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Author Information
Cheng Zhang (Microsoft Research, Cambridge, UK)
Cheng Zhang is a principal researcher at Microsoft Research Cambridge, UK. She leads the Data Efficient Decision Making (Project Azua) team in Microsoft. Before joining Microsoft, she was with the statistical machine learning group of Disney Research Pittsburgh, located at Carnegie Mellon University. She received her Ph.D. from the KTH Royal Institute of Technology. She is interested in advancing machine learning methods, including variational inference, deep generative models, and sequential decision-making under uncertainty; and adapting machine learning to social impactful applications such as education and healthcare. She co-organized the Symposium on Advances in Approximate Bayesian Inference from 2017 to 2019.
Mihaela van der Schaar (University of Cambridge)
More from the Same Authors
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2022 : A Causal AI Suite for Decision-Making »
Emre Kiciman · Eleanor Dillon · Darren Edge · Adam Foster · Joel Jennings · Chao Ma · Robert Ness · Nick Pawlowski · Amit Sharma · Cheng Zhang -
2022 : Deep End-to-end Causal Inference »
Tomas Geffner · Javier Antorán · Adam Foster · Wenbo Gong · Chao Ma · Emre Kiciman · Amit Sharma · Angus Lamb · Martin Kukla · Nick Pawlowski · Miltiadis Allamanis · Cheng Zhang -
2022 : Rhino: Deep Causal Temporal Relationship Learning with history-dependent noise »
Wenbo Gong · Joel Jennings · Cheng Zhang · Nick Pawlowski -
2022 : Causal Reasoning in the Presence of Latent Confounders via Neural ADMG Learning »
Matthew Ashman · Chao Ma · Agrin Hilmkil · Joel Jennings · Cheng Zhang -
2022 : Fifteen-minute Competition Overview Video »
Jack Wang · Joel Jennings · Cheng Zhang · Wenbo Gong · Simon Woodhead · Nick Pawlowski · Digory Smith · Craig Barton -
2023 Workshop: Machine Learning with New Compute Paradigms »
Jannes Gladrow · Benjamin Scellier · Eric Xing · Babak Rahmani · Francesca Parmigiani · Paul Prucnal · Cheng Zhang -
2022 Competition: Causal Insights for Learning Paths in Education »
Wenbo Gong · Digory Smith · Jack Wang · Simon Woodhead · Nick Pawlowski · Joel Jennings · Cheng Zhang · Craig Barton -
2022 : Panel Discussion »
Cheng Zhang · Mihaela van der Schaar · Ilya Shpitser · Aapo Hyvarinen · Yoshua Bengio · Bernhard Schölkopf -
2022 Workshop: Causal Machine Learning for Real-World Impact »
Nick Pawlowski · Jeroen Berrevoets · Caroline Uhler · Kun Zhang · Mihaela van der Schaar · Cheng Zhang -
2022 : Opening Remarks »
Cheng Zhang · Mihaela van der Schaar -
2022 Poster: Simultaneous Missing Value Imputation and Structure Learning with Groups »
Pablo Morales-Alvarez · Wenbo Gong · Angus Lamb · Simon Woodhead · Simon Peyton Jones · Nick Pawlowski · Miltiadis Allamanis · Cheng Zhang -
2021 : Invited talk #5: Mihaela van der Schaar »
Mihaela van der Schaar -
2021 Workshop: Deep Generative Models and Downstream Applications »
José Miguel Hernández-Lobato · Yingzhen Li · Yichuan Zhang · Cheng Zhang · Austin Tripp · Weiwei Pan · Oren Rippel -
2020 Poster: VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data »
Chao Ma · Sebastian Tschiatschek · Richard Turner · José Miguel Hernández-Lobato · Cheng Zhang -
2020 Poster: A Causal View on Robustness of Neural Networks »
Cheng Zhang · Kun Zhang · Yingzhen Li -
2020 Poster: How do fair decisions fare in long-term qualification? »
Xueru Zhang · Ruibo Tu · Yang Liu · Mingyan Liu · Hedvig Kjellstrom · Kun Zhang · Cheng Zhang -
2020 : Q&A for invited speaker, Mihaela van der Schaar »
Mihaela van der Schaar -
2020 : Interpretable AutoML: Powering the machine learning revolution in healthcare in the era of Covid-19 and beyond »
Mihaela van der Schaar -
2020 Tutorial: (Track1) Advances in Approximate Inference Q&A »
Yingzhen Li · Cheng Zhang -
2020 Tutorial: (Track1) Advances in Approximate Inference »
Yingzhen Li · Cheng Zhang -
2019 Poster: Attentive State-Space Modeling of Disease Progression »
Ahmed Alaa · Mihaela van der Schaar -
2019 Poster: Demystifying Black-box Models with Symbolic Metamodels »
Ahmed Alaa · Mihaela van der Schaar -
2019 Poster: Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck »
Maximilian Igl · Kamil Ciosek · Yingzhen Li · Sebastian Tschiatschek · Cheng Zhang · Sam Devlin · Katja Hofmann -
2019 Poster: Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation »
Ruibo Tu · Kun Zhang · Bo Bertilson · Hedvig Kjellstrom · Cheng Zhang -
2019 Poster: Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model »
Wenbo Gong · Sebastian Tschiatschek · Sebastian Nowozin · Richard Turner · José Miguel Hernández-Lobato · Cheng Zhang -
2019 Poster: Differentially Private Bagging: Improved utility and cheaper privacy than subsample-and-aggregate »
James Jordon · Jinsung Yoon · Mihaela van der Schaar -
2019 Poster: Conditional Independence Testing using Generative Adversarial Networks »
Alexis Bellot · Mihaela van der Schaar -
2019 Spotlight: Conditional Independence Testing using Generative Adversarial Networks »
Alexis Bellot · Mihaela van der Schaar -
2018 Poster: Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks »
Bryan Lim · Ahmed M. Alaa · Mihaela van der Schaar -
2017 : Coffee break and Poster Session II »
Mohamed Kane · Albert Haque · Vagelis Papalexakis · John Guibas · Peter Li · Carlos Arias · Eric Nalisnick · Padhraic Smyth · Frank Rudzicz · Xia Zhu · Theodore Willke · Noemie Elhadad · Hans Raffauf · Harini Suresh · Paroma Varma · Yisong Yue · Ognjen (Oggi) Rudovic · Luca Foschini · Syed Rameel Ahmad · Hasham ul Haq · Valerio Maggio · Giuseppe Jurman · Sonali Parbhoo · Pouya Bashivan · Jyoti Islam · Mirco Musolesi · Chris Wu · Alexander Ratner · Jared Dunnmon · Cristóbal Esteban · Aram Galstyan · Greg Ver Steeg · Hrant Khachatrian · Marc Górriz · Mihaela van der Schaar · Anton Nemchenko · Manasi Patwardhan · Tanay Tandon -
2017 Poster: DPSCREEN: Dynamic Personalized Screening »
Kartik Ahuja · William Zame · Mihaela van der Schaar -
2017 Poster: Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks »
Ahmed M. Alaa · Mihaela van der Schaar -
2017 Spotlight: Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks »
Ahmed M. Alaa · Mihaela van der Schaar -
2017 Poster: Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes »
Ahmed M. Alaa · Mihaela van der Schaar