Dr. Giulia Biancon is an Assistant Professor Adjunct in the Department of Medical Oncology and Hematology at Yale School of Medicine. She holds a PhD from the University of Milan (2019) and is a member of the Halene Lab, focusing on RNA biology and hematologic malignancies. Her research combines high-throughput methodologies to study RNA mechanisms in diseases like myeloid leukemias and splicing factor mutations. Education: PhD in Molecular Biology from the University of Milan (2019). Research Interests: RNA splicing, stress granules in cancer, epitranscriptomics, clonal hematopoiesis, and the interplay between genetic mutations and cellular pathways in blood cancers. Awards: 2024 Eclipse Award, 2022 ASH Abstract Achievement Award, and 2022 RNA Society Best Poster Award. Her work has been published in journals like Cell Reports , Blood , and Molecular Cell . Labs/Teams: Principal member of the Halene Lab and coordinator at the Yale Center for RNA Science and Medicine. Collaborates with institutions like the SeroNet network for immunology studies.
Dr. Michael Mühlebach is a Lecturer at the Department of Information Technology and Electrical Engineering, ETH Zurich, and affiliated with the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He holds a Bachelor's (2010) and Master's (2013) from ETH Zurich, recognized with awards for academic excellence in Robotics, Systems, and Control. His research focuses on multibody dynamics, nonlinear system control, and model predictive control, with applications in robotics and aerospace systems. His work spans theoretical advancements in variational integrators and practical implementations in systems like the Cubli (a reaction wheel-based 3D inverted pendulum) and flying platforms for ducted fan actuation. Publications highlight contributions to model predictive control schemes with stability guarantees, nonlinear analysis, and distributed event-based state estimation. Key awards include the Outstanding D-MAVT Bachelor Award and Willi-Studer Prize. His research integrates control theory with real-world applications, emphasizing both foundational mathematics and engineering implementations. No grants or lab affiliations are explicitly listed in the provided text.
Mina Lee is an Assistant Professor in Computer Science at the University of Chicago, affiliated with the Data Science Institute and Cognitive Science. Her research focuses on 'Writing with AI,' exploring how AI transforms writing processes, content, and identities. She designs AI writing assistants and evaluates human-AI collaboration through user studies and experiments, addressing ethical implications like authorship norms and educational impacts. Education: Ph.D. in Computer Science from Stanford University (2023), advised by Percy Liang. B.S. in Computer Science from Korea University (2016). Postdoctoral research at Microsoft Research's Computational Social Science group (2023–2024). Research interests span Human-Computer Interaction (HCI), NLP, and computational social science. She co-founded workshops on Intelligent Writing Assistants and Human-centered Evaluation of Language Models. Notable awards include MIT Technology Review's Innovators Under 35 Korea (2022) and a Best Paper Award at GPCE 2016. Her work has been published in top venues like CHI, ACL, NeurIPS, and Nature Human Behavior. She advises PhD students on AI-assisted writing, cognitive augmentation, and safe generative models. Current lab projects include designing explainable AI tools and studying AI disclosure norms in writing.
Gail E. Kaiser is a Professor of Computer Science and the Director of the Programming Systems Laboratory (PSL) in the Computer Science Department at Columbia University. She has been with Columbia University since 1985, becoming a full Professor in 1998. Prof. Kaiser's research spans software engineering, program analysis, software testing, and software security, with recent focus on addressing challenges in AI/ML systems testing and security. Prof. Kaiser received her PhD in Computer Science from Carnegie Mellon University in 1985 and her ScB in Computer Science and Engineering from MIT in 1979. Her dissertation at CMU was titled "Semantics for Structure Editing Environments" under advisor Nico Habermann, and at MIT she completed "Automatic Extension of an Augmented Transition Network Grammar for Morse Code Conversations" under advisor Al Vezza. Prof. Kaiser's research interests primarily focus on software engineering following a systems building approach, with recent emphasis on static and dynamic program analysis techniques to improve software reliability and security. Since 2005, she has investigated testing "non-testable" programs, particularly in machine learning, data mining, and scientific computing applications where traditional testing oracles are insufficient. She has developed novel techniques and tools for detecting bugs and verifying repairs in complex systems. Concurrently, she has worked on collaboration environments for computational scientists, creating knowledge sharing and domain-aware environments to support scientific workflows. Prof. Kaiser's recent publications demonstrate a strong focus on the intersection of software engineering and artificial intelligence. Her work addresses critical challenges in testing AI systems, code understanding through deep learning, vulnerability detection, and educational tools for computational thinking. There's a clear evolution from traditional software engineering topics toward AI/ML applications, with particular emphasis on metamorphic testing for non-testable systems, code similarity analysis, and educational applications. Prof. Kaiser has received numerous prestigious awards