About me

I’m an applied AI researcher and engineer focused on building intelligent systems that work reliably in real-world settings. My experience spans natural language processing, computer vision, and machine learning, with a strong emphasis on turning raw, messy data into systems that support real decisions rather than isolated model demos.

My background includes academic research, AI-driven product development, and data-centric engineering. I take a Python-first, systems-oriented approach to problem solving, with end-to-end ownership across the AI lifecycle from data ingestion and model design to evaluation, deployment, and iteration. I care deeply about clarity, robustness, and measurable impact, especially when models are part of larger software systems.

Curious by nature and grounded in engineering reality, I enjoy working at the intersection of research, system design, and practical constraints, where thoughtful AI design makes a tangible difference.

What I Specialize In

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    Language & Vision AI

    Designing models that understand language and interpret visual data using NLP, computer vision, and deep learning.

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    Python-Based AI Engineering

    Building scalable AI systems in Python, including model pipelines, APIs, and automation workflows.

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    Research & Prototyping

    Turning research ideas into working prototypes through rapid iteration and clear evaluation.

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    End-to-End AI Systems

    Developing full-cycle AI systems from data ingestion to deployment within larger software systems.

Daniel lewis
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Daniel lewis

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Resume ↗

Experience

  1. AI Venture Analyst Intern @ Untapped Ventures

    Jul 2025 - Present

    Built an AI-driven avatar interface that simulates founder meetings and captures structured deal data via dynamic conversations.
    Automated deal scoring using uploaded investor rubrics, reducing manual evaluation time and improving intake quality.

  2. Student AI Researcher @ Center for Innovation through Visualization and Simulation, Purdue

    Jan 2025 - Present

    Designed an NLP-driven chatbot using local LLMs and RAG pipelines to automate safety reporting, cutting manual data processing by over 60%.
    Built a real-time computer vision system using YOLOv5 and Faster R-CNN to detect PPE violations and unsafe behavior in industrial environments.

  3. AI / ML Intern @ TechXi

    Dec 2023 - Apr 2024

    Developed a GAN-based tool to colorize black-and-white images using U-Net, and trained a reinforcement learning bot to play Super Mario in OpenAI Gym.
    Also built a multi-disease diagnostic assistant using VGG-19 and classical ML models to support healthcare prediction tasks.

  4. Undergraduate Research Fellow @ Charotar University of Science and Technology

    Aug 2023 - May 2024

    Worked on a research study comparing the performance of transfer learning models on synthetically augmented images.
    Helped streamline collaboration across multiple supervisors while focusing on AI applications in medical imaging.

  5. Data Science and Machine Learning Intern @ BrainyBeam Technologies

    May 2023 - Jun 2023

    Built a medical insurance cost prediction tool using LASSO and Decision Tree models.
    Deployed machine learning models, including an image classifier, with a 13% accuracy improvement using CI/CD pipelines for seamless integration and deployment.

  6. Python Intern @ Webbrains Technologies

    May 2022 - Jul 2022

    Created a Django-based e-commerce website for a local bakery with features like cart, wishlist, and order tracking.
    Worked on backend integration with MySQL and implemented user authentication from scratch.

Leadership & Academic Contributions

  1. Peer Reviewer @ Neural Computing and Applications, Springer Nature

    2024 - Present

    Reviewed a submitted research paper on applied AI for a Springer-indexed journal.

  2. Reviewer @ International Journal of Computing and Digital Systems

    Dec 2023 - Present

    Assessed research papers in machine learning and deep learning as part of the peer review process.

  3. Lead Student Coordinator @ Training and Placement Cell, Charotar University

    Jul 2025 - Present

    Led campus placement coordination, company liaison, and student recruitment logistics.

  4. Student Chair @ ACM Student Chapter, Charotar University

    Aug 2021 - Aug 2022

    Directed a 30-member student body and organized workshops and tech events to promote peer learning.

Education

  1. Purdue University

    2024-2026

    M.S. in Computer Science with specialization in Artificial Intelligence

  2. Charotar University of Science and Technology

    2020-2024

    B.Tech in Computer Science and Engineering

My skills

  • Programming:

    Python, C++, C, Java, JavaScript, TypeScript, SQL, R, Bash

  • Machine Learning & AI:

    TensorFlow, PyTorch, Keras, Scikit-learn, Transformers, Ollama, LangChain, Pandas, NumPy, Matplotlib, Seaborn, LLMs, RAG Pipelines, SVM, Decision Trees, Random Forest, Naive Bayes, Regression

  • Computer Vision & NLP:

    OpenCV, NLTK, VGG-19, YOLOv5, Faster R-CNN, CNNs, GANs, Lip Reading Models, Text Classification, NER, Image-to-Text

  • Frameworks & Development:

    Flask, FastAPI, Django, Streamlit, REST APIs, HTML, CSS, Jinja, Bootstrap

  • DevOps & Tools:

    Git, Docker, Linux (Ubuntu, Kali), CI/CD, Jupyter, VS Code, Google Colab, Power BI

  • Databases & Cloud:

    MySQL, PostgreSQL, MongoDB, Firebase, Oracle DB, AWS (EC2/S3), NoSQLb

research

Contact

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