Hi, I'm Aayam 👨‍💻
A computer science student, an undergraduate researcher, and an aspiring AI/ML engineer
ARZ

About

I am a senior undergraduate at Mississippi State University, specializing in artificial intelligence and machine learning. I seek opportunities to apply my technical skills and contribute to innovative projects in the industry.

Work Experience

Center for Equitable AI and Machine Learning Systems

May 2025 - Present
ML Research Intern

Developing a robust non-contact AI drowsiness detection system using an ensemble of pre-trained large CNN architectures (e.g., EfficientNet, DenseNet) to enhance accuracy and build on existing driver safety research

Wireless Communications Lab, MSU

Dec 2023 - Present
Undergraduate Researcher

Conducting research on NSF-funded AERPAW and Open AI Cellular projects to enhance scalability in next-gen wireless communications with software-driven solutions

Geospatial Computing for Environmental Research, MSU

Jan - May 2025
DIS Research Student

Annotated color infrared imagery to create high-res land cover datasets and worked on U-Net-based semantic segmentation models for classifying land cover types based on biophysical properties

Social Winter of Code

Jan - Feb 2025
Open-Source Fellow

Participated in a 2-month open-source fellowship, contributing to 5+ full-stack and AI projects and improving user experience and code quality across various tech stacks while developing collaborative engineering skills"

Education

Mississippi State University

Aug 2022 - Present
B.S. in Computer Science, concentration in AI, minor in Mathematics

Skills

Python
PyTorch
TensorFlow
Keras
Scikit-learn
NumPy
Pandas
Matplotlib
C++
ReactJS
TypeScript
Flask
SQL
Docker
Publications

I co/author research papers

During university and beyond, I collaborated with peers and mentors to transform innovative ideas into published research.

  • N

    Non-Contact AI-Drowsiness Detection System for Safe Driving

    Deep learning ensemble stacking framework for real-time, non-contact drowsiness detection to enhance driver fatigue monitoring and alerting
  • E

    Enhancing UAV-to-Ground Channel Modeling for AERPAW Digital Twin Using Generative Adversarial Networks

    A ML framework for AERPAW’s digital twin to improve wireless channel modeling via synthetic data

Get in Touch

Want to talk? Send me an email, and I'll respond at my earliest convenience.