Experience

1. AI & ML Expert

   WearDOXX September 2025 – Present
   • 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 September 2024 – Present
   • 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 May 2024 – September 2024
   • 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 January 2024 – Present
   • 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