Prashanna Raj Pandit

About Me

I am a Computer Science graduate student at Southern Illinois University Edwardsville (SIUE), specializing in Statistics, Machine Learning, Deep Learning, and Computer Vision. I am originally from Nepal, where I completed my Bachelor’s degree in Electronics, Communication, and Information Engineering from Tribhuvan University, Pulchowk Campus—one of Nepal’s leading engineering institutes.

Currently, I am working as a Graduate Research Assistant, focusing on developing deep learning models for multimodal time-series data, particularly in gait biomechanics and noisy real-world datasets. My work involves end-to-end data processing, model design, and high-performance computing on GPU clusters.

I have hands-on experience with TensorFlow, Keras, PyTorch, and OpenCV, along with a strong foundation in predictive modeling, data preprocessing, and statistical analysis. I also work with cloud platforms and MLOps practices—building, containerizing, and deploying scalable machine learning pipelines using tools like Docker, CI/CD, and cloud infrastructure. My goal is to bridge theory and real-world applications by developing reliable, intelligent, and data-driven systems.

Technical Skills

Programming Languages

Python R SQL C C++

Frameworks & Libraries

TensorFlow Scikit-Learn Keras OpenCV Optuna YOLO Flask Pandas NumPy SciPy Matplotlib Seaborn

Tools & Software

Git/GitHub Docker Tableau GitHub Actions Airflow AWS (S3, EC2) PostgreSQL Bash Linux Mlflow

Cloud Technologies

S3 EC2 SageMaker IAM Lambda ECR ECS CloudWatch CodePipeline/CodeBuild API Gateway SNS & SQS

Concepts

Object Oriented Programming Machine Learning Statistical Modeling Data Preprocessing Neural Networks/DL Time Series ML Pipeline Model Deployment CI/CD Cloud Services

Soft skills

Collaboration Communication Project management Leadership

Experience

Graduate Research And Teaching Assistant

Jan 2026 – Present

Southern Illinois University Edwardsville

• Edwardsville, IL, USA

Research in autism detection model and assist in CS 325, CS 584, and CS590 courses.

Assisted students in designing modular, object-oriented software systems, emphasizing SDLC best practices, clean architecture, and maintainable code. (CS 325)
Guided students in building CI/CD pipelines, Docker-based containerization, and REST API integration for production-style applications.(CS 325)
Mentored students in data processing pipelines, including data cleaning, feature engineering, exploratory data analysis, and model evaluation. (CS 584)

Research Assistant

Jan 2025 – Jan 2026

Edwardsville, IL, USA

Research in gait analysis and AI-based motion understanding using deep learning and signal processing.

Designed and implemented end-to-end data processing pipelines by extracting 2D pose keypoints from noisy video datasets using OpenPose; processed large-scale JSON data with Python (Pandas, NumPy), OpenCV, and Bash scripting to compute clinically relevant gait features such as gait cycle, stride length, cadence, and joint angles.
Applied statistical methods and feature engineering to gait time-series data, including cubic spline interpolation, Savitzky–Golay smoothing, gait phase segmentation, and turn removal; constructed a clean, multimodal dataset optimized for deep learning models and visualized gait patterns using Matplotlib and Seaborn.
Developed and trained sequential deep learning models (LSTM) for autism classification, achieving 88% accuracy, and performed model optimization through validation, class balancing, and performance analysis.
Packaged trained machine learning models using Docker and deployed them through RESTful APIs, integrating them into a production-ready inference pipeline with CI/CD automation to support scalable, repeatable deployments and seamless integration with a web-based application.

Software Engineer

Jan 2023 – Jul 2024

Vrit Technologies

• Kathmandu, Nepal

Full-stack web development and backend optimization for scalable AI-ready systems.

Built and deployed a Flask-based web application with RESTful APIs, leveraging SQL-backed structured data models and JSON-based data exchange to support analytics, reporting, and backend business logic; improved system performance and SEO metrics by 20%.
Designed and maintained data workflows using SQL queries for data retrieval, transformation, and validation, enabling reliable storage, querying, and integration of application data across services.
Implemented CI/CD pipelines using GitHub Actions and Docker in a Linux environment, automating testing and deployment and reducing manual release effort by 40%, while collaborating with the team using Git and Bash scripting.