At MI, I use the data that our digital products produce to create artificial intelligence models that enhance DTx efficacy and user experience. I also generate peer-reviewed studies that probe the robustness and accuracy of our practices in AI.More broadly, I am a researcher and developer in the field of AI and medical imaging (especially deep learning and deep reinforcement learning). Although I am deeply passionate about improving and developing novel AI algorithms and models, I always focus on using AI to boost human wellbeing.Before joining MI, I worked as Oracle database and SUN Solaris LINUX system administrator at Yemen Financial Services Co (YFSC). After some time as a software engineer, I decided to pursue my higher studies in China and obtained my MEng in deep learning-driven process minding from Shanghai Jiao Tong University.My diverse work experience from administrating a sensitive financial database to recovery techniques has made me a data-aware expert. I also hold degrees in Comp Sci and IT from Sana’a Community College in Yemen and the University of Modern Sciences, respectively. At Sana’a, my thesis described the creation of AI that predicts the best sport that one might fit into based on fingerprints, and was the top-ranked thesis of the year.
Our software uses facial photoplethysmography (PPG) and deep neural networks to personalise safe and effective treatments, while providing real time data on real world efficacy. The resulting gamified "measure-treat-measure" system has been clinically proven to reduce the risk of mental illness in cancer patients, as well as alleviate anxiety in young adults when compared to placebo in multiple clinical trials.
AI-based theragnostics every patient can access.
Digitally-enabled pharmacotherapy, theragnostics and mental health endpoints.
Giving policyholders access to clinically-validated mental wellness tools.
Supporting personalised healthcare on site and at home.
Effective and accessible healthcare for every human.