Udit Agarwal

Work

Document Intelligence Lab | Prof. Santanu Choudhary | Dept. of CSE
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UNDERGRADUATE STUDENT RESEARCHER

Summary

Extracted key information from document images for visual question answering. Experimented with various transformer-based architectures for scene and text understanding like ViBERT, VILBERT, Chargrid, etc. Performed multi-modal learning for VQA (visual question answering) using layout aware scene text transformers.

Novus Hi-Tech Robotics Systems Ltd.
|

GRADUATE ENGINEER TRAINEE

Summary

Developing Al-driven AMRs (Autonomous Mobile Robots), L2 Autonomous vehicle for reducing human intervention in shop floors, warehouses, and manufacturing plants. Working on deep learning architectures for V-SLAM, structure from motion, scene reconstruction, and monocular depth estimation. Worked on multiple sensor fusion (camera, lidar, GPS & IMU) for mapping and localization of autonomous vehicles, based on autoware. Finetuned YOLOv8 model on real world data captured from Intet RealSense Depth Camera, for robust pallet detection. Implemented detection and pose estimation from detected bounding boxes using docker container on Nvidia Jetson Nano. Performed multi-view object detection by minimizing epipolar error using Hungarian matching.

Education

NEHRU WORLD SCHOOL

CLASS 12

CBSE

Grade: 95.3%

NEHRU WORLD SCHOOL

CLASS 10

ICSE

Grade: 90.17%

IIT JODHPUR

B.TECH

MECHANICAL ENGINEERING

Grade: 7.44/10

Awards

Student Distinguished Contributions Award Winner

Awarded By

IIT Jodhpur

Student Distinguished Services Award Winner

Awarded By

IIT Jodhpur

Represented IIT Jodhpur and Bagged 8th position in InterIIT Tech Meet.

Awarded By

IIT Jodhpur

Skills

PROGRAMMING

C++, C, Python, Simulink, R, Shell, Matlab, Java.

ML/DL TECHNOLOGIES

PyTorch, PyTorch Lightning, TensorFlow, ONNX, TensorRT, OpenCV, ROS1/ROS2, Open3D, Hugging-face, Ollama, SQL, Docker, Git, Scikit-Learn, Rust, SHAP, Xgboost, Lime, EDA, Tableau, Matplotlib.

MLOPS/AI ENGINEERING

AI/MLOps - AWS/Azure/GCP, Model Deployment (Docker & Kubernetes), Weights & Biases (W&B), DVC (Data Version Control), CI/CD for ML (GitHub Actions, GitLab CI), Linux shell utilities, Slurm HPC, RAG, Data Science.

Projects

IMPLEMENTATION AND OPTIMIZATION OF GPT 2

Summary

Self Deep Learning Project

RAG PIPELINE FOR PDF QUESTION ANSWERING

Summary

Self Deep Learning Project

FINGERPRINT GENERATION USING DIFFUSION MODELS

Summary

Course Project (Advanced ML) | Dr. Mayank Vatsa