CV

Work experience

• Current employment (Sep 2020)
  • 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

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)

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, JMLR
• Blogger

Publications

Preprints / Under Review

1. Extracting Structural Motifs from Pair Distribution Function Data of Nanostructures using Explainable Machine Learning .
   Andy S. Anker, Emil T. S. Kjær, Mikkel Juelsholt, Troels Lindahl Christiansen, Susanne Linn Skjærvø, Mads Ry Vogel Jørgensen, Innokenty Kantor, Daniel Risskov Sørensen, Simon J. L. Billinge, Raghavendra Selvan, Kirsten M. Ø. Jensen.
   Chemrxiv, 2022. (link) (pdf)
   
2. DeepStruc: Towards structure solution from pair distribution function data using deep generative models .
   Emil T. S. Kjær, Andy S. Anker, Marcus N. Weng, Simon J. L. Billinge, Raghavendra Selvan, Kirsten M. Ø. Jensen.
   Chemrxiv, 2022. (link) (pdf)
   

Journal Articles

1. Patch-based medical image segmentation using Quantum Tensor Networks .
   Raghavendra Selvan, Erik B Dam, Søren Alexander Flensborg, Jens Petersen.
   The Journal of Machine Learning for Biomedical Imaging (MELBA), 2022. (link) (pdf)
   
2. Dynamic β-VAEs for quantifying biodiversity by clustering optically recorded insect signals .
   Klas Rydhmer, Raghavendra Selvan.
   Journal of Ecological Informatics, 2021. (link) (pdf)
   
3. Locomotor deficits in a mouse model of ALS are paralleled by loss of V1-interneuron connections onto fast motor neurons .
   Ilary Allodi, Roser Montañana-Rosell, Raghavendra Selvan, Peter Low, Ole Kiehn.
   Nature Communications, 2021. (link) (pdf)
   
4. Automatic airway segmentation from Computed Tomography using robust and efficient 3-D convolutional neural networks .
   Antonio Juarez, Raghavendra Selvan, Zaigham Saghir, HAWM Tiddens, Marleen de Bruijne.
   Scientific Reports, 2021. (link) (pdf)
   
5. Locally orderless tensor networks for classifying two- and three-dimensional medical images .
   Raghavendra Selvan, Silas Ørting, Erik B Dam.
   The Journal of Machine Learning for Biomedical Imaging (MELBA), 2021. (link) (pdf)
   
6. Detection of foraging behavior from accelerometer data using U-Net type convolutional networks .
   Manh Cuong Ngo, Raghavendra Selvan, Outi Tervo, Mads Peter Heide-Jørgensen, Susanne Ditlevsen.
   Ecological Informatics, 2021. (link) (pdf)
   
7. 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 Zöllner Ankarfeldt, Gert Mehl Virenfeldt, Matilde Winther-Jensen, Allan Linneberg, Mostafa Mehdipour Ghazi, Nicki Detlefsen, Andreas David 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.
   Scientific Reports, 2021. (link) (pdf)
   
8. Graph Refinement based Airway Extraction using Mean-Field Networks and Graph Neural Networks .
   Raghavendra Selvan, Thomas Kipf, Max Welling, Antonio GU Juarez, Jesper H. Pedersen, Jens Petersen, Marleen de Bruijne.
   Medical Image Analysis, 2020. (link) (pdf)
   
9. Segmentation of roots in soil with U-Net .
   Abraham George Smith, Jens Petersen, Raghavendra Selvan, Camilla Ruø Rasmussen.
   Journal of Plant Methods, 2019. (link) (pdf)
   
10. Increasing Accuracy of Optimal Surfaces Using Min-Marginal Energies .
    Jens Petersen, Andres M Arias-Lorza, Raghavendra Selvan, Daniel Bos, Aad van der Lugt, Jesper H Pedersen, Mads Nielsen, Marleen de Bruijne.
    IEEE transactions on medical imaging, 2019. (link) (pdf)
    
11. Extracting tree-structures in CT data by tracking multiple statistically ranked hypotheses .
    Raghavendra Selvan, Jens Petersen, Jesper H. Pedersen, Marleen de Bruijne.
    International Journal of Medical Physics Research and Practice, 2019. (link) (pdf)
    
12. A batch algorithm for estimating trajectories of point targets using expectation maximization .
    Abu Sajana Rahmathullah, Raghavendra Selvan, Lennart Svensson.
    IEEE Transactions on Signal Processing, 2016. (link) (pdf)
    

Refereed Conference/Workshop Papers

1. Interpreting Latent Spaces of Generative Models for Medical Images using Unsupervised Methods .
   Julian Schön, Raghavendra Selvan, Jens Petersen.
   Deep Generative Models Workshop, MICCAI, 2022. (link) (pdf)
   
2. Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis .
   Raghavendra Selvan, Nikhil Bhagwat, Lasse F. Wolff Anthony, Benjamin Kanding, Erik B. Dam.
   25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022. (link) (pdf)
   
