About me

As an AI Researcher at NeuroCare.ai, I work on managing and organizing datasets, conducting literature reviews, and developing deep learning algorithms. I also focus on implementing and testing these algorithms on large datasets to create reliable solutions.

Between 2022 and 2023, I was a Research Assistant at the Artificial Intelligence Diagnostics Lab. My work centered on 3D MRI analysis for brain tumor segmentation and treatment planning, ensuring data precision and developing tools in close collaboration with medical professionals.

In 2022, during my time as a Research Scholar at the National Center of Robotics and Automation, I contributed to defect detection projects using deep learning. I worked with engineers and developers to enhance model performance and was involved in a separate project on cloud resource allocation, gaining experience in research workflows and technical writing.

What i'm doing

  • Writing

    I have experience creating well-researched manuscripts, technical documents, and engaging blog content.

  • Research

    I conduct literature reviews, design experiments, and analyze data to draw meaningful conclusions.

  • Coding

    I have experience in developing algorithms, and building real-world solutions.

  • Data Management

    I curate and organize large datasets, ensuring they are accurate and accessible for analysis and model development.

Daniel lewis
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Daniel lewis

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Publications

  1. Deep Learning-Based Multiclass Instance Segmentation for Dental Lesion Detection

    2023, Healthcare (Basel). Doi: 10.3390/healthcare11030347. PMID: 36766922; PMCID: PMC9914729

    Authors: Fatima A, Shafi I, Afzal H, Mahmood K, Díez IT, Lipari V, Ballester JB, Ashraf I.

    Download Paper

  2. Advancements in Dentistry with Artificial Intelligence: Current Clinical Applications and Future Perspectives

    2022, Healthcare (Basel). Doi: 10.3390/healthcare10112188. PMID: 36360529; PMCID: PMC9690084

    Authors: Fatima A, Shafi I, Afzal H, Díez IT, Lourdes DRM, Breñosa J, Espinosa JCM, Ashraf I.

    Download Paper

  3. Internal defects detection and classification in hollow cylindrical surfaces using single shot detection and MobileNet

    2022, Measurement, 202, 111836

    Authors: Shafi I, Mazahir A, Fatima A, & Ashraf I

    Download Paper

Experience

  1. Artificial Intelligence (AI) Researcher

    NeuroCare.AI

    2024 - Present

    - Set up annotation tools, and preprocess data from organizations for efficient annotation.

    - Work closely with the AI team to develop algorithms, create data pipelines, and build visualizations to simplify development processes.

    - Prepare and maintain documentation for AI ethics and regulations compliance.

  2. Research Assistant

    Artificial Intelligence and Diagnostic Lab (AIDL), FAST-NUCES, Islamabad

    Nov 2022 - Oct 2023

    - Developed segmentation algorithms for brain tumor detection with team.

    - Presented our work to delegations, showcasing the progress and outcomes of the project.

    - Led a team of interns in developing AI algorithms for medical imaging.

  3. Research Scholar

    National Center for Robotics and Automation, CEME, NUST

    Oct 2021 — Oct 2022

    - Trained and optimized deep learning models for cylindrical surface defects for analysis.

    - Documented findings to improve defect detection and enhance industrial product longevity.

    - Assisted in manuscript preparation using LaTeX.

    - Presented research findings and maintained detailed experimental records.

Trainings and Seminars

  1. Trainer, Workshop on Computer Vision and Medical Imaging

    Aga Khan University, Pakistan

    2023

    Conducted a 3‐day workshop as a trainer at Aga Khan University, imparting expertise in medical image visualization, preprocessing, and standardization of raw 3D medical imaging datasets to medical professionals and researchers.

  2. Speaker, Seminar on AI in Medical Image Processing

    FAST-NUCES, Islamabad

    2023

    Featured as a speaker at an AI Seminar on medical image processing at FAST-NUCES, where I explained the step‐by‐step preprocessing of raw MRIs, discussed common challenges faced with real‐world datasets, and presented the practical techniques used to overcome these challenges.

Education

  1. MS Software Engineering

    National University of Sciences and Technology (NUST)

    2019 - 2022

    Thesis: An Automated Teeth Lesion Diagnosis System Based on Deep Learning

    Supervisors: Dr Hammad Afzal, Dr Imran Shafi

  2. BS Computer Science

    International Islamic University

    2014 - 2018

    Project Title: Automatic Currency Recognition System Using Image Processing

    Supervisor: Dr Sadia Afzal