At SUNY Buffalo, my research addressed practical human needs – such as effective rehabilitation for ageing related disability such as Stroke and Parkinson’s disease. A combination of clinical statistics and mobile programming is used to enhance their lifestyle.

During my initial years of grad school, I worked on developing energy efficient architectures for 3D Printers.

If you are looking for the supplementary material such as code, demo, presentation slides, poster, etc. associated with each study, please click on the corresponding publication link.

  • Concerning Geriatrics

    Towards Pervasive Monitoring

    A quick, coarse and short study to identify whether skeleton-extracting Deep Learning models can reliably monitor the Parkinsonian Gait on publicly available videos: BHI18

    New Approaches for Stroke Rehabilitation

    Collaborated with Dr. Feng Lin to write code for the smart-mat employed in his study concerning Upper Extremity Rehabilitation: WH16

  • Concerning 3D Printers

    Reducing the energy consumption of 3D Printer

    Motivating the problem of high energy consumption in 3D Printers: APSys 16

    Solution to reduce energy consumption by 25%: ASPLOS 17