretical institutional analysis with practical applications in digital community design, showing particular growth in translating Ostrom's design principles into computational frameworks. Awards: Honorable Mention Award for Best Paper at ACM CSCW 2019 Advising and Grants: Frey mentors students interested in data science applications at the intersection of communication, cognition, and complex systems, emphasizing resourcefulness and intellectual curiosity. His research has secured substantial funding from: National Science Foundation (NSF) NASA Ford Foundation Google Open Source Foundation He actively encourages aspiring graduate students with strong self-directed research skills to explore computational approaches to social phenomena. Labs and Teams: He leads the Computational Communication Lab at UC Davis and co-directs the Institutional Grammar Research Initiative. Through Metagov, he develops the 'Governance API' framework for modular community governance. His past affiliations include Disney Research (Walt Disney Imagineering) where he applied complexity science to theme park systems, and the New England Complex Systems Institute (NECSI). Current collaborations span Ethereum governance, Minecraft server ecosystems, and Colorado's cannabis monitoring infrastructure.
Audrey Bowden is an Associate Professor at Vanderbilt University in both the Department of Biomedical Engineering and Department of Electrical and Computer Engineering . She is also the Dorothy J Wingfield Phillips Chancellor Faculty Fellow . Education: PhD in Biomedical Engineering (2007) from Duke University BSE in Electrical Engineering (2001) from Princeton University Research Interests: Bowden's work focuses on biomedical optics and point-of-care diagnostics , with a strong emphasis on addressing healthcare disparities through low-cost technologies. Key areas include: Biomedical Imaging Biophotonics Image Processing Machine Learning in Medical Imaging Optical Coherence Tomography (OCT) Functional Near-Infrared Spectroscopy (fNIRS) Publication Trends: Recent work combines machine learning with endoscopic imaging to differentiate cancer from inflammation, develops low-cost OCT systems for smartphones, and improves fNIRS accessibility for diverse patient populations. Her lab also focuses on 3D reconstruction algorithms for urological applications and specular reflection removal in endoscopic videos. Lab & Clinical Collaborations: The Bowden Biomedical Optics Laboratory (BBOL) collaborates with clinical departments including urology , dermatology , otolaryngology , and women's health . The lab integrates optics , microfluidics , and computer science to create hardware/software tools for resource-constrained environments.
Talia Ringer is an Assistant Professor in the Department of Computer Science at the University of Illinois, where she is a member of the PL/FM/SE (Programming Languages/Formal Methods/Software Engineering) research group. She leads the Illinois Theorem Provers (ITP) lab, which focuses on advancing proof engineering technologies to make formal verification accessible to programmers of all skill levels across all domains. Research Interests Dr. Ringer's research spans multiple aspects of proof engineering with a strong focus on integrating techniques from dependent type theory, program transformations, and neural proof synthesis to solve real-world verification challenges. Her work addresses how to build systems that allow programmers to prove the absence of costly or dangerous bugs in software. She is particularly interested in proof repair, machine learning for proofs, and developing new methodologies that can drive the creation of large, secure, and robust verified software and hardware systems. Research Trends Dr. Ringer's recent publications demonstrate a strong shift toward integrating machine learning with formal verification, particularly in proof repair and synthesis. Her work explores how large language models can assist with theorem proving, how reinforcement learning can automate verification processes, and how to make proof engineering more practical for real humans. Many publications involve collaborations with students and researchers from multiple institutions, reflecting her commitment to interdisciplinary research. Awards and Recognition Distinguished Paper Award at ESEC/FSE 2023 for "Baldur: Whole-Proof Generation and Repair with Large Language Models" ACM SIGPLAN Distinguished Service Award in 2023 Mentoring and Service Dr. Ringer is a dedicated mentor who has advised numerous undergraduate and graduate students. She is the founder and president of the Computing Connections Fellowship, which provides transitional funding for computer science PhD students needing to escape unhealthy environments. She is also the founder and previous chair of the SIGPLAN Long-Term Mentoring Committee (SIGPLAN-M), which connects more than 200 mentors and 300 mentees across more than 44 countries. Her service work was formally recognized with the 2023 ACM SIGPLAN Distinguished Service Award. Laboratory and Collaborations Dr. Ringer leads the Illinois Theorem Provers (ITP) lab with current members including postdocs, PhD students, masters students, and undergraduates. She collaborates extensively with researchers at the University of Washington, UMass Amherst, Google Research, Galois, and other institutions on various proof engineering projects.