3. Hybrid Ladder Transformers with Efficient Parallel-Cross Attention for Medical Image Segmentation .
   Haozhe Luo, Yu Changdong, Raghavendra Selvan.
   5th International Conference on Medical Imaging with Deep Learning, 2022. (link) (pdf)
   
4. Identifying partial mouse brain microscopy images from Allen reference atlas using a contrastively learned semantic space .
   Justinas Antanavicius, Roberto Leiras Gonzalez, Raghavendra Selvan.
   International Workshop on Biomedical Image Registration, 2022. (link) (pdf)
   
5. Deep ensemble model for segmenting microscopy images in the presence of limited labeled data .
   Jan Mikolaj Kaminski, Ilary Allodi, Roser Montañana-Rosell, Raghavendra Selvan, Ole Kiehn.
   4th Conference on Medical Imaging with Deep Learning (MIDL), 2021. (link) (pdf)
   
6. Carbon footprint driven deep learning model selection for medical imaging .
   Raghavendra Selvan.
   4th Conference on Medical Imaging with Deep Learning (MIDL), 2021. (link) (pdf)
   
7. Segmenting two-dimensional structures with strided tensor networks .
   Raghavendra Selvan, Erik B Dam, Jens Petersen.
   27th international conference on Information Processing in Medical Imaging (IPMI), 2021. (link) (pdf)
   
8. Multi-layered tensor networks for image classification .
   Raghavendra Selvan, Silas Ørting, Erik B Dam.
   First Workshop on Quantum Tensor Networks in Machine Learning. In conjunction with 34th NeurIPS, 2020., 2020. (link) (pdf)
   
9. Characterising the Atomic Structure of Mono-Metallic Nanoparticles from X-Ray Scattering Data Using Conditional Generative Models .
   Andy Sode Anker, Emil TS Kjær, Erik B Dam, Simon JL Billinge, Kirsten MØ Jensen, Raghavendra Selvan.
   16th International Workshop on Mining and Learning with Graphs, 2020. (link) (pdf)
   
10. Uncertainty quantification in medical image segmentation with Normalizing Flows .
    Raghavendra Selvan, Frederik Faye, Jon Middleton, Akshay Pai.
    11th International Workshop on Machine Learning in Medical Imaging, 2020. (link) (pdf)
    
11. Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models .
    Lasse F Wolff Anthony, Benjamin Kanding, Raghavendra Selvan.
    ICML Workshop on Challenges in Deploying and monitoring Machine Learning Systems, 2020. (link) (pdf)
    
12. Lung Segmentation from Chest X-rays using Variational Data Imputation .
    Raghavendra Selvan, Erik B Dam, Nicki Skafte Detlefsen, Sofus Rischel, Kaining Sheng, Mads Nielsen, Akshay Pai.
    ICML Workshop on The Art of Learning with Missing Values (Artemiss-2020), 2020. (link) (pdf)
    
13. Tensor Networks for Medical Image Classification .
    Raghavendra Selvan, Erik B Dam.
    Proceedings of International Conference on Medical Imaging with Deep Learning (MIDL). Winner of Runner-up Best Paper Award., 2020. (link) (pdf)
    
14. A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs .
    Antonio Juarez, Raghavendra Selvan, Zaigham Saghir, Marleen de Bruijne.
    the proceedings of International Workshop on Machine Learning in Medical Imaging, 2019. (link) (pdf)
    
15. Mean field network based graph refinement with application to airway tree extraction .
    Raghavendra Selvan, Max Welling, Jesper H. Pedersen, Jens Petersen, Marleen de Bruijne.
    21st Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018), Grenada, Spain, 2018. (link) (pdf)
    
16. Extraction of Airways using Graph Neural Networks .
    Raghavendra Selvan, Thomas Kipf, Max Welling, Jesper H. Pedersen, Jens Petersen, Marleen de Bruijne.
    1st Conference on Medical Imaging with Deep Learning (MIDL 2018), Amsterdam., 2018. (link) (pdf)
    
17. Extraction of airways with probabilistic state-space models and Bayesian smoothing .
    Raghavendra Selvan, Jens Petersen, Jesper H. Pedersen, Marleen de Bruijne.
    Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics, 2017. (link) (pdf)
    
18. Extraction of airway trees using multiple hypothesis tracking and template matching .
    Raghavendra Selvan, Jens Petersen, Jesper H. Pedersen, Marleen de Bruijne.
    Sixth International Workshop on Pulmonary Image Analysis. MICCAI, 2016. (link) (pdf)
    

Monographs

1. Extraction of Airways from Volumetric Data .
   Raghavendra Selvan.
   University of Copenhagen (PhD Thesis), 2018. (link) (pdf)
   
2. Bayesian tracking of multiple point targets using expectation maximization .
   Raghavendra Selvan.
   Chalmers University (MSc Thesis), 2015. (link) (pdf)