Experience

  1. AI & ML Expert

    WearDOXX
    • Researching, developing, and implementing machine learning and deep learning models for healthcare applications
    • Responsible for data preprocessing, model design, optimization, training, evaluation, and deploying AI solutions into production
    • Collaborating with cross-functional teams to integrate AI technologies into real-world healthcare products and services
  2. Deep Learning Research Assistant

    Mitacs
    • Engineering and rigorous validation of AI-powered biomedical systems for clinical translation
    • Designing data pipelines, curating multimodal datasets, and implementing deep learning architectures for biomedical signals and imaging
    • Conducted end-to-end experimentation from hypothesis formulation to model training, benchmarking, and deployment
    • Collaborating with clinicians and engineers to refine system requirements and ensure scientific rigor in research outputs
  3. Deep Learning Associate Researcher

    Scanbo
    • Contributed to innovative healthcare solutions through advanced AI technologies
    • Developed AI models for diagnostic methods enhancement and patient care improvement
    • Performed data analysis, model development, and Collaborated with multidisciplinary teams on cutting-edge healthcare initiatives
  4. Graduate Research Assistant

    York University
    • Integrated Diagnostic Suite: Engineered a comprehensive AI-driven platform facilitating volumetric 2D/3D segmentation, multi-class lesion classification, and automated structured reporting for seamless clinical workflow integration
    • Advanced Segmentation Models: Proposed a novel deep learning framework integrating architectural modifications to U-Net and a custom-designed loss function, demonstrating SOTA performance across diverse medical benchmarks
    • Efficient 3D Reconstruction: Developed a pipeline for 3D volume synthesis by fusing 2D planar predictions via lightweight neural networks, optimizing the trade-off between fidelity and latency
    • Adversarial Augmentation: Formulated adversarial strategies to mitigate data scarcity, significantly improving inference stability in data-limited scenarios
    • Optimization Algorithms: Implemented Particle Swarm Optimization (PSO) algorithms to enhance feature selection and convergence speed in complex medical dataset analysis
    • Neuro-Diagnostic Wearable: Prototyped a non-invasive smart goggle device for early screening of neurodegenerative disorders (Alzheimer’s, Parkinson’s) via multi-modal retinal and gait analysis
    • Onco-Diagnostic Platform: Designed a wearable biodiagnostic sensor for early breast cancer detection by analyzing inflammatory biomarkers in sweat samples
    • Rapid Testing Systems: Developed electrochemical multiplexed lateral flow platforms for high-precision quantification of critical blood parameters
Skills & Hobbies
Technical Skills
Python
PyTorch & TensorFlow
Medical Imaging & CV
Optimization Algorithms
C/C++ & Java
Soft Skills
Leadership & Communication
Analytical Problem Solving
Creativity & Innovation
Interdisciplinary Collaboration
Hobbies
Traveling
Hiking
Fitness
Photography
Reading
Fishing
Awards
Ph.D. Fellowship
York University ∙ January 2024
Awarded full funding for doctoral studies at York University covering tuition and living expenses (2024–Present)
Mitacs Accelerate Internship
Mitacs ∙ January 2024
Granted two-year research internship with $90,000 CAD funding to develop AI-driven medical technologies for clinical applications (2024–2026)
Distinguished M.Sc. Student Award
University of Tehran ∙ September 2023
Outstanding academic achievements, holding the Second-rank position in major (University of Tehran)
Member
The National Organization for Development of Exceptional Talents (NODET) ∙ Present