Scholar
Mukul Ranjan
Google Scholar ID: fFBR0j0AAAAJ
Researcher, MBZUAI
Citations & Impact
Citations
74
H-index
4
i10-index
2
Publications
6
Co-authors
7
list available
Publications
Resume (English only)
Academic Achievements
- - Publications: Published research in PLOS ONE on using advanced language models for topic modeling in Hindu philosophy, mapping themes between the Upanishads and the Bhagavad Gita.
- - Awards: Meesho Panchayat Award (2022), Undergraduate Samsung Fellowship Award (2021), Gold Medal in Inter-IIT Tech Meet (2021).
- - Certificates: Probability and Statistics, Python for Everybody, Deep Learning Specialization, Machine Learning from Coursera.
Research Experience
- - Data Scientist, Meesho, February 2022 – Present, Bangalore, India: Developed and deployed a representation learning-based model with over 1.3B parameters to learn the long-term interest of users.
- - AI Scientist, Qure.AI, December 2021 – February 2022, Bangalore, India: Developed a segmentation-assisted deep learning method for stroke severity measurement.
- - Machine Learning Researcher, UNSW Sydney, May 2021 – December 2021, Sydney, Australia: Used language models to find relationships between two ancient Indian texts, Bhagavad Gita and Upanishads.
- - Research Intern, Wadhwani AI, December 2021 – February 2022, Mumbai, India: Developed an end-to-end and multi-task learning framework to diagnose tuberculosis patients using radiological image data and deep learning methods.
- - Research Intern, UIUC, July 2019 – May 2019, Urbana-Champaign, USA: Developed a framework for automated annotation of spectral tissue images using mutual information-based image registration of FTIR and H&E images.
- - Research Intern, IIST Trivandrum, December 2018 – January 2019, Thiruvananthapuram, India: Worked on developing algorithms for single object tracking.
Education
- - Degree: B.Tech in ECE (Electronics and Communication Engineering)
- - University: IIT Guwahati (Indian Institute of Technology, Guwahati)
- - Graduation Year: 2021
Background
- - Research Interests: Vision-Language Models, Representation Learning, Natural Language Processing, Reinforcement Learning, Computer Vision, Information Extraction, Recommender Systems
- - Professional Field: Machine Learning
- - Biography: Currently pursuing a Master's degree in Machine Learning at MBZUAI, working with Professor Zhiqiang Shen on improving the efficiency and reasoning capabilities of LLMs, VLMs, and T2I models. Previously worked as a Data Scientist at Meesho, modeling long-term user interactions and product quality.
