CV

Education

• PhD in Medical Image Analysis, University of Copenhagen, Denmark (2018)
• MSc in Electrical Engineering, Chalmers University, Sweden (2015)
• Bachelor in Electronics and Communication Engineering, BMS Institute of Technology, India (2009)

Work experience

• Sep 2020 – Ongoing
  • Role: Assistant Professor
  • Employer: University of Copenhagen
• Jan 2019 – Aug. 2020
  • Role: Post-doc
  • Employer: University of Copenhagen, Copenhagen
• Aug 2011 – July 2013
  • Role: Lecturer
  • Employer: BMS Institute of Technology, Bangalore
• Nov 2009 – July 2011 * Role: Networking Engineer
  • Employer: MRO-TEK, Bangalore
• Freelance writer
  • Columnist for The Hindu, Frontline
  • Nov 2011 - Ongoing

Awards

• Runner-up Best Paper Award at International Conference of Medical Imaging with Deep Learning (2020). Interview.
• Swedish Institute Scholarship covering MSc expenses (2013)
• Limca Book of Records Award: Team Member of India’s smallest satellite project - StudSat (2011)

Skills

• Reviewer at high impact journals and conferences such as IEEE Transactions of Medical Image Analysis, Medical Image Analysis, MICCAI, MIDL, NeurIPS
• Blogger

Publications

Multi-layered tensor networks for image classification

Raghavendra Selvan, Silas Ørting, Erik B Dam; Multi-layered tensor networks for image classification; First Workshop on Quantum Tensor Networks in Machine Learning. In conjunction with 34th NeurIPS, 2020.

DEVELOPING AND VALIDATING COVID-19 ADVERSE OUTCOME RISK PREDICTION MODELS FROM A BI-NATIONAL EUROPEAN COHORT OF 5594 PATIENTS

Espen Jimenez-Solem, Tonny S Petersen, Casper Hansen, Christian Hansen, Christina Lioma, Christian Igel, Wouter Boomsma, Oswin Krause, Stephan Lorenzen, Raghavendra Selvan, Janne Petersen, Martin Erik Nyeland, Mikkel Zoellner Ankarfeldt, Gert Mehl Virenfeldt, Matilde Winther-Jensen, Allan Linneberg, Mostafa Mediphour Ghazi, Nicki Detlefsen, Andreas Lauritzen, Abraham George Smith, Marleen de Bruijne, Bulat Ibragimov, Jens Petersen, Martin Lillholm, Jon Middleton, Stine Hasling Mogensen, Hans-Christian Thorsen-Meyer, Anders Perner, Marie Helleberg, Benjamin Skov Kaas-Hansen, Mikkel Bonde, Alexander Bonde, Akshay Pai, Mads Nielsen, Martin Sillesen " DEVELOPING AND VALIDATING COVID-19 ADVERSE OUTCOME RISK PREDICTION MODELS FROM A BI-NATIONAL EUROPEAN COHORT OF 5594 PATIENTS." Medrxiv, 2020.

Locally orderless tensor networks for classifying two- and three-dimensional medical images

Raghavendra Selvan, Silas Ørting, Erik B Dam, "Locally orderless tensor networks for classifying two- and three-dimensional medical images." Arxiv, 2020.

Characterising the Atomic Structure of Mono-Metallic Nanoparticles from X-Ray Scattering Data Using Conditional Generative Models

Andy Sode Anker, Emil T. S. Kjær, Erik B. Dam, Simon J. L. Billinge, Kirsten M. Ø. Jensen, Raghavendra Selvan; Characterising the Atomic Structure of Mono-Metallic Nanoparticles from X-Ray Scattering Data Using Conditional Generative Models; 16th International Workshop on Mining and Learning with Graphs, 2020.

Uncertainty quantification in medical image segmentation with Normalizing Flows

Raghavendra Selvan, Frederik Faye, Jon Middleton, Akshay Pai, "Uncertainty quantification in medical image segmentation with Normalizing Flows." 11th International Workshop on Machine Learning in Medical Imaging, 2020.

Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models

Lasse F. Wolff Anthony, Benjamin Kanding, Raghavendra Selvan;Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models; ICML Workshop on Challenges in Deploying and monitoring Machine Learning Systems, 2020.

