Minahil Irshad · imagine-talent

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Academic

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Year

2019

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Skills

Python, PyTorch, Figma, Flask, Federated Learning, Cryptographic algorithms, Web Interface Development

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.

Group Members: Minahil Irshad (i19 - 2178)

CURATIO MORBI
A Cryptographically Secured Federated Learning for Healthcare Consortia
Objective: A centralized federated learning model that is secured by using cryptographic algorithms.
Workflow: Logs data into the local dataset -> Extracts weights -> Uploads encrypted local model -> Calculates aggregated model -> Shares aggregated model -> Prognosis of a disease
Timeline: SEP-OCT (Literature Review, Implementing the Federated Learning model on our dataset) | NOV-DEC (Implementing Cryptogram algorithm) | FEB-MAR (Developing the Web Interface, Integration of FL model, Cryptogram algorithm and the Web Interface) | APR-MAY (Enhancements, Documentation)
Tools & Technologies: Python, PyTorch, Figma, Flask
Supervisor: Ms. Hina Binte Haq
Co-Supervisor: Dr. Zainab Abaid

AI enrichment

Minahil Irshad is a student who worked on a group project developing a cryptographically secured federated learning system for healthcare. The project involved implementing machine learning models, cryptographic algorithms, and a web interface using Python, PyTorch, and Flask.

Skills (AI)

["Python", "PyTorch", "Flask", "Figma", "Federated Learning", "Cryptography", "Web Development", "Machine Learning"]

Status: ai_done

Provenance

Source file: FAST - School of Computing -Graduate Directory-2023.pdf
From job #14 page 291
Created: 1778140212