Pulkit Kumar

I am a research scientist at ParallelDots, where I work mainly on medical imaging diagnosis through deep learning. I am also a research assiatant under Dr. Anubha Gupta and Dr. Chetan Arora at IIIT, Delhi where i am exploring the amalgation of computer vision with deep learning in medical domain.

I did my bachelors at Netaji Subhas Institute of Technology, New Delhi in Information Technology, where I was advised by Dr. Anand Gupta in my Bachelor Thesis Project. During my junior and senior year, I split my time studying at NSIT and interning with the amazing team at ParallelDots.

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U-Segnet: Fully convolutional neural network based automated brain tissue segmentation tool
Pulkit Kumar , Pravin Nagar , Chetan Arora , Anubha Gupta
International Conference on Image Processing (ICIP), 2018

A hybrid of SegNet and U-Net architecture for segmentation of Grey Matter, White Matter and Cerebrospinal Fluid in brain MRI.

Boosted Cascaded Convnets for Multilabel Classification of Thoracic Diseases in Chest Radiographs
Pulkit Kumar* , Monika Grewal*, Muktabh M. Srivastava
International Conference Image Analysis and Recognition (ICIAR), 2018

Combining boosting and cascading with DenseNets to detect all the pathologies in the Chest X-Ray 8 dataset.

RADNET: Radiologist level accuracy using deep learning for hemorrhage detection in CT scans
Monika Grewal, Muktabh M. Srivastava, Pulkit Kumar* , Srikrishna Varadarajan*
International Symposium of Biomedical Imaging (ISBI), 2018

A Deep Learning model combining DenseNets with attention and LSTMs to detect haemorrhage from brain CT scans which matches the accuracy of senior radiologists.

Anatomical labeling of brain CT scan anomalies using multi-context nearest neighbor relation networks
Srikrishna Varadarajan, Muktabh M. Srivastava, Monika Grewal*, Pulkit Kumar*
Poster in International Symposium of Biomedical Imaging (ISBI), 2018

Used multi-context feature embeddings from a pre-trained VGG model with nearest neighbours to train RelationNets for anatomic labelling in brain CT Scans.

A Big Data Analysis Framework Using Apache Spark and Deep Learning
Anand Gupta, Hardeo Thakur, Ritvik Shrivastava, Pulkit Kumar, Sreyashi Nag
International Conference of Data Mining (ICDM) workshop on Data Science and Big Data Analytics (DSBDA), 2017

A cascaded approach to predict the approval of H-1B visas on factors such as qualification, salary, location of job etc.

He is a great guy.