I am a University Lecturer in the Statistical Laboratory and the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge. I was previously Stein Fellow in the Department of Statistics at Stanford, where I did my PhD in the School of Medicine.
Research Interests
I am a statistician specialising in Bayesian methods and Bayesian nonparametrics, in particular. I have a background in Structural Biology, and I have previously worked on applications to molecular dynamics simulations and single-molecule biophysics. More recently, I have developed methods for the analysis of human microbiome studies.
I am interested in the problem of scaling Bayesian computations to modern applications in biology and more broadly. These problems increasingly require algorithms for approximate inference, such as variational Bayesian methods and approximate Bayesian computation, and I am interested in characterizing the tradeoff between accuracy and computational cost implicit in these algorithmic choices.
I am a member of the Cambridge Strategic Research Initiative in Big Data.
Publications
- Miguel García-Ortegón, Gregor N. C. Simm, Austin J. Tripp, José Miguel Hernández-Lobato, Andreas Bender, and Sergio Bacallado. DOCKSTRING: easy molecular docking yields better benchmarks for ligand design. [arXiv preprint], 2021.
- Nisha Ramakrishnan, Matthew Hird, Stephen Thompson, David J. Williamson, Luxi Qiao, David R. Owen, Allen F. Brooks, Peter J. Scott, Sergio Bacallado, John T. O’Brien, and Franklin I. Aigbirhio. Preclinical evaluation of (S)-[18F] GE387, a novel 18-kDa translocator protein (TSPO) PET radioligand with low binding sensitivity to human polymorphism rs6971. European Journal of Nuclear Medicine and Molecular Imaging, pp.1-12, 2021.
- Sergio Bacallado, Christophe Sabot, Pierre Tarres. The *-Edge-Reinforced Random Walk. [arXiv preprint], 2021.
- Steffen Ventz, Sergio Bacallado, Rifaquat Rahman, Sara Tolaney, Jonathan D. Shoenfeld, Brian M. Alexander and Lorenzo Trippa. The Effects of Releasing Early Results from Ongoing Clinical Trials. Nature Communications, 2021 (in press).
- Miguel Garcia-Ortegon, Andreas Bender, Carl Rasmussen, Hiroshi Kajino and Sergio Bacallado. Combining variational autoencoder representations with structural descriptors improves prediction of docking scores. NeurIPS workshop on Machine Learning for Molecules, 2020 [PDF]
- Qingyuan Zhao, Nianqiao Yu, Sergio Bacallado, Rajen Shah. BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic, The Annals of Applied Statistics, 2020 [PDF].
- Steffen Ventz, Matteo Cellamare, Sergio Bacallado, and Lorenzo Trippa. Bayesian uncertainty-directed trial designs. Journal of the American Statistical Association, 2018. [PDF]
- Annie Marsden, Sergio Bacallado. Sequential Matrix Completion. Technical report. [PDF]
- Boyu Ren, Sergio Bacallado, Stefano Favaro, Tommi Vatanen, Curtis Huttenhower, Lorenzo Trippa. Bayesian Mixed Effects Models for Zero-inflated Compositions in Microbiome Data Analysis, [arXiv preprint], 2017.
- Boyu Ren, Sergio Bacallado, Stefano Favaro, Susan Holmes, and Lorenzo Trippa. Bayesian Nonparametric Ordination for the Analysis of Microbial Communities. Journal of the American Statistical Association, 2017. [PDF]
- Sergio Bacallado, Vijay Pande, Stefano Favaro, Lorenzo Trippa. Bayesian regularization of the length of memory in reversible sequences. Journal of the Royal Statistical Society B, 2015. [PDF]
- Sergio Bacallado, Persi Diaconis, Susan Holmes. de Finetti priors using Markov chain Monte Carlo computations. Journal of Statistics and Computing, (25), 797-808, 2015. [PDF]
- Stefano Favaro, Sergio Bacallado, Lorenzo Trippa. Looking-backward probabilities for Gibbs-type exchangeable random partitions. Bernoulli, (21), 1-37, 2014. [PDF]
- Sergio Bacallado, Stefano Favaro, Lorenzo Trippa. Bayesian nonparametric inference for shared species richness in multiple populations. Journal of Statistical Planning and Inference, (166), 14-23, 2014. [PDF]
- Sergio Bacallado, Stefano Favaro, Lorenzo Trippa. Bayesian nonparametric analysis of reversible Markov chains. The Annals of Statistics, (41), 2, pp. 870- 896, 2013. [PDF]
- Huang-Wei Chang, Sergio Bacallado, Vijay Pande, and Gunnar Carlsson. Persistent Topology and Metastable States in Conformational Dynamics. PloS One, (8), 4, p. e58699, 2013. [PDF]
- Sergio Bacallado. Bayesian analysis of variable-order, reversible Markov chains. The Annals of Statistics, (39), 2, pp. 838-864, 2011. [PDF]
- Sergio Bacallado, John Chodera, and Vijay Pande. Bayesian comparison of Markov models of molecular dynamics with detailed balance constraint. Journal of Chemical Physics, (131), 4, p. 045106, 2009. [PDF]
- Xuhui Huang, Greg Bowman, Sergio Bacallado, Vijay Pande. Rapid equilibrium sampling initiated from non-equilibrium data. Proceedings of the Natural Academy of Sciences, (106), 47, pp. 19765-19769, 2009. [PDF]
- Akin Akinc, Andreas Zumbuehl, Michael Goldberg, Elizaveta Leshchiner, Valentina Busini, Naushad Hossain, Sergio Bacallado, David Nguyen, Jason Fuller, Rene Alvarez, Anna Borodovsky, Todd Borland, Rainer Constien, Antonin de Fougerolles, J Robert Dorkin, K Narayanannair Jayaprakash, Muthusamy Jayaraman, Matthias John, Victor Koteliansky, Muthiah Manoharan, Lubomir Nechev, June Qin, Timothy Racie, Denitza Raitcheva, Kallanthottathil G Rajeev, Dinah Sah, Jurgen Soutschek, Ivanka Toudjarska, Hans-Peter Vornlocher, Tracy Zimmermann, Robert Langer, and Daniel Anderson. A combinatorial library of lipid-like materials for delivery of RNAi therapeutics. Nature Biotechnology, (26), 5, pp. 561-569, 2008. [PDF]
Teaching