Sarah E. Stein is an Associate Professor and Deloitte Foundation Faculty Fellow in the Department of Accounting and Information Systems at Virginia Polytechnic Institute and State University (Virginia Tech). She serves as Director of the Ph.D. Program within the Pamplin College of Business. Her academic journey includes a Ph.D. from the University of Missouri, a B.S. and M.S. in Accounting from Truman State University, and CPA licensure in Colorado. Prior to academia, she worked as an audit manager at Deloitte in Denver. Education: Ph.D., University of Missouri; B.S. and M.S., Truman State University; CPA (Colorado) Roles: Deloitte Foundation Faculty Fellow, Director of Ph.D. Program Dr. Stein’s research focuses on auditor expertise, corporate governance, auditing networks, and financial reporting challenges. Her work has been published in top journals like The Accounting Review and Auditing: A Journal of Practice & Theory . She received the 2019 Best Paper Award in Issues in Accounting Education and the 2020 Innovation in Auditing Education Award for her data visualization audit case. Her recent articles (2023–2025) highlight themes such as audit committee responsibilities, CFO-audit partner dynamics, and small accounting firm strategies. Her teaching includes graduate auditing courses and PhD seminars. Research trends in her articles emphasize audit quality, governance evaluation, and emerging technologies in auditing. She actively contributes to professional standards through commentaries on PCAOB releases. Awards: 2019 Best Paper Award, 2020 Innovation Award, Deloitte Doctoral Fellowship Dr. Stein advises the Ph.D. program and collaborates with industry on audit innovation. Her lab focuses on auditing education and case development, reflecting her commitment to bridging academic research and practical application.
Professor Line Roald is a faculty member in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. Her research focuses on power system optimization, renewable energy integration, grid resilience, and wildfire risk mitigation using stochastic optimization and data-driven methods. Education : PhD (2016), MS (2012), BS (2009) from ETH Zurich Key Research Areas : Power Systems Optimization, Renewable Energy Integration, Wildfire Risk Mitigation, Stochastic Programming, Grid Decarbonization Her work addresses critical challenges in sustainable energy systems, including balancing grid efficiency and risk, optimizing electrolyzer scheduling for flexibility, and predicting cascading blackout severity using graph neural networks. She has developed frameworks for carbon intensity comparison and wildfire risk assessment in power systems. Scientific Awards : 2024 Inclusion, Equity and Diversity in Engineering Award 2024 Vilas Faculty Early Career Investigator Award 2023 IEEE Power Tech Best Student Paper Award 2021 NSF CAREER Award 2019 MTLE Fellow Professor Roald mentors graduate students and teaches courses including Introduction to Optimization and On-Line Control of Power Systems . Her publications highlight innovative approaches to grid security, carbon-efficient energy markets, and climate resilience in infrastructure systems.
Travis Desell is a Professor in the Department of Software Engineering at Rochester Institute of Technology (RIT), part of the B. Thomas Golisano College of Computing and Information Sciences. His research focuses on data science and machine learning applied to large-scale datasets using high-performance and distributed computing. He specializes in neuro-evolution, combining evolutionary algorithms with neural networks, particularly through his EXACT and EXAMM algorithms. He leads the D2S2 Lab and has developed the SALSA programming language based on the actor model. Currently funded projects include the National General Aviation Flight Information Database (NGAFID) and an NSF award exploring contextual bandits for decision-making in cyber-physical systems. His work emphasizes practical scientific applications, including stock forecasting, power plant data prediction, and explainable time series models. Education details are not explicitly provided, but his roles and publications indicate advanced academic credentials. Research interests span neuro-evolutionary techniques, recurrent neural networks, and distributed computing frameworks. Key projects include EXAMM for time series forecasting and NGAFID for flight safety analysis. Collaborations involve students and teams at RIT and beyond, with a focus on advancing AI-driven solutions in dynamic environments. Lab affiliations include the D2S2 Lab, where he mentors students and conducts cutting-edge research. Current opportunities exist for PhD students with backgrounds in software engineering and expertise in areas like NLP, web development, and distributed systems.
Dr. Zhibao Mian is a Lecturer in the School of Computer Science at the University of Hull, UK, and previously held an Associate Professor position at Northwest Normal University. He specializes in trustworthy AI, machine learning, and intelligent maintenance systems. His research integrates AI with IoT, blockchain, and digital twins in Industry 4.0/5.0 contexts. He leads projects on predictive maintenance for offshore wind turbines and AI-driven sustainable energy solutions. Dr. Mian holds a PhD from the University of Hull and an MSc from the University of Nottingham. Research interests include AI ethics, model-based safety analysis, and RCM. He has secured grants such as the CPHC-funded study on AI in software education and oversees multiple PhD scholarships. Notable roles include Editorial Board member of the American Journal of Artificial Intelligence and Reviewer for high-impact journals/conferences like JSS and IEEE. He is a Senior Fellow of the Higher Education Academy and received the Royal Academy of Engineering's 2024 Exceptional Talent designation. Recent publications (2023-2025) focus on ordinal networks, outlier detection, Belt and Road trade analysis, and carbon emissions modeling. He actively advises PhD students on topics like UAV-based anomaly detection and predictive maintenance frameworks.