Lung Segmentation from Chest X-rays using Variational Data Imputation

Raghavendra Selvan, Erik Dam, Sofus Rischel, Kaining Sheng, Mads Nielsen, Akshay Pai, "Lung Segmentation from Chest X-rays using Variational Data Imputation." ICML Workshop on The Art of Learning with Missing Values (Artemiss), 2020.

Tensor Networks for Medical Image Classification

Raghavendra Selvan, Erik Dam, "Tensor Networks for Medical Image Classification." In the proceedings of International Conference on Medical Imaging with Deep Learning (MIDL), 2020.

Locomotor deficits in ALS mice are paralleled by loss of V1-interneuron-connections onto fast motor neurons

Ilary Allodi, Roser Montanana-Rosell, Raghavendra Selvan, Peter Low, Ole Kiehn, "Locomotor deficits in ALS mice are paralleled by loss of V1-interneuron-connections onto fast motor neurons." bioRxiv, 2020.

Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks

Raghavendra Selvan, Thomas Kipf, Max Welling, Antonio Juarez, Jesper Pedersen, Jens Petersen, Marleen Bruijne, "Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks." Medical Image Analysis, 2020.

Segmentation of roots in soil with U-Net

Abraham Smith, Jens Petersen, Raghavendra Selvan, Camilla Rasmussen, "Segmentation of roots in soil with U-Net." Journal of Plant Methods, 2019.

Increasing Accuracy of Optimal Surfaces Using Min-Marginal Energies

Jens Petersen, Andres Arias-Lorza, Raghavendra Selvan, Daniel Bos, Aad Lugt, Jesper Pedersen, Mads Nielsen, Marleen Bruijne, "Increasing Accuracy of Optimal Surfaces Using Min-Marginal Energies." IEEE transactions on medical imaging, 2019.

Extracting tree-structures in CT data by tracking multiple statistically ranked hypotheses

Raghavendra Selvan, Jens Petersen, Jesper Pedersen, Marleen Bruijne, "Extracting tree-structures in CT data by tracking multiple statistically ranked hypotheses." The International Journal of Medical Physics Research and Practice, 2019.

A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs

Antonio Juarez, Raghavendra Selvan, Zaigham Saghir, Marleen Bruijne, "A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs." In the proceedings of International Workshop on Machine Learning in Medical Imaging, 2019.

Mean field network based graph refinement with application to airway tree extraction

Raghavendra Selvan, Max Welling, Jesper Pedersen, Jens Petersen, Marleen Bruijne, "Mean field network based graph refinement with application to airway tree extraction." In the proceedings of 21st Conference on Medical Image Computing & Computer Assisted Intervention (MICCAI 2018), Grenada, Spain (preprint), 2018.

Extraction of Airways from Volumetric Data

Raghavendra, Selvan. Extraction of Airways from Volumetric Data. Department of Computer Science, Faculty of Science, University of Copenhagen, 2018.

Extraction of Airways using Graph Neural Networks

Raghavendra Selvan, Thomas Kipf, Max Welling, Jesper Pedersen, Jens Petersen, Marleen Bruijne, "Extraction of Airways using Graph Neural Networks." In the proceedings of 1st Conference on Medical Imaging with Deep Learning (MIDL 2018), Amsterdam., 2018.

Extraction of airways with probabilistic state-space models and Bayesian smoothing

Raghavendra Selvan, Jens Petersen, Jesper Pedersen, Marleen Bruijne, "Extraction of airways with probabilistic state-space models and Bayesian smoothing." In the proceedings of Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 2017.

Extraction of airway trees using multiple hypothesis tracking and template matching

Raghavendra Selvan, Jens Petersen, Jesper Pedersen, Marleen Bruijne, "Extraction of airway trees using multiple hypothesis tracking and template matching." In the proceedings of The Sixth International Workshop on Pulmonary Image Analysis. MICCAI, 2016.

A batch algorithm for estimating trajectories of point targets using expectation maximization

Abu Rahmathullah, Raghavendra Selvan, Lennart Svensson, "A batch algorithm for estimating trajectories of point targets using expectation maximization." IEEE Transactions on Signal Processing, 2016.

Bayesian tracking of multiple point targets using expectation maximization

Selvan, Raghavendra. Bayesian tracking of multiple point targets using expectation maximization. MS thesis. 2015.