About Me

Ph.D. candidate in Computer Science and Engineering (CSE) at University of South Florida (USF) - Expected Graduation: August'2025
M.Sc. in Computer Science (CS) at University of South Florida (USF)
B.Sc. in Electrical & Electronics Engineering (EEE) from Bangladesh University of Engineering & Technology (BUET)

Currently, I am a Graduate Research Assistant in SCoRE Lab, Department of Computer Science and Engineering, University of South Florida.

Open to Work: Actively seeking opportunities to apply my AI expertise in impactful fields - especially public health - to help communities and improve lives.

Research Interest – Computer Vision | Deep Learning | Machine Learning

Please find my latest resume here

CV - Farhat Binte Azam.pdf

Employments

Graduate Research Assistant

Jan 2021 - Present

Developing an innovative initiative - MosquitoAI is dedicated to developing Artificial Intelligence powered systems tailored for various aspects of mosquito anatomy classification and segmentation.
Leading a team, to deploy our AI models to a hardware called “Mosquito-Trap” - a valuable tool for mosquito surveillance and control, ultimately benefiting communities at risk of mosquito-borne diseases.
With teamwork and collaboration, all the AI models are being deployed in our AI dashboards, making them accessible for citizen scientists engaged in mosquito monitoring.

Research Assistant

Feb 2020 - July 202

Led the creation of a Phonocardiogram (PCG) dataset by managing data collection efforts with medical professionals in hospital settings.
Developed a deep learning framework with a novel feature fusion technique to address noise and channel distortion in heart sound signals captured via digital stethoscopes.
Co-authored a research publication detailing the dataset and AI model, with key contributions to signal preprocessing and noise-handling methodologies.

Skills

Data Analyzing

Deep LearningMachine LearningNatural Language Processing

Processing

Computer VisionDigital Image Processing
Digital Signal Processing

Languages & Tools

Python, C, C++, MATLABPytorch, Tensorflow, KerasAssembly Language

Hardware

PCB design (Eagle/Proteus)Circuit Simulation (Proteus)Arduino, AVR, Raspberry pi

Certifications

www.coursera.org/account/accomplishments/specialization/WS8VA2C2AE57

Deep Learning Specialization

Authorized by Stanford University, offered through Coursera

Neural Network and Deep Learning (96.50%)
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (95.20%)
Structuring Machine Learning Projects (86.70%)
Convolutional Neural Network (95.60%)
Sequence Models (98.50%)

www.coursera.org/account/accomplishments/records/LNRTEM9TYKJD

Machine Learning (95.70%)

Authorized by Stanford University, offered through Coursera

Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).
Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).
Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI)

Volunteering

Data Extraction Team

Social Network Coordinator

Hobbies

Exploring Nature: I have an unwavering passion for travel and adventure. Whenever I have some free time, you'll likely find me on a journey with friends, discovering the breathtaking beauty of the natural world. From hiking in the mountains to relaxing on pristine beaches, exploring nature is my ultimate escape.
Road Trips: Going for both long and short drives is my way of finding peace and maintaining focus. The open roads, scenic routes, and the freedom of the journey help me unwind and clear my mind.
Musical Meditation: Music is my constant companion. Listening to songs that match my mood is akin to meditation. Whether it's relaxing with soothing tunes or getting energized with rhythmic beats, music is a source of solace and inspiration in my life.

Check out some of my videos!! 👇