throughout her career: Distinguished Journal Award (10 Years) from 18th IEEE International Conference on Software Testing, Verification and Validation (ICST), April 2025 Best Research Paper Award at 24th IEEE International Conference on Source Code Analysis & Manipulation (SCAM), October 2024 Distinguished Reviewer Awards for ASE 2024 and FSE 2024 ACM SIGSOFT Distinguished Paper Award for "CONCORD: Clone-aware Contrastive Learning for Source Code", July 2023 Best Student Paper Award at ICCE 2021 Multiple ACM SIGSOFT Distinguished Paper Awards dating back to 2014 Presidential Young Investigator in Software Engineering and Software Systems from NSF (1988-1993) Prof. Kaiser has chaired Columbia's doctoral program since 1997 and served on editorial boards including IEEE Internet Computing and as a founding associate editor of ACM Transactions on Software Engineering and Methodology. Her lab has been continuously funded by major agencies including NSF, NIH, DARPA, ONR, NASA, and numerous companies. Current grants include significant NSF funding for secure containers architecture, learning semantics of code for software assurance, and finding semantic security bugs. As Director of the Programming Systems Laboratory (PSL), Prof. Kaiser leads research in software systems, program analysis, and software testing. The lab has developed numerous tools and techniques for software reliability and security, with recent focus on challenges in AI/ML systems. Her work bridges theoretical foundations with practical applications, often resulting in deployable tools that address real-world software engineering challenges.
Dr. Winnie Yip is a Professor of the Practice of Global Health Policy and Economics at the Harvard T.H. Chan School of Public Health. She serves as Faculty Director of the China Health Partnership and recently concluded her role as Acting Director at Harvard's Fairbank Center for Chinese Studies. Previously, she was a Professor at the University of Oxford and led the Global Health Policy Program. She holds a PhD in Economics from MIT and a BA from UC Berkeley. Her research focuses on systemic healthcare interventions, policy design, and aging populations' impact on health systems. She collaborates closely with governments and international agencies like the World Bank and WHO, advising on reforms in Asia. Her work emphasizes equitable access, health system efficiency, and innovative eldercare solutions. Dr. Yip’s academic leadership includes roles as past President of the International Health Economics Association and editorial positions at journals like Social Science & Medicine . Her grants include funding from NSF, Bill & Melinda Gates Foundation, and EU Commission. Key areas of study include telemedicine, long-term care financing, and healthcare delivery in low-income regions.
Kevin Manaugh is an Associate Professor at McGill University, specializing in Urban Planning with a focus on sustainable transportation and spatial justice. His research examines how decision-making processes in urban development balance environmental, economic, and social equity goals, particularly through transport systems. He holds a PhD in Urban Planning from McGill University (2013). His key research interests include integrating social equity into land use policies, analyzing accessibility impacts on socioeconomically diverse populations, and studying behavior change related to sustainable transportation. Current projects explore equitable transit accessibility, responses to local mobility policies, and health/well-being effects of sustainable transport choices. Manaugh has published extensively on transportation equity, urban form analysis, and GIS applications. His work bridges theoretical frameworks with practical policy implementation, emphasizing participatory approaches to urban planning. Notable contributions include studies on pandemic street reallocation equity and cycling infrastructure prioritization strategies. His research has been supported by interdisciplinary collaborations and applied to Canadian urban contexts. Despite prolific output, Manaugh maintains an active engagement with public discourse on urban mobility challenges and equitable urban futures.
Samir Dani is a Professor of Operations and Supply Chain Management at Keele University’s Keele Business School. He holds Chartered Manager status and is a Fellow of multiple professional bodies, including the Higher Education Academy and Chartered Institute of Logistics and Transport. Prior to academia, he worked in India’s automotive industry. His research focuses on supply chain resilience, sustainability, food logistics, and Industry 4.0 technologies like AI and Blockchain. Affiliations: Keele University (current), University of Huddersfield (2014–2019), Loughborough University (2005–2008) Leadership: Former Head of Logistics, Marketing, Hospitality, and Analytics Department at University of Huddersfield Industry Engagement: £5M Leeds City Region LEP Supply Chain Program, UK-India trade advisory roles Research Interests: Supply chain risk and resilience Food supply chain sustainability AI, IoT, and Blockchain applications Industry 4.0 transformations Recent Article Trends: Focus on climate action impacts, blockchain trust mechanisms, and SME net-zero strategies. His work bridges academic theory with industry challenges, emphasizing technology adoption and sustainability. Awards: Prix des Associations (2015), UK Top 100 Logistics Professional (2017/18) Grants: £800K+ from EPSRC, IMCRC, and KTP Advisory Roles: Editorial Board member of Supply Chain Management: An International Journal, Academic Review Board member of International Journal of Operations and Production Management.
