Personal Information
Name: Shantanu Chandra
Current Position: Sr. AI Research Scientist
Company: ZS
Location: Bengaluru, India
LinkedIn Profile: [Shantanu Chandra on LinkedIn](https://in.linkedin.com/in/shantanu-chandra-63b26a106)
Educational Background
Shantanu Chandra holds a Master's degree in Artificial Intelligence (cum laude) from the University of Amsterdam. His thesis was supervised by Ekaterina Shutova at ILLC (Institute for Logic, Language, and Computation).
Professional Overview
Current Role at ZS
Shantanu serves as a Senior AI Research Scientist at ZS. His work revolves around:
- Generative AI
- Foundational models
- Graph Neural Networks
Major Achievements and Research
1. SAFER (Socially-Aware Fake News Detection Framework):
- Developed a framework addressing fake news through social context-aware mechanisms.
- Utilized relational and hyperbolic Graph Neural Networks for user and community modeling.
- Achieved state-of-the-art results on fake news datasets from multiple domains.
2. Hateful Memes Challenge (NeurIPS 2020):
- Shantanu's team utilized UNITER-based architecture to detect hateful, multi-modal content.
- Secured 4th place in the competition.
GitHub Repositories
Shantanu maintains several open-source projects on his GitHub profile:
- SAFER: Official code for the fake news detection paper.
- meme_challenge: Code repository for the hateful memes challenge.
- Multi_Object_Tracking: Object tracking in videos.
- Pose_Estimation: Pose estimation in animals using DeepLabCut.
- Medical_Imaging_UNet: Segmentation of optical coherence tomography images using UNet.
- Cond-Restricted-Boltzman-Machines-pytorch: Implementation of Conditional Restricted Boltzman Machines.
[Visit Shantanu's GitHub Profile](https://github.com/shaanchandra)
Google Scholar Presence
Shantanu Chandra's academic contributions are also recognized on Google Scholar with verified research in:
- Deep Learning
- Graph Neural Networks
- Generative Models
[Shantanu Chandra on Google Scholar](https://scholar.google.com/citations?user=aaa2q3kAAAAJ&hl=en)
Additional Publications and Thought Leadership
Shantanu is an active contributor to AI Fusion Labs on Medium. Some notable articles include:
- Training GANs on Spatio-Temporal Data: A practical guide across three parts discussing the complexities and practicalities of GANs in this context.
- Retentive Networks (RetNet) Explained: An in-depth look at RetNet, positioning it as a transformative approach in AI architectures.
- Data-centric AI: Discusses the importance and future of data-centric AI methodologies.
[Explore Publications on Medium](https://medium.com/@shantanu.chandra)
Relevant Skills and Interests
- Research: Shantanu demonstrates significant expertise in conducting comprehensive research in AI and data science.
- Technology Stack: Proficient in Python and deep learning frameworks.
- Project Management: Proven ability to lead and manage technical projects effectively from conceptualization through execution.
Contact Information
For professional inquiries, Shantanu Chandra can be reached through his LinkedIn profile or his professional email at ZS.
This detailed profiling report provides a well-structured and comprehensive summary of Shantanu Chandra's professional background, highlighting his key achievements, roles, and contributions in the field of AI research.
