Deepanway Ghosal
Senior Research Scientist at Google DeepMind
Bengaluru, Karnataka, India
Summary
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Rockstar🎓
Top SchoolDeepanway Ghosal is a Senior Research Scientist at Google DeepMind with a decade of experience researching language reasoning and multimodal models. He holds a PhD in Computer Science from SUTD and has progressed from research roles at IIT Patna and NTU to impactful positions at Google and DeepMind. His work spans both core research and engineering—contributing model implementations for conversational emotion recognition and modernizing architectures like DialogueRNN and DialogueGCN for current PyTorch ecosystems. Based in Bengaluru, he blends academic rigor with production-oriented development, often bridging dataset preparation, training pipelines, and model design. Colleagues describe him as someone who moves fluidly between theoretical ideas and pragmatic code changes that make research reproducible. He brings a knack for updating legacy research code to modern frameworks, accelerating adoption of new models in practice.
10 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Singapore University of Technology and Design (SUTD)Bachelor of Technology (B.Tech.), Electrical Engineering, Bachelor of Technology (B.Tech.), Electrical Engineering at Indian Institute of Technology, Patna
Hindi, Bengali, English
Github Skills (8)
pytorch10
lstm10
emotion-recognition10
natural-language-processing9
machine-learning9
n7
sentiment-analysis7
rnn-model7
Programming languages (2)
Github contributions (5)
declare-lab/conv-emotion
May 2019 - Oct 2020
This repo contains implementation of different architectures for emotion recognition in conversations.
Role in this project:
ML Engineer
ML EngineerContributions:40 commits, 2 PRs, 34 pushes in 1 year 4 months
Contributions summary:Deepanway contributed to the implementation of emotion recognition architectures within the conversational AI domain. Their work involved updating and modifying existing models like DialogueRNN for compatibility with newer PyTorch versions. They also added files related to DialogueGCN, including a pre-processed dataset and training scripts, indicating involvement in model development and potentially data handling.
emotion-recognitionnatural-language-understandingdialogue-systemssentiment-analysistensorflow
declare-lab/dialogue-understanding
Sep 2020 - Nov 2020
Contributions:34 commits, 22 pushes, 12 comments in 2 months
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