I’m a Master’s graduate in Cognitive Science with a strong passion for Deep Learning, and Computer Vision. In my Master’s thesis, I explored advanced deep learning methods for fluorescence microscopy, focusing on AI-based denoising and reconstruction at low signal-to-noise ratios.
Alongside my academic journey, I have worked as a Research Assistant, Student Assistant, and Student Tutor, developing solid programming, debugging, and analytical skills. I’m eager to apply my knowledge to impactful projects in AI, GenAI, and Data Science.
- Programming Languages: Python, C++
- Deep Learning & Computer Vision: TensorFlow, PyTorch, Keras, OpenCV, Numpy, Scikit-Image
- Data Science & NLP: Pandas, Scikit-Learn, NLTK, Transformer Architectures, Generative AI
- Tools: Git, GitLab, Docker, Visual Studio, MLFlow
- Operating Systems: Linux, Windows
Demo [https://github.com/ArghaSarker/llm_project]
- Compared the base model vs full instruction fine-tuned model vs PEFT fine-tuned model.
- upcoming: RLHF and model distillation
🎓 Master’s Thesis: * AI-based Reconstruction and Denoising for Robust Structured Illumination Microscopy at Low Signal-to-Noise Ratios.*
Read my thesis here: [https://github.com/ArghaSarker/Mather-Thesis-]
Demo [https://github.com/ArghaSarker/RDL_denoising]
Demo [https://github.com/ArghaSarker/projection_upsampling_network]
- Developed a robust SIM reconstruction model to enhance image resolution using deep learning.
- Achieved improved reconstruction speed and quality compared to traditional Fourier-based methods.
- Application: Low SNR fluorescence microscopy data in bioimage analysis.
Demo [https://github.com/ArghaSarker/Data_augmentation_with_VAE]
- Built a VAE to generate synthetic microscopy data, supporting improved deep learning training.
- Helped address challenges with limited high-resolution datasets in bioimage analysis.
Demo - Not available due to company ownership.
- Collaborated with LMIS GmbH to develop a privacy-preserving solution based on GDPR.
- Focused on anonymization of license plates, faces, tattoos, texts, and screens using DL models.
Demo [https://github.com/madammann/SaccadicEyeMovementNET]
- Engineered a pipeline to fetch, preprocess, and generate data for image classification.
- Combined CNN and LSTM for spatio-temporal feature extraction.
- Investigated the use of reinforcement learning for visual signal classification.
Demo [https://github.com/ArghaSarker/COVID-19-Global-data-EDA-]
- Conducted data visualization and exploratory analysis on global COVID-19 data.
- Identified trends and correlations among variables using statistical methods.
- Generative AI with Large Language Models (LLMs)
- Email: [[email protected]]
- LinkedIn: [https://www.linkedin.com/in/argha-sarker-cogsci/]