SIDDHARTH
RAMCHANDRAN
Doctoral Candidate in Machine Learning
Aalto University, Helsinki
Pushing the frontiers of Machine Learning for personalised medicine and predictive health care.
Biography
Siddharth’s specialisation is in probabilistic modelling, deep learning and statistical genetics. He has been actively involved over the past couple of years in the Computational Systems Biology research group. His research interests are deep generative models, approximate inference methods and gaussian processes to name a few.
He is currently working on unsupervised deep generative models for clinical data with an aim to build comprehensive models for multi-disease modelling that can analyse bio-bank data at a population-wide scale and covering data from individuals even from birth/early life until disease onset.
Education
Doctoral of Science (Technology)
Oct 2019 - Present
Machine Learning (Computer Science)
Aalto University, Helsinki, Finland
Master of Science (Technology)
Sept 2016 - July 2019
Machine Learning, Data Science and Artificial Intelligence
Minor in Bio-informatics
Aalto University, Helsinki, Finland
Final CGPA: 4.7 / 5.0
Graduated with honours
Sept 2012 - May 2016
Bachelor of Science (Technology)
Information Technology
VIT University, Vellore, India
May 2016
Final CGPA: 9.73 / 10.0
Ranked #1 in a class of 243
Biography
Siddharth’s specialisation is in probabilistic modelling, deep learning and statistical genetics. He has been actively involved over the past couple of years in the Computational Systems Biology research group. His research interests are deep generative models, approximate inference methods and gaussian processes to name a few.
He is currently working on unsupervised deep generative models for clinical data with an aim to build comprehensive models for multi-disease modelling that can analyse bio-bank data at a population-wide scale and covering data from individuals even from birth/early life until disease onset.
Education
Doctor of Science (Technology)
October 2019 - Present
Machine Learning (Computer Science)
Aalto University, Helsinki, Finland
Master of Science (Technology)
September 2016 - July 2019
Machine Learning, Data Science and Artificial Intelligence
Minor in Bio-informatics
Aalto University, Helsinki, Finland
Final CGPA: 4.7 / 5.0
Graduated with honours
September 2012 - May 2016
Bachelor of Science (Technology)
Information Technology
VIT University, Vellore, India
May 2016
Final CGPA: 9.73 / 10.0
Ranked #1 in a class of 243
Publications
Published in: International Conference on Artificial Intelligence and Statistics [AISTATS] (2021), San Diego, California, USA
Published in: Nature Communications, Vol 10, No. 1798, (2019)
Published in: International Conference on Artificial Intelligence and Statistics [AISTATS] (2021), San Diego, California, USA
Published in: International Journal of High Performance Computing and Networking, 10(1-2), pp. 109-117.
Published in: Nature partner journal Systems Biology and Applications, (2020)
Presentations
March 2020
Statistical Genetics and Personalised Medicine course (Spring 2020), Aalto University, Espoo, Finland
Deep generative modelling for biomedical data
Ramchandran, S
July 2019
Deep Learning and Reinforcement Learning Summer School,
Edmonton, Canada
Latent Gaussian processes with composite likelihoods for data-driven disease stratification.
Ramchandran, S., Koskinen, M. and Lähdesmäki, H.
June 2019
36th International Conference on Machine Learning (ICML), Workshop on Computational Biology, Long Beach, CA, USA
An additive Gaussian process regression model for interpretable probabilistic non-parametric analysis of longitudinal data.
Cheng L, Ramchandran S, Vatanen T, Timonen J, Lietzen N, Lahesmaa R, Vehtari A, Lähdesmäki H
December 2018
11th annual RECOMB/ISCB Conference on Regulatory & Systems Genomics,
New York, NY, USA
An additive Gaussian process regression model for interpretable probabilistic non-parametric analysis of longitudinal data.
Cheng L, Ramchandran S, Vatanen T, Timonen J, Lietzen N, Lahesmaa R, Vehtari A, Lähdesmäki H
December 2018
AI Day, Espoo, Finland
Latent Gaussian processes with composite likelihoods for data-driven disease stratification.
Ramchandran, S., Koskinen, M. and Lähdesmäki, H.
Collaborators
Get in Touch!
Siddharth Ramchandran
Department of Computer Science,
PO Box 15400, FI-00076 Aalto
Finland
Email: siddharth.ramchandran(at)aalto.fi