Changxi Zheng is an Associate Professor in the Department of Computer Science at Columbia University's School of Engineering and Applied Science (SEAS). He directs Columbia's Computer Graphics Group (C2G2) within the Columbia Vision and Graphics Center (CVGC). After receiving his PhD from Cornell University, he joined the faculty of Computer Science Department at Columbia, where he has established himself as a leading researcher in computer graphics and scientific computing. Dr. Zheng's research spans multiple areas of applied computer science with a particular focus on computer graphics and scientific computing. His work centers around developing numerical models for simulating physical phenomena involving complex motions such as fluids, bubbles, and thin rods, along with their resulting acoustic waves. Leveraging computational insights from these models, he devises methods for improving tangible object creation, enabling novel human-computer interactions, and developing software tools for acoustic and photonic devices. His research has attracted significant public interest and media coverage, including projects like FontCode, AirCode, and Computational Metallophone Design. His recent publications reveal a strong interdisciplinary approach, bridging computer graphics, physics simulation, machine learning, and hardware design. His work demonstrates consistent innovation in computational methods for simulating physical phenomena and applying these techniques to practical problems in 3D printing, acoustic modeling, and interactive systems. The breadth of his research spans from fundamental physics-based simulations to practical applications in industry. Columbia SEAS Dean's Fellow (for advised students) NSF Graduate Research Fellow (for Ruilin Xu) Snap Research Fellow (for Rundi Wu) CKGSB Fellow (for Yun Fei) Adobe Research Fellow (for Gabriel Cirio) Marie Sklodowska-Curie Individual Fellow (for Rundi Wu) Best Paper Award at ACM International Conference on Multimedia (ACMMM), 2019 Dr. Zheng actively mentors a diverse group of students, including current PhD candidates and postdoctoral researchers. His research group has received support from various sources that enable their innovative work in computational graphics and physics-based simulation. He has supervised numerous successful students who have gone on to positions at leading technology companies including Adobe, Tencent, Facebook, and academic institutions. As director of Columbia's Computer Graphics Group (C2G2) within the Columbia Vision and Graphics Center (CVGC), Dr. Zheng leads a vibrant research team focused on advancing the state of the art in computer graphics, physics-based simulation, and their applications. The group maintains strong collaborations with industry partners and academic institutions worldwide, fostering an environment of innovation and practical application of theoretical concepts.
Christopher J. Palmer is an Associate Professor of Finance at the MIT Sloan School of Management, specializing in financial decision-making, credit markets, and policy interventions. His research focuses on how individuals and institutions respond to economic upheavals in areas like bankruptcy, retirement savings, and real estate. He holds a PhD in Economics from MIT and a BA in Economics and Mathematics from Brigham Young University. Palmer’s work has been published in top journals such as the American Economic Review , Journal of Finance , and Review of Financial Studies . He explores topics including racial disparities in bankruptcy outcomes, consumer payment behavior, and the effects of quantitative easing. His research is supported by affiliations with the National Bureau of Economic Research (NBER) and the Jameel Poverty Action Lab (J-PAL). Key honors include the 2022 Jamieson Prize and the 2019 Society for Financial Studies Best Paper Award. Palmer has contributed to public debates on policy issues like rent control and retirement savings through media outlets such as The New York Times , Bloomberg , and Vox .
