Kopil Das

Kopil Das

AI Enthusiast | Machine Learning & Deep Learning Researcher | Passionate about Medical Diagnosis & Computer Vision Projects

About Kopil Das

Welcome to my personal website! I am Kopil Das, a passionate researcher and software engineer with a deep interest in Artificial Intelligence, specifically focusing on deep learning applications in medical diagnosis. My academic journey began with a B.Sc. in Computer Science and Engineering from North East University Bangladesh (NEUB), and I am currently involved in cutting-edge research at the CRC Research Centre on the project titled “Haematological Disorders Classification from CBC Data using Autoencoder Enhanced Semi-Supervised Learning with Ensemble Techniques and XAI.”

🧑‍🔬 Research Experiences

Areas of Expertise

  • Machine Learning & Deep Learning: Specializing in the development and implementation of algorithms for medical diagnostics, including pneumonia detection and eye disease identification using X-ray and retinal images.
  • Python Programming: Proficient in building AI models using Python libraries such as TensorFlow, PyTorch, and Scikit-learn.
  • Research & Innovation: Actively working on research projects and exploring innovative solutions in medical AI.

Ongoing Research

I am currently leading research on the following topics:

  • PIK3CA-Mutant and Wild-Type Endometrial Cancer’s Comparative Interactomics Analysis Using STRING PPI Networks and TCGA–GTEx Expression.: Analysing PIK3CA-Mutant and Wild-Type theough PPI network
  • Haematological Disorders Classification from CBC Data using Autoencoder Enhanced Semi-Supervised Learning with Ensemble Techniques and XAI. Classifing nine hematological diseases.
  • Two-Stage Noise-Reduced Pneumonia Detection in Chest X-Ray Images Using Denoising Autoencoder–CNN Integration. Utilizing autoencoder approach to classify noisy madical images.

Academic Achievements

  • Thesis Project: Using Machine Learning and Deep Learning to Identify Pneumonia from Chest X-ray Images (2024)

👩‍💻 Technical Skills

  • Programming Languages: Python, C, C++, Java, JavaScript, TypeScript, R (basic)
  • DS & ML Tools (Python): NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, Keras, TensorFlow, Pycaret, PyTorch
  • ML Techniques: Normal ML Methods, Deep Learning, NLP, Computer Vision, Graph Neural Networks, Explainable AI, Robust Modeling, etc.
  • DS Techniques: EDA, Hypothesis Testing, Sampling, Statistical Testing, Correlation Analysis and Inference
  • Data Analysis: MS Excel, SAS, Tableau, Power BI
  • IT Automation: Automation in MS Word, PowerPoint, Excel, Google Sheets, Adobe Photoshop, Illustrator, Python-based Photo Manipulations
  • Computer Vision: Image processing, object detection, augmention
  • Deep Learning: Image classification, and natural language processing
  • Documentation and Illustration: LaTeX, MS Office

Get in Touch

I am always eager to collaborate on research projects, exchange ideas, and learn from others. Feel free to reach out to me through the following channels:

“Bringing innovative AI solutions to life through research and collaboration.”