I am interested in Machine Learning, especially in the field of Deep Learning. I have experience in Graph Machine Learning, Computer Vision (CV), and Natural Language Processing (NLP).

• During my undergrad days, I published a long paper at AAAI (top-tier ML conference) that has garnered over 100 citations
• Open source contributor to famous projects like Pytorch Geometric and TorchVision (Pytorch)
• Recipient of various prestigious academic fellowships as well as Microsoft AI for Earth grant
• Been part of teams that have won multiple national and international competitions

I completed my Bachelors from Indian Institute of Technology (IIT) Guwahati. Download Resume.

Publications
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ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
Ekagra Ranjan, Soumya Sanyal, Patha Talukdar
AAAI 2020 | Paper | Slides | Code
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Joint Learning Mechanism to Compress and Classify Radiological Images
Ekagra Ranjan*, Soumava Paul*, Siddharth Kapoor, Aupendu Kar, R. Sethuraman, Debdoot Sheet
ICVGIP 2018 (Oral Accept Rate: <10% ) | Paper | Slides | Code
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Auto-SCMA: Learning Codebook for Sparse Code Multiple Access using Machine Learning
Ekagra Ranjan*, Ameya Vikram*, A. Rajesh, P.K. Bora
NCC 2021 | Paper | Slides | Code
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Multilingual Abusiveness Identification on Code-Mixed Social Media Text
Ekagra Ranjan, Naman Poddar
Preprint | Paper | Slides | Code
Work Experience
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Data Scientist
Microsoft Search Assistance and Intelligence (MSAI)
Jul 2020 - Present

• Working on Knowledge Graph Search and Recommendation using Graph Machine Learning.
• Improved the relevance by 2x.
• Designed and deployed custom Message Passing Algorithms in low latency scenarios.
• Engineered dataset creation without explicit labeled data in an eyes-off and compliant setting.
• Developing the core relevance infrastructure for distributed supervised graph learning.
• Migrated Spark pipelines to Azure Machine Learning. Added CI/CD pipelines along with tests.
• Gave internal talks and wrote blogs for broader audience outside my team.

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Open Source Contributor
Pytorch Geometric (PyG)
May 2019 - Jul 2019

PyTorch Geometric (PyG) is a geometric deep learning extension library for PyTorch. It is a popular open source library for implementing Graph Neural Networks.
Following are some of my notable contributions to this library:-
• Added Dense Graph Convolution layer #445
• Added ASAP pooling and LEConv layers #1218
• Added Self-Attention Graph pooling #364
• Added Edge Weighted GraphConv #489
Contributors list: link

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Open Source Contributor
TorchVision (Pytorch)
Jan 2019 - Jul 2019

TorchVision is the computer vision library maintained by the Pytorch team at Facebook.
Some of my notable contributions to this library are:-
• Added GPU-Memory Efficient Densenet #1003, #797
• Added Affine Transformation #793
• Refactored Image Segmentation, Detection and Classification models #1009, #1091, #889
Contributors list: link

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Research Intern - Deep Learning
Indian Institute of Science (IISc)
May 2019 - Aug 2019

Advisor: Dr. Partha Talukdar
• Proposed a hierarchical sparse pooling operator for Graph Neural Nets. It has better edge connectivity in the pooled graph compared to other sparse methods.
• Introduced a new self-attention framework that is better suited for pooling.
• Proposed a new graph convolution operator that can adaptively learn functions of local extremas in a graph substructure.

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Research Intern - Deep Learning
Indian Institute of Technology (IIT) Kharagpur
May 2018 - Aug 2018

Advisor: Dr. Debdoot Sheet
• Worked on classification of thoracic diseases on NIH ChestX-Ray14 dataset.
• Proposed a model to reduce the loss of discriminative features which occurs during downsampling large images before feeding to classifiers.
• Achieved state of the art results on the official test set released by NIH.

Kaggle
  • Sharechat@IndoML' 21: 2nd Rank on Multilingual Abusive comment identification challenge organized by Sharechat
  • IndoRE@IndoML' 21: 2nd Rank on a relation extraction task for three low resource Indian Languages (Bengali, Telugu and Hindi)
  • Sharechat@IEEE BigMM' 21: 4th Rank on Indic Multilingual Abusive comment identification challenge organized by Sharechat
Academic Awards
  • Shastri Research Student Fellowship 2019: Among 18 people from Canada and India to be offered the fellowship by Ministry of Human Resource and Developement (MHRD), Government of India.
  • Charpak Lab Scholarship 2019: Among 30 people in India to be sponsored by Indian French Embassy
  • Tsinghua Deep Learning Summer School 2019: Among top 40 students globally to be invited for the event
  • Indian Academy of Sciences Fellowship 2018: Received the prestigious Indian Academy of Sciences Fellowship
  • Joint Entrance Examination 2016: Among top 0.1% out of 1.2 million students
Achievement in Competitions
  • Microsoft AI For Earth: Entitled $5000 Azure grant and inclusion to Microsoft AI for Earth community
  • Microsoft code.fun.do++ 2018: Secured 2nd place at National Finals
  • Microsoft Big Idea 2018: Among top 10 teams internationally and among top 2 teams in India
  • American Express Analyze This 2018: Top 0.8% among 2700+ participating teams
  • Microsoft Imagine Cup 2018: Finalist of Imagine Cup 2018 Nationals
  • Microsoft code.fun.do 2017: Secured 1st postion in 'Junior Division' and 2nd in 'Senior Division'
  • Inter-IIT Techmeet 2017: First in public leaderboard of Data science competition among all IITs
  • Goldman Sachs GS Quantify 2017: Ranked 3rd in campus and 32nd in India at Machine Learning section
  • American Express Analyze This 2017: Top 1.9% in 2600+ teams. Declared 'Outstanding Performer' by Amex