CV

Education

• PhD in Computer Science (Marie Curie fellowship) - 09/2020 - Present
  I3S/CNRS Laboratory, University Cote d’Azur, Nice, France.
  BiomechanicsCapture: Deep learning based biomechanics capture.
  • The aim of this project is to address the problem of acquiring the pose, shape, appearance, motion and dynamics of humans in 3D using multi-camera environment in real-time, which is fundamental to a wide range of applications including e-health, sport performance analysis, human-robot interaction, augmented reality and many more.
  • Industry partner: Youdome, Monaco
  • Academic partners: Brown University, United States
• MSc in Computer Science & Engineering - 09/2017 - 04/2020
  Politecnico di Milano, Milan, Italy.
  • Specialized in Artificial Intelligence and Computer vision.
  • Theoretical knowledge focused on AI, Machine learning, IoT, computer vision, and robotics.
  • Practical projects like: ”Art with computer vision”, ”Dancing robot”, ”Robotics with ROS and Gazebo”, and ”smart led net- work”.
• B.Tech in Computer Science & Engineering - 08/2013 - 08/2017
  West Bengal University of Technology, Kolkata, India
  • With practical experience in software engineering and Image processing.

Work experience

• Visiting Research Fellow - 10/2022 - Current
  Brown University, Providence, RI, USA.
  • Canonical Human: Canonicalization of 3D human model using Tensor Field Networks
• Teaching Assistant - 05/2021 - 06/2021
  University Cote d’Azur, Sophia Antipolis, France.
  • 3D Machine vision course for Master’s students.
• Machine Learning Engineer - 06/2020 - 09/2020
  Next Industries, Milan, Italy.
  • Machine learning applications for wearable gesture & motion controllers.
• Data Scientist Intern - 09/2019 - 03/2020
  Unicredit Services, Milan, Italy.
• Design and implementation of end-to-end applications to automate manual processes.
• Implemented an OCR web service with pre and post-processing modules to improve OCR quality.
• Worked on object detection, document classification, and entity recognition/extraction-related projects.

Skills

• Python, C++ , C , C# , .NET , Java , JavaScript , Matlab , Octave , Node.js , React / React Native , SQL , MongoDB , ROS , Git , Docker
• PyTorch , Tensorflow , Keras , Matplotlib , Scikit-learn , OpenCV , Pandas , MLflow , AWS , Cloud Computing , NLTK , Spacy , Jupyter
• Computer Vision , Deep Learning , Machine Learning , Data Science
• Languages - English, Bengali, Hindi, Italian, French

Publications

RGB-D Neural Radiance Fields: Local Sampling for Faster Training

Arnab Dey, Andrew I. Comport. RGB-D Neural Radiance Fields: Local Sampling for Faster Training

Mip-NeRF RGB-D: Depth Assisted Fast Neural Radiance Fields

Dey, A. and Ahmine, Y. and Comport, A.I., Mip-NeRF RGB-D: Depth Assisted Fast Neural Radiance Fields, Journal of WSCG, Volume 30 pages 34-43. DOI:10.24132/JWSCG.2022.5.

PNeRF: Probabilistic Neural Scene Representations for Uncertain 3D Visual Mapping

PNeRF: Probabilistic Neural Scene Representations for Uncertain 3D Visual Mapping. Y Ahmine, A Dey, AI Comport - arXiv preprint arXiv:2209.11677, 2022

Thesis

• A. Dey, Human activity and emotion recognition from RGB videos using deep learning. Politecnico di Milano, a Deep learning-based approach to recognize human activities and emotions from real-time RGB videos for robotics applications, Implemented using PyTorch.
• A. Dey, Automated region selection in images based on visual saliency. West Bengal University of Technology, Achieved automated region selection without prior knowledge and user interaction, Implemented using MatLab.

Teaching

3D Machine Vision

Awards

• Best Poster Award in Eurographics 2022 for RGB-D Neural Radiance Fields.
• Winner of E-Health Creathon by Innovation Center for Entrepreneurship of the University Cote d’Azur.