Sotabase

Career

· Assistant Professor, University of Wisconsin-Madison2022–
· Postdoctoral Scholar, University of California, Berkeley2019–2022
· Research Intern, Microsoft2016–2016
· PhD, Computer Science/ Machine Learning, Carnegie Mellon University2013–2018
· Software Engineering Intern, Google2011–2011
· Associate Engineer (Intern), Zone24x7 (Pvt) Ltd2011–2011
· B. Sc. (Eng) in Electronic & Telecommunication Engineering, University of Moratuwa2008–2013

Publications (66)

Neural Architecture Search with Bayesian Optimisation and Optimal Transport
Neural Information Processing Systems · 2018
646
cited
High Dimensional Bayesian Optimisation and Bandits via Additive Models
International Conference on Machine Learning · 2015
397
cited
Parallelised Bayesian Optimisation via Thompson Sampling
International Conference on Artificial Intelligence and Statistics · 2018
267
cited
Multi-fidelity Bayesian Optimisation with Continuous Approximations
International Conference on Machine Learning · 2017
243
cited
Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly
Journal of machine learning research · 2019
190
cited
A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations
Conference on Uncertainty in Artificial Intelligence · 2018
158
cited
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations
Neural Information Processing Systems · 2016
156
cited
Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning
Cell Reports Physical Science · 2019
143
cited
ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations
International Conference on Artificial Intelligence and Statistics · 2019
140
cited
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations
Neural Information Processing Systems · 2015
125
cited
Nonparametric Estimation of Renyi Divergence and Friends
International Conference on Machine Learning · 2014
95
cited
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models
International Conference on Artificial Intelligence and Statistics · 2016
84
cited
Multi-fidelity Gaussian Process Bandit Optimisation
Journal of Artificial Intelligence Research · 2016
80
cited
Bayesian active learning for posterior estimation
2015
56
cited
Offline Contextual Bayesian Optimization
Neural Information Processing Systems · 2019
53
cited
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA
International Conference on Machine Learning · 2016
45
cited
The Multi-fidelity Multi-armed Bandit
Neural Information Processing Systems · 2016
41
cited
Cilantro: Performance-Aware Resource Allocation for General Objectives via Online Feedback
USENIX Symposium on Operating Systems Design and Implementation · 2023
36
cited
Asynchronous Parallel Bayesian Optimisation via Thompson Sampling
arXiv.org · 2017
33
cited
Query efficient posterior estimation in scientific experiments via Bayesian active learning
Artificial Intelligence · 2017
31
cited
Sotabase
Kirthevasan Kandasamy | Researcher Profile | Sotabase | Sotabase