amulyamat Goto Github PK

I'm a master's student @

pursuing a degree in Aritifical Intelligence Engineering in Biomedical Engineering. My passion lies at the intersection of AI and healthcare, where I aim to revolutionize biotech and medtech through innovative machine learning solutions. My academic journey has equipped me with a comphensive skill set, including proficiency in programming languages, and expertise in AI frameworks like OpenCV, PyTorch, TensorFlow, PySparkML, and Scikit-Learn. I am well-versed in a wide range of machine learning techniques from traditional methods like Random Forest and XGBoost to more complex models such as CNNs, GNNs, ResNET, and GANs, all of which underscore my capability to tackle intricate challenges in data science and machine learning.

I am deeply motivated by the potential of AI to transform patient care, drug discovery, and disease diagnosis. My goal is to leverage my knowledge and skills to push the boundaries of what's possible in healthcare and biotech, making meaningful contributions to the future of medicine.

Programming Languages Python, MATLAB, C, C++, SQL, R

Machine Learning Frameworks PyTorch, TensorFlow, Keras, Scikit-Learn, River, SHAP, MNE, PySpark ML

Data Manipulation & Vizualization Tools Pandas, Numpy, Matplotlib, Seaborn, Plotly, PowerBI, Tableu, Excel

Cloud Computing Services AWS (EC2, S3, Lambda, CloudWatch), GCP, Snowflake

1. Cell classification through Raman Spectroscopy
2. Caffeine Classification based on EEG signals
3. Breast MRI classification
4. Seizure detection through EEG signals
5. BCI EEG signal machine learning implementation
6. Classification of protein-bonding affinity [in progress]