Multi-Label retinal Disease Classification
Summary
Utilized MuRed dataset with 20 disease class labels. Implemented DenseNet201 as the base model with Multi-Scale Fusion Module (MFSM) and Transformer architecture. Achieved ML AUC of 0.94
About
Work
IIT INDORE
Summary
Classifying building damage levels in short time from satellite imagery for rapid disaster response.
Highlights
Classifying building damage levels in short time from satellite imagery for rapid disaster response.
IIT HYDERABAD
Summary
An open-source Python software for viewing, processing, and classifying medical images with a modular GUI and future integration of deep learning models.
Highlights
An open-source Python software for viewing, processing, and classifying medical images with a modular GUI and future integration of deep learning models.
Rappo
Summary
Developed a QA system using LangChain, Google Generative Al, and FAISS. Processed data in documents and created a vector database for efficient retrieval. Created this FAQ system for a service based startup Rappo.
Highlights
Developed a QA system using LangChain, Google Generative Al, and FAISS.
Processed data in documents and created a vector database for efficient retrieval.
Created this FAQ system for a service based startup Rappo.
Volunteer
AMU ML Club
|R&D Team Member
→
ZFR SAEI
|Managment Team Member
→
Summary
Was part of management team which secured 4th rank in procurement event of Formula Bharat Pi-EV competition.
Highlights
Was part of management team which secured 4th rank in procurement event of Formula Bharat Pi-EV competition.
Education
Aligarh Muslim University (ZHCET)
B Tech
Artificial Intelligence
Christ Church College
Class XII (ISC)
Christ Church College
Class X (ICSE)
Skills
Machine Learning
KNN, SVM, K-Means, Regression, Decision Tree, PCA, LDA.
Deep Learning
Transformers, NLP, BERT, VIT.
Programming Languages
Python, C/C++.
NLP
LangChain, RAG.
Miscellaneous
Optimization, Statistical Learning, Git, FAISS, Preprocessing, Visualization, Clustering, Generative Al.
Soft Skills
Good communication, management and presentation skills, critical thinking, problem solving, leadership skills..
Projects
IPL Win Probability Predictor
Summary
Used IPL_Data_Set (2008-2019) for prediction modeling Data cleaning, feature extraction and implemented One-Hot Encoding and Logistic Regression in a pipeline. Achieved an accuracy score of 80%.