Jenna Wiens is an Associate Professor of Computer Science and Engineering at the University of Michigan's College of Engineering. She serves as Associate Director of the Artificial Intelligence Lab and co-Director of AI & Digital Health Innovation. Leading the MLD3 research group, her work focuses on machine learning and AI applications for healthcare data. PhD from MIT (2014) under John Guttag NSF CAREER Award recipient (2016) Humboldt Foundation Carl Friedrich von Siemens Award (2024) Her research addresses four key technical thrusts: Time-series analysis for predicting clinical outcomes Robust machine learning against spurious correlations Decision-making with causal inference and offline reinforcement learning Human-AI collaboration frameworks Notable methodological contributions include the FIDDLE preprocessing pipeline for clinical time-series data, foundational work on survival analysis, and novel approaches to model selection in healthcare reinforcement learning. Her work has led to real-world AI deployments in infection prevention and patient risk stratification. Scientific honors include: Forbes 30 Under 30 (2015) MIT Tech Review 35 Innovators Under 35 (2017) Sloan Research Fellowship in Computer Science (2020) Sarah Goddard Power Award (2023) Wiens collaborates with clinicians across disciplines, emphasizing clinician-in-the-loop AI systems and ethical implementation in healthcare workflows.
Dr Andrew Rhead is a Senior Lecturer in the Department of Mechanical Engineering at the University of Bath, specializing in aerospace composites and damage tolerance analysis. His research focuses on impact damage detection, failure mechanism modeling, and Non-Destructive Evaluation (NDE) techniques for composite structures. MSci in Mathematical Sciences (Dynamical Systems) - University of Bristol (2006) PhD in Composite Damage Tolerance - University of Bath (2009) His work develops computationally efficient analytical models for compression after impact (CAI) strength prediction in composite laminates, surpassing traditional finite element methods. Key projects include hydrogen storage systems for aircraft, cryogenic composite testing, and steered fiber manufacturing optimization. Active in 10 projects including ASPIRE and HyFIVE Collaborates with Airbus, GKN Aerospace, and EPSRC Research trends show emphasis on sustainable aviation materials, structural battery integration, and advanced testing methodologies. Current affiliations include the Institute for Mathematical Innovation (IMI) and Centre for Integrated Materials, Processes & Structures (IMPS).
Andrea Modena is a Lecturer at Ca' Foscari University of Venice and a postdoc researcher at the University of Mannheim , Department of Economics. He is affiliated with the Bonn-Mannheim Center for Collaborative Research (CRC TR 224, Group C03) and the Leibniz Institute for Financial Research SAFE . His research bridges macroeconomic theory and financial economics, focusing on macro-finance dynamics and financial intermediation efficiency. Modena’s scholarly work explores the interplay between financial sectors and macroeconomic stability. His publications analyze business cycle fluctuations, risk pooling mechanisms, and leverage dynamics in financial intermediaries. While no formal awards are listed, his active participation in prestigious research groups (e.g., with Pietro Dindo and Loriana Pelizzon) underscores his contributions to economic theory. He holds a PhD in Economics from Ca' Foscari University of Venice (2020) and maintains dual academic roles, balancing research at Mannheim with teaching and affiliations at Ca' Foscari and Bonn. His expertise spans modeling macro-financial linkages, policy implications for financial sectors, and quantitative economic dynamics.
Michael O'Boyle is a Professor at the University of Edinburgh's School of Informatics, where he serves as Director of the ARM Research Centre of Excellence and the EPSRC Centre for Doctoral Training in Pervasive Parallelism. Holding an EPSRC Established Career Research Fellowship, he leads pioneering work in compiler technology for heterogeneous architectures, bridging theoretical advances with practical high-performance computing applications. Professor O'Boyle's research spans multiple cutting-edge areas including heterogeneous code discovery and optimization, neural machine translation for program synthesis, deep neural network system stack optimization, software-defined hardware, and compiler/architecture co-design. His approach integrates constraint analysis, program synthesis, and machine learning to address complex challenges in high-performance computing across diverse hardware platforms. His recent publications reveal a strong trend toward integrating machine learning with traditional compiler techniques, particularly in neural program synthesis, tensor optimization, and architecture-aware compilation. This work represents a paradigm shift in compiler design, moving from rule-based systems to learning-based approaches that can automatically adapt to diverse hardware targets. IEEE/ACM CGO 2025 Distinguished Paper Award for 'Tensorize: Fast Synthesis of Tensor Programs from Legacy Code' IEEE/ACM CGO 2024 Test of Time Award ACM GPCE 2023 Best Paper Award for 'C2TACO: Lifting Tensor Code to TACOM' ACM ASPLOS 2021 Distinguished Paper Award IEEE HPCA 2021 Best Paper Award for 'Prodigy: Improving the Memory Latency of Data-Indirect Irregular Workloads' Professor O'Boyle has successfully mentored numerous PhD students who have secured prominent positions in academia (including at Cambridge, Edinburgh, Leeds, and McGill) and industry (including Meta, NVIDIA, Qualcomm, Huawei, and Microsoft). His research is supported by significant funding from EPSRC, ARM, and European projects including Bonseyes and Transmuter, demonstrating strong international recognition and industry impact. He leads the influential Compiler and Architecture Design (CArD) Group at the University of Edinburgh and is a founder of the HiPEAC Network of Excellence, which has grown into a major European initiative connecting researchers and practitioners in high-performance and embedded computing.