Stefan Krastanov is an Assistant Professor at the University of Massachusetts Amherst, focusing on quantum hardware design, control, and optimization across multiple layers of quantum computing and networking technologies. His work bridges physical hardware descriptions with logical circuit compilation, emphasizing resilience in noisy quantum systems. Research Interests include Quantum Hardware Design, Entanglement-Based Networking, Quantum Error Correction, and Modeling Software for Quantum Systems. His primary lab is the Quantum Information Lab , with affiliations to the Advanced Classical and Quantum Information Research Lab. Recent work trends highlight advancements in quantum repeater networks, error-corrected compilation, and photonic neural networks. His publications span topics like non-Markovian dynamics simulation, NP-hard optimization in quantum dot arrays, and scalable spin quantum memory control. Labs and Teams: Quantum Information Lab (leading experimental/theoretical work) and collaborations through the Advanced Classical and Quantum Information Research Lab.
Professor Kurt Squire is a leading scholar in games research and development at the University of California Irvine, affiliated with the Donald Bren School of Information and Computer Sciences. He holds a Ph.D. in Education from Indiana University (2004). His work focuses on leveraging computer games and augmented reality to enhance learning outcomes and social impact. Squire has pioneered platforms enabling students and teachers to co-create educational tools, fostering global grassroots communities through collaborative game design. Notable contributions include the Games + Learning + Society (GLS) center, which he co-founded with Constance Steinkuehler and has since relaunched at UCI. He currently explores AR applications, community-based AI design, and mitigating right-wing extremism in gaming ecosystems. Squire’s research has been funded by NSF, NIH, and major foundations, with over a dozen commercially launched games stemming from his projects. Education: Ph.D. in Education, Indiana University, 2004 Research Interests: Squire investigates how games and emerging technologies can address societal challenges through participatory design. His work spans educational equity, cognitive development via casual gaming, and ethical AI frameworks. He emphasizes translating academic innovations into market-ready solutions while aligning with institutional goals. Recent projects include wearable apps for youth self-regulation and trauma-informed GenAI design with marginalized communities. Notable Achievements: Recipient of the Inaugural Hasso Plattner Endowed Chair in Artificial Intelligence (2025) Co-founder of GLS, a globally influential research hub Authored Making Games for Impact (2021), a practitioner-focused guide Labs/Teams: Directs the Games + Learning + Society center at UCI, focusing on XR research, well-being technologies, and entrepreneurship in education. Collaborates with MIT on augmented reality initiatives.
Sai Zhang is an Assistant Professor in the Department of Epidemiology at the University of Florida (UF), holding affiliations with the College of Public Health & Health Professions and College of Medicine. He is also an Affiliate Faculty in the J. Crayton Pruitt Family Department of Biomedical Engineering at the Herbert Wertheim College of Engineering. Previously, he was an Instructor at Stanford University School of Medicine and a Research Associate at the VA Palo Alto Epidemiology Research and Information Center (ERIC). Dr. Zhang completed his Ph.D. in Computer Science and Technology at Tsinghua University, followed by postdoctoral training in Dr. Michael Snyder’s lab at Stanford Genetics. His research integrates machine learning, genomics, and precision medicine to uncover genomic bases of complex diseases. Key focuses include developing algorithms for multiomic data analysis, modeling genotype-phenotype relationships, and leveraging deep learning for biological sequence analysis. His work emphasizes cell-type-specific mechanisms in diseases like ALS, coronary artery disease, and neurodegenerative disorders. Notable contributions include frameworks for polygenic risk scoring (e.g., PRS-Net), biomarker discovery for ALS, and tools for time-to-event prediction in neurological diseases. He leads the Zhang Laboratory, advancing computational systems for precision health applications.
Olga Goriunova is a Professor in the Department of Media Arts at Royal Holloway, University of London, and affiliated with the Humanities and Arts Research Institute. She holds a PhD in Digital Media from Aalto University and a philology degree from Lomonosov State University. Her research spans cultural theory, media philosophy, and AI ethics, focusing on how technology reshapes subjectivity and ecology. Research interests include digital art practices, data abstraction in AI, and the intersections of ecology with technical systems. Notable works include *Bleak Joys* (2019) and the upcoming *Ideal Subjects* (2025). She co-founded the journal *Computational Culture* and led projects like StoryFutures Academy funded by UKRI. Recent collaborations span global institutions including ANU and Leuphana University’s Digital Cultures Lab. She has served on AHRC peer review panels and edited volumes on software studies. Current roles include Director of Research for Media Arts and REF lead.
