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About

I recently graduated from the CS Ph.D. program at UC Berkeley where I worked with Yun S. Song. I am broadly interested in developing methods in statistical machine learning, probabilistic modeling, and experimental design as well as its real-world applications, in particular, I have worked on biology, healthcare, and forecasting in the past.

During my Ph.D, I had the good fortune of working with many fantastic mentors during internships. I worked with Ali Bashir at Google Accelerated Sciences on machine learning algorithms for genomics. Prior to that, I worked with Andy Miller and Emily Fox on the Apple Health AI team where I worked on representation learning for healthcare data. Lastly, I worked with Lawrence Murray at Uber AI Labs where I worked on online learning methods for time series. Prior to Berkeley, I received an M.Eng in Computer Science from MIT and a B.S. in Mathematics and Computer Science from MIT. I was funded by the NSF Graduate Research Fellowship.

Email: chanjed AT berkeley DOT edu

Preprints and Publications

Jeffrey Chan*, Aldo Pacchiano*, Nilesh Tripuraneni*, Yun S. Song, Peter Bartlett, Michael I. Jordan. Parallelizing Contextual Linear Bandits, In Submission.

Jeffrey Chan, Andrew C. Miller, Emily B. Fox. Representing and Denoising Wearable ECG Recordings, NeurIPS ML for Mobile Health Workshop 2020. Spotlight Talk.

Jeffrey Chan, Jeffrey Spence, and Yun S Song. Exchangeable variational autoencoders for genomic data. NeurIPS Advances in Approximate Bayesian Inference(AABI) Workshop 2019.

Jeffrey Chan, Valerio Perrone, Jeffrey P. Spence, Paul A. Jenkins, Sara Mathieson, Yun S. Song. A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks, NeurIPS 2018. Spotlight Talk.

J Victor Moreno-Mayar*, ..., Jeffrey Chan*, et al. Early human dispersals within the Americas. Science, 2018.

Jeffrey Chan, Yun S. Song. Reference-Free Archaic Admixture Segmentation Using A Permutation-Equivariant Neural Network. NeurIPS Machine Learning for Computational Biology 2017. Best Talk Award.

John A. Kamm, Jeffrey P. Spence, Jeffrey Chan, Yun S. Song. Two-locus likelihoods under variable population size and fine-scale recombination rate estimation. Genetics, 2016.

Ephrem K. Melese, Jeffrey Chan, Lauren S. Blieden, Alice Z. Chuang, Laura A. Baker, Nicholas P. Bell, and Robert M Feldman. Determination and validation of thresholds of anterior chamber parameters by dedicated anterior segment optical coherence tomography. American Journal of Ophthalmology, 2016.

Megan M. Geloneck, Jeffrey Chan, Alice Z. Chuang, and Helen A. Mintz-Hittner. BEAT-ROP refraction data at age 2 years. Journal of American Association for Pediatric Ophthalmology and Strabismus, 2013.

[*] Equal contribution

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