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padmajaabaskar/README.md

👾Hey hi, Padmajaa here!

🩺 Biomedical Engineer | 💻 AI in Healthcare Enthusiast | 🔬 Data Scientist | 🛠️ Tech Creator

🧠 Who Am I?
I’m a pre-final year Biomedical Engineering student on a mission to blend AI, data science, and biomedical innovation to reshape healthcare. I thrive at the intersection of machine learning and medical technology, building intelligent systems that decode disease patterns, optimize diagnostics, and transform patient care.

🚀 What Drives Me?
Designing deep learning pipelines for high-impact diagnostic models, from early cancer detection to cardiovascular risk assessment.
Extracting insights from high-dimensional biological data using advanced statistical models and cutting-edge bioinformatics tools.
Pushing the boundaries of biomedical device design with real-time, data-driven systems that predict, prevent, and personalize patient care.

💻 Tech Arsenal:
Programming: Python, R, C, Embedded C, Assembly
AI & ML: TensorFlow, Keras, OpenCV, Scikit-learn, ARIMA, Grad-CAM, LRP
Data Science: EDA, Time-Series Analysis, Predictive Modeling, Feature Engineering, Signal Processing
Biomedical Tools: AutoCAD, COMSOL, MATLAB, PyRx, AutoDock Vina, DESeq2
Clinical Know-How: Next-Gen Sequencing, Medical Device Calibration, Regulatory Compliance (ISO 13485)

🧪 My Projects:
👁️ Non-Contact IOP Estimation Device: Built a head-mounted ESP32-CAM device with real-time image processing to estimate intraocular pressure using applanation dynamics.

🫀 Carotid Artery Stenosis Detection: Developed a DNN with Grad-CAM and LRP for explainable ultrasound analysis, achieving 87% accuracy.

🦠 Pancreatic Cancer Genomics: Ran RNA-Seq and molecular docking studies, uncovering 200+ potential therapeutic targets.

🔥 Sterilization Forecasting: Reduced sterilization cycle variance by 15% using ARIMA time-series modeling for high-throughput medical environments.

🔎 Breast Cancer Detection: Achieved 94% sensitivity in microcalcification detection through advanced image segmentation.

🎯 What I’m Aiming For:
To engineer smarter AI systems that improve diagnostic speed and accuracy.
To push the frontiers of personalized medicine through predictive analytics and real-time bioinformatics.
To merge my biomedical knowledge with cutting-edge AI to create impactful healthcare tech.

🎨 Fun Facts About Me
I have a knack for finding hidden patterns in messy biological data.
I’m a creative coder who sees code as a form of art.
I lead branding for Yuva SREC, balancing my technical pursuits with a creative edge.

🌐 Socials:

LinkedIn email

💻 Tech Stack:

AssemblyScript C Python R Azure Google Cloud Adobe Premiere Pro Canva Sketch Up Keras Matplotlib mlflow NumPy Pandas Plotly PyTorch scikit-learn TensorFlow Scipy GitHub Arduino Docker Power Bi Raspberry Pi

📊 GitHub Stats:



✍️ Thought Process.log

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  1. Early-Detection-of-Breast-Cancer Early-Detection-of-Breast-Cancer Public

    Micro-calcifications are one of the key indicators of early breast cancer in mammograms. Our aim is to utilize region-based segmentation and classification method to detect micro-calcifications in …

    Python

  2. Measurement-of-UV-Exposure-over-Human-Skin Measurement-of-UV-Exposure-over-Human-Skin Public

    The measurement of UV exposure over human skin serves as a fundamental aspect in assessing the risk of skin damage, including sunburn, premature aging, and increased risk of skin cancer. In this ex…

    C++

  3. Non-Contact-Intraocular-Pressure-IOP-Measurement-Device Non-Contact-Intraocular-Pressure-IOP-Measurement-Device Public

    This project aims to develop a portable, non-contact device for Intraocular Pressure (IOP) measurement using an ESP32-CAM module. By utilizing real-time image processing, it measures corneal deform…

    Python 1

  4. Optimization-of-Medical-Instrument-Sterilization-Process Optimization-of-Medical-Instrument-Sterilization-Process Public

    This project optimizes medical instrument sterilization using machine learning by analyzing parameters like temperature, pressure, and contamination levels. Predictive models enhance efficiency, re…

    Python