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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
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Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 1
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portfolio
Portfolio item number 1
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Portfolio item number 2
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publications
Gene hunting with knockoffs for hidden Markov models
Published in Biometrika, 2019
Rejoinder: ‘Gene hunting with knockoffs for hidden Markov models’
Published in Biometrika, 2019
Deep Knockoffs
Published in Journal of the American Statistical Association, 2019
Multi-resolution localization of causal variants across the genome.
Published in Nature Communications, 2020
A comparison of some conformal quantile regression methods
Published in Stat, 2020
Causal inference in genetic trio studies
Published in Proc. Natl. Acad. Sci. U.S.A., 2020
Classification with valid and adaptive coverage
Published in Advances in Neural Information Processing Systems 33 (NeurIPS, spotlight presentation), 2020
Controlling the false discovery rate in GWAS with population structure
Published in Proc. Natl. Acad. Sci. U.S.A., 2020
Testing for Outliers with Conformal p-values
Published in Annals of Statistics (in press), 2021
Conformal Prediction using Conditional Histograms
Published in Advances in Neural Information Processing Systems 34 (NeurIPS, spotlight presentation), 2021
Searching for robust associations with a multi-environment knockoff filter
Published in Biometrika, 2021
Interpretable Classification of Bacterial Raman Spectra with Knockoff Wavelets
Published in IEEE Journal of Biomedical and Health Informatics, 2021
Transfer learning in genome-wide association studies with knockoffs
Published in Sankhya B, 2021
Hyperoxemia among Pediatric Intensive Care Unit Patients Receiving Oxygen Therapy
Published in Journal of Pediatric Intensive Care, 2021
Searching for local associations while controlling the false discovery rate
Published in pre-print, 2022
Long-term effect of liver resection on circulating stem cells expressing PD-L1 in patients with hepatocellular carcinoma–Pilot study
Published in Zeitschrift für Gastroenterologie, 2022
Long-term dynamics of circulating tumor cells and their prognostic relevance after liver resection in patients with hepatocellular carcinoma
Published in Zeitschrift für Gastroenterologie, 2022
Conformalized Frequency Estimation from Sketched Data
Published in Advances in Neural Information Processing Systems 35 (NeurIPS), 2022
Robotic-assisted esophagectomy leads to significant reduction in postoperative acute pain: A retrospective clinical trial
Published in Annals of Surgical Oncology, 2022
Training Uncertainty-Aware Classifiers with Conformalized Deep Learning
Published in Advances in Neural Information Processing Systems 35 (NeurIPS), 2022
Conformal inference is (almost) free for neural networks trained with early stopping
Published in Proceedings of the 40th International Conference on Machine Learning, 2023
Derandomized novelty detection with FDR control via conformal e-values
Published in Advances in Neural Information Processing Systems 36 (NeurIPS), 2023, 2023
Frequency and cardinality recovery from sketched data: a novel approach bridging Bayesian and frequentist views
Published in pre-print, 2023
Integrative conformal p-values for powerful out-of-distribution testing with labeled outliers
Published in Journal of the Royal Statistical Society: Series B, 2023
Conformal Frequency Estimation using Discrete Sketched Data with Coverage for Distinct Queries
Published in Journal of Machine Learning Research, 2023
Conformalized adaptive forecasting of heterogeneous trajectories
Published in Proceedings of the 41th International Conference on Machine Learning, 2024
Uncertainty in Language Models: Assessment through Rank-Calibration
Published in Conference on Empirical Methods in Natural Language Processing, 2024, 2024
Structured Conformal Inference for Matrix Completion with Applications to Group Recommender Systems
Published in pre-print, 2024
Conformal Classification with Equalized Coverage for Adaptively Selected Groups
Published in Advances in Neural Information Processing Systems 37 (NeurIPS), 2024, 2024
Random measure priors in Bayesian frequency recovery from sketches
Published in Journal of Machine Learning Research (2024), 2024
Collective Outlier Detection and Enumeration with Conformalized Closed Testing
Published in pre-print, 2024
Adaptive conformal classification with noisy labels
Published in Journal of the Royal Statistical Society: Series B, 2024
Doubly Robust Conformalized Survival Analysis with Right-Censored Data
Published in pre-print, 2024
talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Stats 195, Introduction to R
Undergraduate course, Stanford University, 2018
Stats 390, Consulting Workshop
Graduate course, Stanford University, 2018
Stats 195, Introduction to R
Undergraduate course, Stanford University, 2020
Course page: http://web.stanford.edu/~msesia/stats195/
BUAD 310, Applied Business Statistics
Undergraduate course, University of Southern California, 2020
BUAD 310, Applied Business Statistics
Undergraduate course, University of Southern California, 2021
Misc tutorials for graduate students
Misc Tutorials, University of Southern California, 2022
GSBA 506b, Applied Managerial Statistics
Graduate course, University of Southern California, 2023
Enrolled students can find all course information in the relevant USC Blackboard page.
Predictive uncertainty in ML with conformal inference
Graduate course, University of Torino and Collegio Carlo Alberto, 2023
This is a short but intensive course on cutting-edge distribution-free methods for predictive inference using complex machine learning algorithms. This course will cover both the theory and practice of distribution-free predictive inference. Computer-based sessions will focus on hand-on implementations of the described methods using the Python programming language (students will be assumed to have some familiarity with Python), and on applications to real data.
GSBA 524, Data Science for Business
Graduate course, University of Southern California, 2024
Enrolled students can find all course information in the relevant USC Blackboard page.
DSO 522, Applied Time Series Analysis for Forecasting
Graduate course, University of Southern California, 2024
Enrolled students can find all course information in the relevant USC Brightspace page.
GSBA 524, Data Science for Business
Graduate course, University of Southern California, 2025
Enrolled students can find all course information in the relevant USC Brightspace page.