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Learning & Improving
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Learning & Improving

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animikhaich/README.md

Typing SVG

🧐 About Me

πŸ‘‹ Hi there! I'm Animikh, a Machine Learning Engineer with a passion for Anime and Video Games. I'm currently working as a Computer Vision and Machine Learning Engineer at Moultrie - An EBSCO Company. Here, we're developing next-generation Computer Vision algorithms for Cellular Trail Cameras, aimed at enhancing wildlife monitoring.

I graduated with an MS in AI from Boston University, where I worked under Prof. Eshed Ohn-Bar at the H2X Lab. My research focused on end-to-end Autonomous Driving, specifically on closing the Sim2Real gap and developing offline and online driving evaluation metrics for my thesis.

Previously, I was the Computer Vision Engineer and Lead at Wobot.ai, where I spearheaded the development of a robust deep learning tech stack that powers real-time video analytics across hundreds of cameras worldwide.

I ❀️ building things and strongly believe that Multi-Modal Self-Supervised Learning is key to AGI 🀫. My areas of focus include Generative AI, Multi-Modal Learning, and more.

I'm always open to new opportunities and a good chat β˜•. Feel free to connect with me on LinkedIn or reach out at [email protected].

πŸ’» Tech Stack

Tools

Visual Studio Code Sublime Text Linux macOS Windows Google Chrome LaTeX Jupyter ChatGPT

Languages++

Python C++ JavaScript Dart Flutter Markdown HTML5 CSS3

Machine Learning & AI

PyTorch TensorFlow Keras OpenCV NumPy scikit-learn mlflow OpenAI Matplotlib

Web Development

Streamlit Flask FastAPI Nginx Replicate MongoDB

Cloud

AWS AWS S3 Azure Git Docker

πŸ“Š Some Stats

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πŸ”— Connect With Me

X LinkedIn Gmail Instagram Google Scholar ResearchGate

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  1. VidTune VidTune Public

    Forked from tensorsofthewall/VidTune

    VidTune: Tailored Music For Your Videos

    Python 1

  2. No-Code-Classification-Toolkit No-Code-Classification-Toolkit Public

    Containerized Tensorflow-based image classification training utility with Streamlit-based interface designed to choose between common architectures and optimizers for quick hyperparameter tuning.

    Python 8 3

  3. 3D-Text2LIVE 3D-Text2LIVE Public

    Zero-shot, text-driven appearance manipulation on multiple views of an object to generate 3D renderings.

    Python 3 2

  4. Semantic-Segmentation-using-AutoEncoders Semantic-Segmentation-using-AutoEncoders Public

    Lightweight and Fast Person Segmentation using Autoencoders (Trained Weights Included)

    Jupyter Notebook 20 7

  5. ECG-Atrial-Fibrillation-Classification-Using-CNN ECG-Atrial-Fibrillation-Classification-Using-CNN Public

    This is a CNN based model which aims to automatically classify the ECG signals of a normal patient vs. a patient with AF and has been trained to achieve up to 93.33% validation accuracy.

    Jupyter Notebook 47 19

  6. Deep-Convolutional-Background-Subtractor Deep-Convolutional-Background-Subtractor Public

    End-to-end CNN-based Autoencoder that can segment any objects even if it is out of the classes present in the training set.

    Jupyter Notebook 4 1