About Me

I am a Machine Learning Scientist who has transitioned into a Consulting role to accommodate personal ventures. Primarily interested in developing Machine Learning for Health-Tech at the moment, I like solving hard problems which will have a positive impact on society and our environment. I am also a Vedic Astrologer, Consultant and Healer. Reach out if you wish to book a consultation session.

I worked as an Applied Scientist at the Computer Vision, Machine Learning Group at Amazon, USA from 2018-2023. I was the lead scientist on the Amazon Halo Body Fat Estimation Pipeline (check out our Nature Digital Medicine Paper). Prior to joining Amazon, I was a Computer Vision Post-Doctoral Researcher working for SNCF/Railenium, Paris. I completed my PhD at INRIA, Ecole Centrale-Supelec Paris, working with Prof. Iasonas Kokkinos. I am interested in developing Machine Learning applications.

I was a Research Intern at Facebook Artificial Intelligence Research (FAIR), Paris under Dr. Camille Couprie. In the past I have worked as a Research Assistant at the Center for Visual Information Technology (CVIT), IIIT Hyderabad, and as a visiting Research student at the Visual Geometry Group (VGG), University of Oxford. I received my (MS by Research + Bachelor of Technology (Honours) in Computer Science) at the International Institute of Information Technology, Hyderabad, India.

I used to sing for a Metal/Rock band called Karmic Blend. I have been part of other Rock bands, Blackhole, and Victims of Rock before. I am looking to collaborate with musicians, so please reach out if interested and available. I like to write, and occasionally write poems, songs, short stories. I have played various sports over the years: cricket, football, basket ball, tennis. I am a fitness enthusiast, and I like to travel, and cook.

News

• [July 2022] Serving as Area Chair for British Machine Vision Conference (BMVC), London, UK
• [April 2022] Work on "Smartphone Camera Based Assessment of Adiposity" accepted at Nature Portfolio Journal on Digital Medicine
• [July 2020] Work on "Box2Seg: Attention Weighted Loss and Discriminative Feature Learning for Weakly Supervised Segmentation" accepted at ECCV
• [March 2020] Work on "Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation" published in Frontiers of Computational Neuroscience
• [August 2019] Arxiv Report on "Proof of Correctness and Time Complexity Analysis of a Maximum Distance Transform Algorithm"
• [June 2019] Work on "Learning to generate synthetic data via compositing" accepted at CVPR 2019.
• [November 2018] Arxiv Report on "Identifying the best machine learning algorithms for brain tumor segmentation".
• [February 2018] Work on "Deep Spatio-Temporal Random Fields for Efficient Video Segmentation" accepted at CVPR 2018.
• [August 2017] Work on "Structured Output Prediction and Learning for Deep Monocular 3D Human Pose Estimation" accepted at EMMCVPR 2017.
• [July 2017] Work on "Dense and Low-Rank Gaussian CRFs Using Deep Embeddings" accepted at ICCV 2017.
• [May 2017] I will be interning at Facebook Aritificial Intelligence Research (FAIR) Paris this summer.
• [September 2016] Code for "Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs" online.
• [September 2016] Successful conclusion of EU-Project MOBOT.
• [July 2016] Work on "Human Joint Angle Estimation and Gesture Recognition for Assistive Robotic Vision" accepted at ACVR, ECCV 2016.
• [July 2016] Work on "Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs" accepted at ECCV 2016.
• [October 2015] Work on "Accurate Human-Limb Segmentation in RGB-D images for Intelligent Mobility Assistance Robots" accepted at ACVR, ICCV 2015.
• [July 2015] Work on "Surface Based Object Detection in RGBD Images" accepted at BMVC 2015.

