Arijit De | Computational Modeling | Best Researcher Award

 

 

 

Mr Arijit De | Computational Modeling | Best Researcher Award 

Senior Research Fellow at  Jadavpur University ,Kolkata, India

Arijit De is a seasoned Machine Learning Engineer with over 6 years of expertise in the field. 🌟 His skills span data science, Python programming, and SQL, adeptly applied in projects using PyTorch, TensorFlow, and OpenCV. Arijit has a strong background in Computer Vision and Natural Language Processing, contributing to end-to-end ML solutions. Currently, he leads deep learning pipeline development at mVizn Pte. Ltd., focusing on semantic segmentation of 3D point clouds. His career includes impactful roles at TCS and as a TCS Research Fellow at Jadavpur University, where he developed innovative ML solutions for healthcare and data quality enhancement projects.

Profile:

Scopus 

📚 Education:

Arijit De has pursued an extensive academic journey culminating in a pending PhD from Jadavpur University, focusing on cutting-edge research in Machine Learning. He holds an M.Tech in Computer Science & Engineering and a B.Tech from Techno India, Kolkata, showcasing his academic prowess with impressive GPAs. Arijit has augmented his academic achievements with certifications such as Deep Learning and TensorFlow from Deeplearning.ai, underscoring his commitment to staying at the forefront of technological advancements in AI. His academic and certification credentials solidify his expertise in applying theoretical knowledge to practical ML solutions, driving innovation in the field.

 

👨‍🏫 Professional Experience

As a Machine Learning Engineer at mVizn Pte. Ltd., Arijit spearheads the development of DL pipelines for semantic segmentation, optimizing data processing and deploying models in web applications. His tenure at TCS Research Fellow focused on Alzheimer’s disease classification and brain tumor detection using advanced ML techniques.

 

Skills and Technologies

Arijit’s proficiency extends across Python, Java, C++, and SQL, alongside technologies such as PyTorch, TensorFlow, and OpenCV. He leverages cloud platforms like Microsoft Azure and possesses theoretical expertise in Deep Learning, Computer Vision, and NLP.

 

 

Research focus:

Arijit De’s research focus is likely centered around the application of machine learning (ML) and data science techniques to solve real-world problems. Specifically, his interests may include:

  1. Machine Learning Development: Arijit has extensive experience in developing end-to-end ML solutions using frameworks like PyTorch, TensorFlow, and Scikit-Learn. His research may involve advancing ML algorithms, improving model performance, and exploring novel applications of ML in various domains.
  2. Computer Vision: Given his proficiency in OpenCV and experience in Computer Vision principles, Arijit may be researching topics related to image and video analysis, object detection and recognition, and image processing techniques using ML.
  3. Natural Language Processing (NLP): With skills in NLTK and likely other NLP tools, Arijit may be interested in research related to text analysis, sentiment analysis, language modeling, and other NLP applications.
  4. Data Analysis and Visualization: Arijit’s expertise in Python and SQL for data analysis and visualization suggests he may also be involved in research focused on deriving insights from large datasets, exploratory data analysis, and developing visualization techniques to communicate complex data.
  5. Cloud Computing and Deployment: Knowledge of deploying ML applications on cloud platforms indicates research interest in scalable and distributed ML systems, cloud-native ML architectures, and optimizing ML models for deployment in cloud environments.
  6. Project Management and Risk Management: Arijit’s background in planning, estimation, and risk management of projects suggests a practical focus on applying ML and data science methodologies in industry settings, ensuring project success and mitigating risks.

Citations:

Citations: 42 📑

Documents: 7 📄

h-index: 2📈

 

Publication Top Notes: