Welcome to My GitHub Profile!

👋 Hi, I’m Soham Kalghatgi
I am a Mechanical Engineer persuing a Master's in Mechatronics.
I am a passionate individual with a strong interest in the field of Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, and Cloud Computing. I am constantly exploring new technologies and techniques to expand my knowledge and skills in these areas.
Skills: Python, C, C++, MATLAB, Simulink, Linux, Kubernetes, Docker, Continuous Integration (CI), AWS S3.
Libraries: numpy, pandas, scikit-learn, matplotlib, seaborn, plotly, keras, tensorflow, torch, PIL, opencv-python, ipywidgets, boto3, kubernetes

Amazon S3

Docker

Git

GitLab

Ubuntu

Python

Kubernetes

Matlab

Repository Highlights

The projects that I have worked on are:

Artificial intelligence

Fault Injection in Autonomous Vehicles.
Deep Fake detection.
Image reconstruction and Anomaly detection.
Image Denoising.

Automotive

Specially Abled Utility Vehicle (SAUV).
SAEINDIA Supra.
SAEINDIA Baja.

Contact Me

You can reach me via the following channels:

Email: [email protected]
LinkedIn www.linkedin.com/in/sohamk

Soham Kalghatgi's Projects

analyzing-the-effects-of-fault-injection-into-a-camera-based-autonomous-vehicle-prototype

Identifying failure modes of vehicle cameras in the domain of autonomous driving (ADAS) and, designing a Fault Injection Module (FIM) to inject these faults through image processing into the autonomous vehicle system. Compassion between the faults to validate the robustness of an autonomous vehicle system.

deep-fake-detection

Learning how to distinguish fake content from genuine content with machine learning . The Machine Learning framework used is PyTorch.

image-denoising

DnCNN model trained by residual learning formulation to recover a clean image x from a noisy observation y. The noisy observation y is a combination of a clean image x and residual image v. y = x + v. The Machine Learning framework used is PyTorch.

image-reconstruction-and-anomaly-detection

CNN autoencoder is trained on the MNIST numbers dataset for image reconstruction. Anomaly detection is carried out by calculating the Z-score. The framework used is Keras.

programmed-solutions-for-gyroscope-and-governor.-

Course project under Dynamics of Machines, formulating calculations on Gyroscope and Governor, through executable computer programs using source codes written in C and C++

sohamk10

Config files for my GitHub profile.

specially-abled-utility-vehicle-sauv

A safe, ergonomic, detachable hand-controlled mechanism that allows full coordinated actuation of accelerator, brake, and clutch of a manual transmission vehicle, by just one hand without any -leg input from the driver.