The MSDS Research Project is a critical component of the MSDS program, designed to allow students to apply theoretical knowledge to practical problems through extensive research. This project fosters the development of independent research skills, contributing valuable insights to the computer science field. For more details, visit MSDS Research Project
Submissions from 2023
Workflow Automation of MIS Generation in Financial Industry, Muhammad Huzaifa Alam
Web Scraping and Sentiment Analysis of Foodpanda Reviews, Mohammad Naseer Batla
Creating a Big Data pipeline for E-commerce data, Muhammad Usman Hasan
Customer Segmentation / Targeting & Customer Management using Classification & Machine Learning(ML) Models, Faizan Jalil
Enerythm - Cloud Based Energy Distribution Management System with Real-Time Analytics and Machine Learning Insights, Tahami Kalim
Application of Machine Learning Techniques for classification of Nonlocal Correlations, Mohammad Yousuf Mehmood
Assessing Neural Machine Translation for English-Urdu with LSTM, GRU, And Transformer, Syed Huzaifa Nafees
On Leveraging Quantized LLMs for Sentence Boundary Prediction in Transcribed Urdu Text, Syed Asad Rizvi
Mapping ICD-10 Codes to Clinical Notes: A comparative analysis of Pre-Trained Language Models and SNOMED-CT MEDCAT, Syed Bilal Rizwan
A Survey on Prior Probability Shift Adaptation, Syed Hassaan Saleem
E-Commerce products form Automation using Video Description, Arslan Shaikh
Submissions from 2022
Creating Customer Persona for Grocery Delivery Service, Waleed Abdul Ghani
Identifying Central Nodes in Unweighted and Undirected Graphs – World City Networks, Syeda Ayesha
Identifying Central Nodes in Unweighted and Undirected Graphs – World City Networks, Syeda Ayesha
Anomaly detection using GMM, Arman Bari
Development of Analytics Pipeline for E-commerce, Syed Junaid Haqqani
Simulation of CI/CD Pipeline (MLOPS), Babar Bin Asif Khan
Application of Machine Learning techniques for classification of nonlocal correlations, Yousuf Mehmood
Influence maximization in City Network using Supervised Machine Learning and Deep Learning, Hifza Moin
Real-Time data ingestion with Metadata Management using Apache Kafka and Amundsen by Lyft, Rabiya Owais
Real-Time Data Ingestion with Metadata Management using Apache Kafka and Amundsen by Lyft, Rabiya Owais
Persona development using Clutser Analysis in Python, Ayman Rehan