Publications

2022	Maulik Majumdar, Siddhartha Chandra et. al. Smartphone Camera Based Assessment of Adiposity (PREPRINT) Nature Portfolio Journal on Digital Medicine
2020	V. Kulharia*, Siddhartha Chandra* et. al. Box2Seg: Attention Weighted Loss and Discriminative Feature Learning for Weakly Supervised Segmentation (LINK) ECCV, 2020
2020	T Estienne, Siddhartha Chandra et. al. Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation (LINK) Frontiers in Computational Neuroscience, 2020
2019	M Sahasrabudhe & Siddhartha Chandra Proof of Correctness and Time Complexity Analysis of a Maximum Distance Transform Algorithm (PDF) Arxiv Report, 2019
2019	Shashank Tripathi*, Siddhartha Chandra* et. al. Learning to generate synthetic data via compositing (PDF) IEEE Conference on Computer Vision and Pattern Recognition, USA, 2019
2018	S Bakas, Siddhartha Chandra et. al. Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge (PDF) Arxiv Report, 2018
2018	Siddhartha Chandra et. al. Context aware 3D CNNs for brain tumor segmentation International MICCAI Brainlesion Workshop, 2018
2018	Siddhartha Chandra, Camille Couprie & Iasonas Kokkinos Deep Spatio-Temporal Random Fields for Efficient Video Segmentation (PDF) IEEE Conference on Computer Vision and Pattern Recognition, USA 2018
2017	Siddhartha Chandra, Nicolas Usunier & Iasonas Kokkinos Dense and Low-Rank Gaussian CRFs Using Deep Embeddings (PDF) International Conference on Computer Vision, Italy 2017
2017	Stefan Kinauer*, Riza Alp Guler*, Siddhartha Chandra & Iasonas Kokkinos Structured Output Prediction and Learning for Deep Monocular 3D Human Pose Estimation (PDF) Energy Minimization Methods in Computer Vision and Pattern Recognition, Italy 2017
2016	Siddhartha Chandra & Iasonas Kokkinos Fast, Exact and Multi-Scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs (PDF) CODE European Conference on Computer Vision, Netherlands 2016
2016	Alp Guler, Siddhartha Chandra & Iasonas Kokkinos et. al. Human Joint Angle Estimation and Gesture Recognition for Assistive Robotic Vision (PDF) Workshop, European Conference on Computer Vision, Netherlands 2016
2015	Siddhartha Chandra, Stavros Tsogkas & Iasonas Kokkinos Accurate Human-Limb Segmentation in RGB-D images for Intelligent Mobility Assistance Robots (PDF) Workshop, International Conference on Computer Vision, Chile 2015
2015	Siddhartha Chandra, Grigoris Chrysos & Iasonas Kokkinos Surface Based Object Detection in RGBD Images (PDF) British Machine Vision Conference, U.K. 2015
2013	Siddhartha Chandra, Shailesh Kumar & C.V. Jawahar, Learning Multiple Non-Linear Subspaces using K-RBMs (PDF) IEEE Conference on Computer Vision and Pattern Recognition, USA 2013
2012	Siddhartha Chandra, Shailesh Kumar & C.V. Jawahar, Learning Hierarchical Bag of Words using Naive Bayes Clustering (PDF) Asian Conference on Computer Vision, Korea 2012
2012	Siddhartha Chandra & C.V. Jawahar, Partial Least Squares Kernel for Computing Similarities between Video Sequences (PDF) (Oral), International Conference on Pattern Recognition, Japan 2012
2012	Vinay Garg, Siddhartha Chandra & C.V. Jawahar, Sparse Discriminative Fisher Vectors in Visual Classification (PDF) (Oral), Indian Conference on Vision, Graphics and Image Processing, India 2012
2010	Mayank Juneja, Siddhartha Chandra, Omkar M. Parkhi, C. V. Jawahar, Andrea Vedaldi, Marcin Marszalek, Andrew Zisserman Oxford/IIIT - TRECVID 2010 - Notebook paper (PDF) In Proceedings of the TREC Video Retrieval (TRECVID) Workshop organized by NIST, Gaithersburg, USA Nov. 2010.

Résumé

Contact Me

Siddhartha Chandra,
7-D/5 Tashkent Road,
Allahabad 211001 India

Phone: +91 933-5151-993
Email ID: robinchandra19<RemoveThisIfYouAreHuman>@gmail.com

Extra-Curricular Music:
Former vocalist of the Rock Band Blackhole, Hyderabad.
Former vocalist of the Rock Band Victims of Rock,Allahabad.
Literature:
Working on my debut Novel, The Guy.
Poet.
Song writer.
Fiction writer.
Blogger. www.sidjustice21.wordpress.com
Sports:
Played Cricket and Football at the school and college
level.