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Publications
EnsembleCI: Ensemble Learning for Carbon Intensity Forecasting
Leyi Yan, Linda Wang, Sihang Liu, Yi Ding
e-Energy'25: The 16th ACM International Conference on Future and Sustainable Energy Systems
Predicting and Understanding College Student Mental Health with Interpretable Machine Learning
Meghna Roy Chowdhury, Wei Xuan, Shreyas Sen, Yixue Zhao, Yi Ding
CHASE'25: IEEE/ACM conference on Connected Health: Applications, Systems and Engineering Technologies
Unlocking Mental Health: Exploring College Students' Well-being through Smartphone Behaviors
Wei Xuan, Meghna Roy Chowdhury, Yi Ding, Yixue Zhao
MOBILESoft'25: IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems
Sustainable LLM Serving: Environmental Implications, Challenges, and Opportunities
Yi Ding, Tianyao Shi
IGSC'24: The 15th International Green and Sustainable Computing Conference (Invited Paper)
Uncertainty-Aware Decarbonization for Datacenters [Slides]
Amy Li, Sihang Liu, Yi Ding
HotCarbon'24: Workshop on Sustainable Computer Systems
EIR'24: ACM SIGENERGY Energy Informatics Review (EIR)
Towards Sustainable Large Language Model Serving [Slides]
Sophia Nguyen*, Beihao Zhou*, Yi Ding, Sihang Liu (*Equal Contributions)
HotCarbon'24: Workshop on Sustainable Computer Systems
EIR'24: ACM SIGENERGY Energy Informatics Review (EIR)
Turaco: Complexity-Guided Data Sampling for Training Neural Surrogates of Programs
Alex Renda, Yi Ding, Michael Carbin
OOPSLA'23: The ACM SIGPLAN conference on Systems, Programming, Languages, and Applications
CAFQA: A Classical Simulation Bootstrap for Variational Quantum Algorithms
Gokul Ravi, Pranav Gokhale, Yi Ding, William Kirby, Kaitlin Smith, Peter Love, Kenneth Brown, Henry Hoffmann, Frederic Chong
ASPLOS'23: The 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems
2023 Innovation Award, Quantum Computing for Drug Discovery Challenge at ICCAD
Minimax Designs for Causal Effects in Temporal Experiments with Treatment Habituation [arXiv]
Guillaume Basse, Yi Ding, Panos Toulis
Biometrika'23 (A Top Statistics Journal)
NURD : Negative-Unlabeled Learning for Online Datacenter Straggler Prediction [Slides]
Yi Ding, Avinash Rao, Hyebin Song, Rebecca Willett, Henry Hoffmann
MLSys'22: The 5th Conference on Machine Learning and Systems
Programming with Neural Surrogates of Programs [Video] [Code]
Alex Renda, Yi Ding, Michael Carbin
Onward!'21: The ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software
Generalizable and Interpretable Learning for Configuration Extrapolation [Video]
Yi Ding, Ahsan Pervaiz, Michael Carbin, Henry Hoffmann
ESEC/FSE'21: The 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
Neighborhood Street Activity and Greenspace Usage Uniquely Contribute to Predicting Crime [Media]
Kathryn E Schertz, James Saxon, Carlos Cardenas-Iniguez, Luís MA Bettencourt, Yi Ding, Henry Hoffmann, Marc G Berman
npj Urban Sustainability, Nature Research Journal, 2021
A Polynomial-time Algorithm for Learning Nonparametric Causal Graphs [arXiv] [Poster] [Code]
Ming Gao, Yi Ding, Bryon Aragam
NeurIPS'20: The 34th Conference on Neural Information Processing Systems
Dynamical Systems Theory for Causal Inference with Application to Synthetic Control Methods [Video]
Yi Ding, Panos Toulis
AISTATS'20: The 23rd International Conference on Artificial Intelligence and Statistics
Generative and Multi–phase Learning for Computer Systems Optimization [Slides] [Lightning Talk] [Poster]
Yi Ding, Nikita Mishra, Henry Hoffmann
ISCA'19: The 46th International Symposium on Computer Architecture
Multiresolution Kernel Approximation for Gaussian Process Regression [arXiv] [Spotlight Video] [Poster]
Yi Ding, Risi Kondor, Jonathan Eskreis-Winkler
NeurIPS'17 (Spotlight): The 31st Conference on Neural Information Processing Systems
Large Scale Kernel Methods for Online AUC Maximization
Yi Ding, Chenghao Liu, Peilin Zhao, Steven CH Hoi
ICDM'17 (Long Oral): The IEEE International Conference on Data Mining
An Adaptive Gradient Method for Online AUC Maximization
Yi Ding, Peilin Zhao, Steven CH Hoi, Yew-Soon Ong
AAAI'15 (Oral): The 29th AAAI Conference on Artificial Intelligence
Learning Relative Similarity by Stochastic Dual Coordinate Ascent
Pengcheng Wu, Yi Ding, Peilin Zhao, Chunyan Miao, Steven CH Hoi
AAAI'14: The 28th AAAI Conference on Artificial Intelligence
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