Farhat Hossain

B.Tech Student in Bioengineering & Biomedical Engineering

Mandi, IN.

About

Highly motivated B.Tech student in Bioengineering and Biomedical Engineering with a strong foundation in Machine Learning and Deep Learning. Proven ability to apply advanced computational techniques to complex biological and medical challenges, as demonstrated through impactful projects in interpretable medical imaging and genomic sequence classification. Eager to leverage expertise in data analysis, model development, and scientific visualization to drive innovation in a research or industry setting.

Volunteer

Design Head

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Xpecto, Technical Fest of IIT Mandi

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Led the design team for IIT Mandi's technical fest, Xpecto, overseeing the creation of promotional materials.

Highlights

Led a design team to conceptualize and create visually compelling posters, brochures, and social media posts, enhancing event visibility.

Design Volunteer

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Miraz, Annual Cultural Fest of IIT Mandi

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Contributed as a design volunteer for Miraz, the annual cultural fest of IIT Mandi, creating diverse visual assets.

Highlights

Created a range of high-quality posters, banners, and digital assets for various events, supporting the successful promotion of the annual cultural fest.

Education

Indian Institute of Technology, Mandi

Mandi, Himachal Pradesh, India
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B.Tech Bioengineering and Biomedical Engineering Grade: CGPA: 8.31/10

Courses

Machine Learning

Probability and Statistics for Data Science

Python for Data Science

Linear Algebra

Bioinformatics

Languages

English

Hindi

Skills

Programming Languages

Python, R, MATLAB, C++.

Technologies & Frameworks

Tensorflow, Scikit-Learn, Flask, Numpy, Pandas, Matplotlib, RadImageNET, OpenCV, Imbalanced-learn, Scientific Computing.

Tools

Jupyter Notebook, Google Colab, Git, Github, SQL(MySQL).

Data Science & Machine Learning

Medical Image Classification, SNP Classification, Deep Learning Architectures, Data Augmentation, Feature Engineering, Model Interpretability, Precision-Recall Curve Analysis, Numerical Integration.

Bioengineering & Biomedical Engineering

Hodgkin-Huxley Model, Biophysical Simulation, Genomic Data Analysis.

Projects

Interpretable Medical Imaging with ResNet50 and Gradient-Based Saliency

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Summary

Developed an interpretable medical imaging solution using ResNet50 and Gradient-Based Saliency techniques, enhancing model transparency and diagnostic utility.

Custom CNN-LSTM for SNP Classification with Sequence-Level Interpretability

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Summary

Designed and implemented a hybrid CNN-LSTM model for interpretable SNP classification, leveraging genomic sequence data.

Hodgkin-Huxley Neuron Simulation using Python and Euler Method

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Summary

Simulated the classic Hodgkin-Huxley neuron model using Python and the Euler method, visualizing neuronal dynamics.