I'm Saroj

PhD Candidate in Mechanical Engineering | Specializing in Additive Manufacturing, 3D Printing Systems, Multiphysics Simulation, Modeling, Optimization

I am a PhD Candidate in Mechanical Engineering at North Carolina State University, specializing in additive manufacturing (specifically vat-photopolymerization-based 3D printing. My research focuses on developing state-of-the-art static and scrolling DLP systems, optimizing energy input for dimensional accuracy, mechanical strength and fabricating functional polymeric materials with potentials for bio-medical, healthcare, soft robotics, electronic devices and many other applications. With experience spanning system design, process optimization, and multiphysics simulation, I bridge academic innovation with practical engineering solutions for industry applications.

Currently looking for full-time roles starting mid-2026.

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Projects

Automated Grayscale Modulation System for High-Precision DLP 3D Printing image

Automated Grayscale Modulation System for High-Precision DLP 3D Printing

Mechanical design and assembly sensor integration LabVIEW MATLAB Motion control Arduino material optimization

Developed an automated grayscale calibration system that corrects non-uniform light distribution in DLP 3D printing. By integrating sensors, motion control, and pixel-level image correction, the solution improved dimensional accuracy and process consistency, enabling more reliable production of high-precision polymer parts.
Irradiation Model and Optimization for DLP Printing image

Irradiation Model and Optimization for DLP Printing

Mechanical design and assembly LabVIEW MATLAB Optimization tools

Developed a physics-based irradiation model to simulate voxel-level energy distribution in DLP 3D printing, enabling prediction of cured geometry and croslinking density. Implemented an optimization framework to minimize overcuring for dimensional accuracy, maximize energy for mechanical strength, improving both precision and realiability in printed parts.
Investigation of Powder Characteristics and Microstructural Evolution of Laser Printed Ti-15Mo Samples Prepared by Ball Milling image

Investigation of Powder Characteristics and Microstructural Evolution of Laser Printed Ti-15Mo Samples Prepared by Ball Milling

Laser Powder Bed Fusion (LPBF) Powder mettalurgy (Ball Milling) SEM/EDS & Optical Microscopy Materials Characterization (LECO, Microtrac) Microhardness Testing Parameter Optimization

Investigated the processing of Ti-15Mo alloy using ball milling and Laser Powder Bed Fusion (LPBF). Characterized powder properties (SEM, LECO, optical microscopy), optimized printing parameters, and analyzed printed parts for porosity, microstructure, and hardness. Achieved improved understanding of powder spreadability, oxygen contamination control, and parameter effects on density and hardness of Ti-15Mo components.
Robotics & Computer Vision for Automated SLA 3D Printing Post-Processing image

Robotics & Computer Vision for Automated SLA 3D Printing Post-Processing

Robotics (UR5e arm, ROS2, MoveIt, Rviz) Computer Vision Python & ROS2 packages Automation & Control Systems Additive Manufacturing (SLA/DLP)

Developed a ROS2-based system integrating robotic arms, custom grippers, and computer vision to automate support removal in Stereolithography (SLA) 3D printing. Designed and tested control workflows using ROS2, Rviz, and MoveIt, and created optimized gripper prototypes to handle dental parts printed on RapidShape systems.
Obesity Risk Classification Using Machine Learning image

Obesity Risk Classification Using Machine Learning

Machine Learning (Random Forest, KNN, CNN) Python (Scikit-learn, TensorFlow, PyTorch, Pandas, Seaborn) Data Preprocessing & Feature Engineering Exploratory Data Analysis & Visualization Hyperparameter Optimization

Built predictive models to classify obesity risk into eight categories using lifestyle and genetic factors. Compared Random Forest, KNN, and CNN models on Kaggle health datasets from Mexico, Peru, and Colombia, achieving up to 95% accuracy. Developed a Streamlit app to enable interactive user predictions.
Ecofriendly Air-Powered Seed Rocket for Reforestation image

Ecofriendly Air-Powered Seed Rocket for Reforestation

Additive Manufacturing (SLA, SLS, FDM) Rocket Design & Simulation Materials Selection (ABS, Tough 2000, PA12 Nylon) Prototyping & Testing

Designed and built an air-powered rocket to disperse seeds in hazardous or difficult-to-access areas, using biodegradable materials and additive manufacturing. Combined SLA, SLS, and FDM printing to fabricate different components, and validated performance through open-source rocket flight simulations, achieving ~70 m horizontal travel.

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