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Achievement: Pull Shark

Achievements

Achievement: Pull Shark

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reeha-parkar/README.md

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🔍 About me

  • MSc Artificial Intelligence at King’s College London (2024–25)
  • ML Research Intern at King’s Forensics — Applying AI to enhance forensic science methodologies
  • Dissertation: Enhancing Contrastive Reconstruction for Multimodal Emotion Recognition with Temporal Preservation
  • Former Business Analyst (NVIDIA Practice, Quantiphi) — Designed AI solution architectures and adoption roadmaps for global enterprise clients
  • Experienced in both enterprise AI consulting and building end-to-end ML systems (GenAI, NLP, Multimodal Learning, RAG, HPC)
  • B.E. Electronics Engineering with AI/ML Specialization, D. J. Sanghvi College of Engineering, Mumbai

🚀 Ongoing . . .

  • Currently exploring Agentic RAG systems — integrating retrieval, orchestration, and evaluation for robust GenAI workflows
  • Passionate about bridging applied AI research with real-world deployment, creating scalable and impactful systems

📸 Snapshot

GitHub Streak

⚙️ Tech stack

Languages

Python C C++ MATLAB SQL Bash

AI, Gen AI & LLMs

PyTorch TensorFlow Keras Scikit-learn NumPy Pandas Matplotlib
Hugging Face LangChain Ollama LangGraph FAISS OpenCV SpaCy

Tools & Frameworks

FastAPI Flask Streamlit AWS MLflow Git Linux

Connect with me on LinkedIn:

LinkedIn

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  1. multimodal-emotion-recognition multimodal-emotion-recognition Public

    A comprehensive implementation of multimodal emotion recognition using the Cross-Modal Adaptive Representation with Attention Transformer (CARAT) architecture, featuring variable-length temporal pr…

    Jupyter Notebook 1 1

  2. incident-intelligence-system incident-intelligence-system Public

    An AI pipeline to process industrial incident reports (PDF/DOCX and images). It uses Hugging Face Transformers and PyTorch to extract summaries , analyze images , and classify operational risks int…

    Python

  3. FasTEX-KCL FasTEX-KCL Public

    Automated textile fiber classification using FTIR spectroscopy and machine learning. Achieves 98.5% accuracy distinguishing natural vs man-made fibers and 95.8% accuracy for multiclass identificati…

    Jupyter Notebook 2

  4. attendance-quality-analyser attendance-quality-analyser Public

    Web application project to capture students' attendance and engagement level as a part of IBM AIML Specialization.

    Python 1 2

  5. samsemo samsemo Public

    Forked from pawel-bujnowski/samsemo

    Multimodal experiments on the SAMSEMO dataset featuring cultural analysis, BERT for text emotion recognition, and Wav2Vec2 audio embeddings.

    Jupyter Notebook

  6. trmf-with-customer-lifetime-value-modeling trmf-with-customer-lifetime-value-modeling Public

    Python