Vaibhav Rajan is an Assistant Professor at the Department of Information Systems and Analytics at the School of Computing, National University of Singapore (NUS). Earlier, he was a Senior Research Scientist at Xerox Research Centre India where he led a project on Clinical Decision Support Systems for over 4 years. He has also worked as a consultant at Hewlett-Packard Labs India and as Chief Data Scientist at Videoken (an education technology startup).
Vaibhav Rajan received his PhD and Master's degrees in Computer Science from the Swiss Federal Institute of Technology at Lausanne (EPFL), Switzerland in 2012 and 2008 respectively and his Bachelor's degree in Computer Science from Birla Institute of Technology and Science (BITS), Pilani, India in 2004. His research interests include Machine Learning, Algorithm Design and their applications, primarily in Healthcare and Bioinformatics. He is a recipient of the ERS IASC Young Researchers Award 2014 given by European Regional Section (ERS) of the International Association for Statistical Computing (IASC).
- Machine Learning, Data Mining and their applications, particularly in Healthcare and Bioinformatics
- Predictive Models for Clinical Decision Support, Multi-view learning, Clustering, Time series analysis
- Predictive models for ICU complications
- Methods for discovering targeted cancer therapeutics
- Deep multi-view models for heterogeneous clinical data
- Copula based dependency models for computational phenotyping
- Temporal models for sparse, irregular clinical time series
- Vine Copulas for Mixed Data: Multi-view Clustering for Mixed Data Beyond Meta-Gaussian Dependencies, Lavanya Sita Tekumalla, Vaibhav Rajan, Chiranjib Bhattacharyya, Machine Learning (Springer), 2017, 1-27.
- Prediction and Imputation in Irregularly Sampled Clinical Time Series Data using Hierarchical Linear Dynamical Models, Abhishek Sengupta, Prathosh AP, Satya Narayan Shukla, Vaibhav Rajan, Chandan K Reddy, 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE EMBC 2017, JeJu Island, S. Korea.
- ICU Mortality Prediction: A Classification Algorithm for Imbalanced Datasets, Sakyajit Bhattacharya, Vaibhav Rajan, Harsh Shrivastava, 31st AAAI Conference on Artificial Intelligence AAAI 2017, San Francisco, USA
- Dependency Clustering of Mixed Data with Gaussian Mixture Copulas, Vaibhav Rajan, Sakyajit Bhattacharya, 25th International Joint Conference on Artificial Intelligence IJCAI 2016, New York, USA
- Predicting Complications in Critical Care using Heterogeneous Clinical Data, Vijay Huddar, Bapu Koundinya Desiraju, Vaibhav Rajan, Sakyajit Bhattacharya, Shourya Roy, Chandan K Reddy, Special Section on Big Data Analytics for Smart and Connected Health, IEEE Access 4, 7988-8001, 2016.
- Analysis of gene copy number changes in tumor phylogenetics, Jun Zhou, Yu Lin, Vaibhav Rajan, William Hoskins, Jijun Tang, BMC Algorithms in Molecular Biology, 11:26, 2016.
- Unsupervised Learning using Gaussian Mixture Copula Model, Sakyajit Bhattacharya, Vaibhav Rajan, 21st International Conference on Computational Statistics COMPSTAT 2014, Geneva, Switzerland (Won us the ERS IASC Young Researchers Award 2014 for best paper by researchers under 35)
- A method of alignment masking for refining the phylogenetic signal in multiple sequence alignments, Vaibhav Rajan, Molecular Biology and Evolution, Oxford University Press 2013 Mar;30(3):689-712.
- Bootstrapping Phylogenies Inferred from Rearrangement Data, Yu Lin, Vaibhav Rajan, BME Moret, BMC Algorithms in Molecular Biology, 7:21,2012 (best papers from WABI '11)
Singapore MOE AcRF Tier I (2018-21), Project Title: Deep Multi-View Learning Methods for Discovering Targeted Cancer Therapeutics (PI)
- Singapore MOE AcRF Tier I (2017-20), Project Title: Models and Algorithms for Clinical Data Analysis (PI)
- Herty Liany (co-supervisor)
- Rakkappan Lakshmanan
- Ratika Sianturi
- IS 6103: Design Science Research in Information Systems (2018)
Program Committee Member
- International Joint Conference on Artificial Intelligence (IJCAI) 2016, 2018
- AAAI Conference on Artificial Intelligence (AAAI) 2017
- ACM IKDD Conference on Data Sciences (CODS) 2015, 2016, 2017