GPA: 4.0/4.0

1. 10-623 - Generative AI

1. • Grade: A

   • Course taught by Prof. Matt Gormley

   • Skills: Generative AI, Stable Diffusion, Large Language Models, Python, Github, AWS, Computer Vision, Deep Learning, Vision Transformers, Diffusion Models, Transfer Learning

   • Project on application of Vision Language Models and Large Language Models

GPA: 3.93/4.0

1. 16-824 - Visual Learning and Recognition

   • Grade: A

   • Course taught by Prof. Jun-Yan Zhu

   • Skills: Generative AI, Stable Diffusion, Large Language Models, Python, Github, AWS, Computer Vision, Deep Learning, Vision Transformers, Diffusion Models, CNNs, Detection and Segmentation, 3D Image understanding, Transfer Learning, 

   • Project on Text to Image generation

2. 24633 - Engineering Optimization

   • Grade: A-

   • Course taught by Prof. Ramteen Sioshansi

   • Skills: AMPL, GAMS, Optimization Theory, MATLAB, Topology Optimization, Optimality Conditions, Duality Theory, Steepest Descent Algorithms, Newton and Quasi-Newton Methods, Conjugate-direction methods, Gradient-projection methods

   • Project on Topology Optimization using MATLAB

GPA: 4.0/4.0

1. 11-785 - Introduction to Deep Learning

   • Grade: A

   • Course taught by Prof. Bhiksha Raj

   • Skills: Python, Deep Learning library from scratch, Deep Learning, Computer Vision, Large Language Models, Version Control (Git)

   • Project on Joint Attention detection using one shot detector

2. 24633 - Additive Manufacturing Lab

   • Grade: A

   • Course taught by Prof. Jack Beuth

   • Skills: Solidworks, Netfabb, ANSYS, Metal AM process control, microstructure characterization

   • Project on New Product Development and feasibility analysis of a lattice structured moebius strip

GPA: 4.0/4.0

1. 24787 - Artificial Intelligence and Machine Learning 

   • Grade: A

   • Course taught by Prof. Amir Barati Farimani

   • Skills: Python, Python libraries, Statistics behind Machine Learning models, Data Science, Data Engineering, Data Visualization

   • Project on Using machine learning models (Random Forest and Linear Regression) to predict value of transfer on Fifa

2. 24632 - Additive Manufacturing Processing and Product Development

   • Grade: A

   • Course taught by Prof. Jack Beuth

   • Skills: Solidworks, Additive Manufacturing processes - Polymer and Metal, Theory behind melt pools and its control

   • Project on new product development and cost analysis for polymer based process (FDM)

3. 24780 - Engineering Computation

   • Grade: A

   • Course taught by Prof. Soji Yamakawa

   • Skills: C++, OpenGL , Object Oriented Programming, Data Structures, Data protection, Audio programming

   • Project on using OpenGL and audio programming