Felix Xiaozhu Lin serves as Associate Professor and William Wulf Faculty Fellow in the Department of Computer Science at the University of Virginia's School of Engineering and Applied Science, where he directs the Computer Science Ph.D. Program and MCS/MS Program. Previously a tenured Associate Professor at Purdue University's School of Electrical and Computer Engineering, Lin joined UVA Engineering in August 2020 after completing his doctoral research at Rice University. His educational credentials include: Ph.D. in Computer Science, Rice University (2014) M.S. in Computer Science, Tsinghua University (2008) B.S. in Automation, Tsinghua University (2006) Lin's research centers on systems software at the intersection of operating systems, compilers, and computer architecture, with emphasis on accelerating and safeguarding software systems. His current projects target on-device large language models and speech processing for low-cost hardware ( Analysis of his recent publications reveals a strong trajectory in edge computing and efficient AI systems. His research demonstrates increasing focus on hardware-software co-design for autonomous devices, with significant contributions in video analytics for energy-constrained cameras, kernel virtualization for heterogeneous architectures, and stream processing frameworks leveraging emerging memory technologies. The work consistently addresses real-world constraints like power limitations and network intermittency while maintaining rigorous academic standards. His scientific recognition includes: National Science Foundation CAREER Award (2019) Google Faculty Research Award (2016) NSF CISE Research Initiation Initiative Award (2015) ACM ASPLOS Best Paper Award (2014) Lin leads the XSEL research group mentoring graduate and undergraduate students in systems software development. His educational initiatives include CS4414/CS6456, a modern operating systems course featuring Arm64 baremetal kernel development, multicore systems, trusted execution environments, and filesystem forensics. The course's experiential approach has received strong student feedback for its modern content and practical relevance. His group actively recruits for projects spanning on-device AI, hardware-accelerated speech processing, and next-generation OS development. Based in Charlottesville, Virginia, Lin's research benefits from UVA's proximity to Shenandoah National Park and collaborative opportunities within the university's vibrant computing ecosystem, including the 2024 LLM Workshop he co-organized with Professor Yangfeng Ji.
David Wentzlaff is a Professor of Electrical and Computer Engineering at Princeton University, with associated faculty roles in Computer Science and the High Meadows Environmental Institute (HMEI). He leads research in computing architecture, green computing, and sustainable system design. As Director of Undergraduate Studies, he shapes educational programs in his field. Education: Ph.D., Electrical Engineering, MIT (2012) M.S., Electrical Engineering and Computer Science, MIT (2002) B.S., Electrical Engineering, University of Illinois at Urbana-Champaign (2000) Research Focus: Future Computing Systems: Designing manycore architectures, cloud computing infrastructure, and chiplet-based systems for exascale computing. Sustainability: Developing energy-efficient hardware, recyclable computing systems, and eco-friendly decommissioning strategies. Hardware-Software Co-Design: Exploring FPGA integration, in-memory computing, and parallel processing frameworks. Advising & Grants: Advises 8 current graduate students, focusing on topics like chiplet design, neural acceleration, and sustainable computing. Recipient of NSF grants for projects like OpenPiton (open-source manycore research platform) and CAREER awards for energy-efficient architectures. Labs & Collaborations: Leads the Wentzlaff Research Group at Princeton. Develops open-source frameworks like PRGA (FPGA prototyping) and OpenPiton (manycore processor).
Henrique O'Neill is an Associate Professor (with Habilitation) in the Department of Marketing, Operations and General Management at ISCTE - University Institute of Lisbon, Portugal. He is an Integrated Researcher at ISTAR-Iscte - Research Center in Information Sciences, Technologies and Architecture. His research focuses on information systems adoption, organizational strategy, and process optimization in healthcare, finance, and public administration. Education: PhD in Business Organization and Management - University of Cranfield (1995) Master's in Electrical and Computer Engineering - Higher Technical Institute (1987) Bachelor's in Electrical Engineering - Higher Technical Institute (1983) Research Interests: His work spans business/IT strategy, systems modeling, process analysis, and technology implementation. Key domains include healthcare informatics, banking systems, and Industry 4.0 applications. He emphasizes practical solutions for organizational performance through technology integration. Publication Trends: Recent articles explore intelligent business systems, telemedicine, design science methodologies, and supply chain innovation. His work consistently bridges theoretical frameworks with sector-specific applications in healthcare, education, and logistics. Professional Engagement: Member: Portuguese Telemedicine Association, Order of Engineers Commissioner: INEM (National Institute of Medical Emergency) reform study Director: Center for IT Development (2010-2014) Advising & Projects: Supervises 7 graduate students (1 PhD, 6 Master's). Leads EU-funded projects including: Atlantic Crossing (2024-2025): US-Portugal academic collaboration in AI/cybersecurity AAL4ALL (2011-2015): Ambient Assisted Living ecosystem UNITE (2000-2002): Ubiquitous teamwork platforms