Dr Mobarak Hoque serves as a Senior Lecturer in the Division of Informatics, Imaging and Data Sciences, School of Health Sciences, University of Manchester. He concurrently holds an external position as Honorary Senior Research Fellow at University College London (UCL) from July 2025 to June 2028. Academic Background: Doctor of Philosophy in Representation Learning in Multimodal Spatiotemporal Image-Guided Medical Procedures, National University of Singapore (NUS), awarded 2019 Research Expertise: Dr Hoque's work centers on Biomedical Data Science and Artificial Intelligence with specialization in Multimodal Large Language Models , Vision-Language Models , and Safe and Responsible AI . His research directly addresses UN Sustainable Development Goal 3 (Good Health and Well-being) through innovations in surgical robotics, medical imaging, and endoscopic procedures including polyp segmentation and low-light enhancement. Publication Trends: Recent publications (2023-2025) reveal a cohesive research trajectory focused on robust AI for surgical applications. Key methodologies include adversarial feature disentanglement, semi-supervised learning frameworks, and multimodal integration of vision-language models. His work consistently targets real-world clinical challenges like instrument segmentation, surgical workflow recognition, and low-light endoscopy enhancement using advanced techniques such as wavelet attention and diffusion models. Academic Supervision: Dr Hoque actively mentors PhD candidates in Biomedical Data Science and AI, particularly welcoming students interested in multimodal learning and responsible AI deployment for healthcare applications.
Albert Presto is a Research Professor in the Department of Mechanical Engineering at Carnegie Mellon University with a courtesy appointment in Civil and Environmental Engineering. He serves as Director of the Center for Atmospheric Particle Studies (CAPS) and is a Faculty Affiliate at the Steinbrenner Institute for Environmental Education and Research. His work spans multiple interdisciplinary collaborations across environmental science, engineering, and public health domains. Department of Mechanical Engineering, College of Engineering Center for Atmospheric Particle Studies (CAPS) Steinbrenner Institute for Environmental Education and Research Africa Clean Air Network Advisory Council Health Effect Institute's Energy Review Committee Presto's research focuses on pollutant emissions from energy extraction and consumption and their subsequent atmospheric transformations. His work examines how gas and oil wells emit methane, how vehicles emit carbon monoxide and particulate matter, and how these pollutants undergo oxidation in the atmosphere to create secondary pollutants like ozone and secondary particulate matter. His approach combines ambient measurements, laboratory experiments, source testing of pollution sources, and atmospheric models to provide a holistic view of pollutant emissions and transformations. His recent publications reveal a strong emphasis on air quality monitoring technologies, particularly low-cost sensor networks deployed internationally. There's a clear trend toward studying air pollution in African cities (especially Nairobi, Kampala, and Addis Ababa), examining spatial and temporal variability of particulate matter, and investigating the health impacts of air pollution exposure. His work increasingly integrates machine learning approaches for pollution forecasting and leverages international collaborations to address global air quality challenges. Member of Africa Clean Air Network Advisory Council Collaborator with US embassies worldwide on air quality data collection Quoted in The Guardian on inequality of air pollution exposure, specifically noting how people of color are more likely to be exposed to harmful air pollution Collaborated on research regarding chemicals released during the Ohio train derailment Presto actively collaborates with medical professionals to develop neighborhood-by-neighborhood studies of pollutant exposure and to understand relationships between emissions and health effects like childhood asthma. His work includes investigating racial-ethnic exposure disparities to airborne pollutants and examining how proximity to pollution sources like fast-food restaurants affects pediatric asthma outcomes. He has received seed funding from the Scott Institute for Energy Innovation for research in clean hydrogen production, AI hardware efficiency, and decarbonizing transportation. As Director of CAPS, Presto leads a research team focused on atmospheric particle studies with applications ranging from local Pittsburgh air quality to global monitoring initiatives. His lab develops and deploys advanced air quality monitoring technologies, including low-cost sensor networks that have been implemented in multiple cities across Africa. The CAPS research group works at the intersection of environmental engineering, atmospheric science, and public health to address critical air quality challenges worldwide.
