Samar Afroz

AI Researcher

Delhi, India0 mo experience

Key Highlights

Achieved 94% accuracy in thyroid cancer detection.
Proficient in multiple programming languages and frameworks.
Passionate about healthcare technology innovations.

Stackforce AI infers this person is a Healthcare-focused Machine Learning Engineer with strong programming skills.

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Skills

Core Skills

Machine LearningDeep LearningComputer Vision

Other Skills

Analytical SkillsArtificial Neural NetworksBatch NormalizationC (Programming Language)C++CNNCode ReviewCommunicationComputer EngineeringConvolutional Neural Networks (CNN)Data StructuresData Structures and AlgorithmsEnglishImage ProcessingJava

About

I am Samar Afroz, a dedicated 3rd-year IT major student at DTU. Passionate about cutting-edge technologies, I specialize in machine learning, artificial intelligence, deep learning, and image segmentation for medical applications. Proficient in Java, C++, C, and Python, my skill set extends to encompass data structures and algorithms. I strive to contribute innovative solutions at the intersection of healthcare and technology. Eager to explore, learn, and make a positive impact through my journey in the world of computer science.

Experience

0 mo

Total Experience

Average Tenure

Current Experience

Indian institute of technology, delhi

Research Intern

Dec 2023 – Feb 2024 · 2 mos · Delhi, India

● Developed ThyroNet, using U-Net based on CNN for segmentation of thyroid nodules from ultrasound images and classification into benign or malign.
● Achieved 94% accuracy, 90% sensitivity, and 85% specificity in thyroid cancer detection.
● Reduced model training time by 25% using OpenCV, TensorFlow, Keras, Batch Normalization.
● Achieved an AUC-ROC score of 0.93, demonstrating excellent discriminatory power in distinguishing cancerous from non-cancerous cases.

OpenCVTensorFlowKerasBatch NormalizationMachine LearningDeep Learning