United Kingdom
- SSC Module Skin Metagenomics (A) - SSC Module Arabic (A) - Year 6 Certificate of Merit (Top 20% of cohort) Activities and Societies: -UCL Mixed Martial Arts Club member -UCL Dodgeball Society Men’s 1st Team player -UCL Pakistan Society Sports Officer -UCL Vascular Surgery Society Media Officer
I had the opportunity to immerse myself in the dermatology department at Chelsea & Westminster Hospital where I gained exposure to an array of cutaneous disease subspecialties. • Shadowed pediatric clinics, where I observed complex genetic dermatological cases (e.g. tuberous sclerosis, Gorlin syndrome) and rare skin diseases (e.g. MAGIC syndrome). • I refined my skills in presenting skin lesions using appropriate dermatological terminology and identifying benign congenital lesions such as smooth muscle hamartomas • Attended multidisciplinary Mohs-Plastic surgery planning sessions, enhancing my understanding of combined therapies e.g radiotherapy, Mohs surgery and vismodegib • At hair loss clinic I assisted with charting patients on emerging therapies for alopecia areata e.g. ritlecitinib • Regularly assisted dermatology residents during acute inpatient on-call, following complex cases with multisystem overlap from initial presentation through to diagnosis and management (e.g. drug reactions). • Sat in male genital dermatology clinic, gaining exposure to genital dermatoses including lichen sclerosus and their varied clinical presentations.
As a representative for Module ABC Rotations at the Royal Free Hospital, I actively listened to fellow medical students, leveraging their feedback gathered through Google surveys and group chat discussions and forwarding data to the medical school.
In my role as a research assistant in the Satsuma Lab at the UCL Centre of Medical Image Computing, generously funded by the BALR, I honed my pattern recognition abilities to a remarkable level, equipping me with a discerning eye for intricate details—an asset invaluable for any future image segmentation work. - Visually analysed and wrote descriptions for over 600 lung CT scans. - Through hands-on experience and training by my supervisor consultant radiologist, I learnt how to recognise numerous morphologies in lung structure, such as atelectasis, emphysema, honeycomb cysts, traction bronchiectasis, pleural effusion, scoliosis, tree in bud, infection etc. - Gained proficiency with Linux syntax, and segmentation software such as: 3D Slicer, ITK-Snap - Learnt how to perform data analysis using python programming techniques. - Used the deep learning architecture nnU-net to create detailed 3D airway models from CT scans of patients with bronchiectasis, and cystic fibrosis. - Used metrics to quantify segmentation accuracy and comparing them to current clinical outcome measures such as FEV1 and radiologist CT scores.