Chandisha Das

About Me

I'm a final year Computer Science Engineering student at Future Institute of Technology with a strong interest in artificial intelligence and machine learning, particularly in healthcare applications

My research at IIT Jodhpur involves developing deep learning models for medical image analysis, particularly in breast cancer classification and brain tumor detection.

My contributions to uncertainty-aware deep learning in medical diagnosis resulted in a paper acceptance at MICCAI: Deep-Brea3th 2025. This work highlights the role of AI in transforming medical diagnostics.

I'm passionate about creating AI solutions that drive meaningful improvements in daily life, combining technical expertise with an understanding of real-world challenges and human needs.

AI/ML & DL
Healthcare AI

Core Expertise

90%

Research in AI

Major Projects

Published Paper

Professional Journey

Indian Institute of Technology, Jodhpur

Research Intern

February 2025 – July 2025

Conducted cutting-edge research in medical AI under Dr. Deepak Mishra's supervision, focusing on multimodal deep learning for breast cancer diagnosis. Contributed to the development of uncertainty-aware cross-modal attention mechanisms that dynamically fuse ultrasound imaging features with clinical data (BI-RADS scores, patient demographics, morphological descriptors) for precise tumor classification.

Achievement: Research paper accepted at MICCAI 2025: 2nd Deep-Brea3th.

Smart India Hackathon 2024 Grand Finale

Team Lead & AI Developer

September 2024 – December 2024

Led development of a comprehensive real-time violence detection system for public safety. Integrated computer vision, gesture recognition, and GIS mapping technologies.

Impact: Achieved 92.43% accuracy in real-time threat detection through intelligent CCTV analysis.

Featured Projects

🔬 Breast Cancer Classification

Developed an advanced multimodal deep learning system for automated breast tumor classification, combining ultrasound imaging with clinical data to distinguish between benign and malignant lesions. This research project at IIT Jodhpur's Medical AI Systems (MAISys) lab contributed to a paper accepted at MICCAI 2025: 2nd Deep-Brea3th.

PyTorch Computer Vision Grad-CAM Medical AI Deep Learning PyRadiomics

🎯 Accuracy: 87.23% ± 6.98% | 📈 Recall: 98.31%

🛡️ Safety Monitoring System

Real-time violence detection system using advanced CCTV analytics. Incorporates gesture recognition, gender classification, and emergency response with GIS-based alerts.

Python OpenCV MediaPipe Flask TensorFlow GIS

🎯 Accuracy: 92.43% | ⚡ Real-time

🫁 Pneumonia Detection

AI-powered diagnostic assistant for detecting pneumonia from chest X-ray images. Optimized convolutional neural networks for high diagnostic accuracy.

TensorFlow Keras OpenCV CNN Medical Imaging

🎯 Accuracy: 94.65% | 🏥 Clinical Ready

🧠 Brain Tumor Analysis

Radiogenomic analysis for predicting MGMT promoter methylation in glioblastoma patients. Advanced multimodal MRI analysis using sophisticated CNN architectures.

MRI Analysis CNN Medical AI Radiogenomics Deep Learning

🏆 MICCAI Challenge | 🔬 Research Grade

Technical Skills

Programming

Python C/C++ SQL JavaScript

Data Science

Pandas NumPy Matplotlib Seaborn Jupyter

Tools & Platforms

Flask Git/GitHub Docker VS Code MediaPipe

Specializations

Computer Vision Deep Learning Medical AI NLP Research

AI/ML Libraries & Frameworks

TensorFlow/Keras PyTorch Scikit-learn PIL OpenCV MediaPipe Nibabel SimpleITK PyRadiomics dcm2niix

Let's Connect

Email

daschandisha@gmail.com

Phone

+91 ******1382

Location

Kolkata, West Bengal, India

Ready to push the limits of what's possible with artificial intelligence?

Let's connect and build something impactful together

Available for opportunities

🔬 Research Collaborations
💼 Full-time Opportunities
📚 Academic Discussions