A prior learning and sampling model informed tool for learning with Single Cell RNA-Seq data

Estimate mobile camera pose and object positions with multiple webcams.

Lecture Notes and Programming Assignments for the Self Driving Car Specialization taught by the University of Toronto on Coursera

Explore the world of UAV-State-Estimation, a detailed Python repository focusing on 3D state estimation for unmanned aerial vehicles (UAVs) through the use of Kalman Filter methods. This repository uniquely merges theoretical frameworks and hands-on simulations, making it an ideal resource for both drone enthusiasts and experts in drone technology.

Implementation of a simple 2D EKF with lidar and radar measurements

Tracking an embodied AI agent to estimate movement from observations

Repo for testing out Simulation Based Inference (sbi) with Hidden Markov Models (HMM)

The programs written over the summer of 2021 while working for the University of Delaware's Information and Decision Sciences (IDS) Lab. For more information about the lab and its other projects, please visit https://sites.udel.edu/ids-lab/ . This repository and README will be updated somewhat reguarly as progress is made on these projects.

Simple dead reckoning example in one dimension

Modeling of double pendulum suspended on a cart system, and designing LQR controllers and LQG controllers to control state variables like cart position, pendulum angular displacement, velocity

Estimating axis of rotation using world-frame observations of points on rigid body

Kalman Filter algorithm simulation with Markov process for state estimation.

This repo contains the code of my Master's Thesis. Specifically, it consists in exploring different techniques(Explanable AI, Physics Informed NN, ...) to perform State Estimation

The "GBEES" repsository containes the codebase accompying the paper "State Estimation of Chaotic Trajectories: A Higher-Dimensional, Grid-Based, Bayesian Approach to Uncertainty Propagation" presented at the January 2024 AIAA/AAS Space Flight Mechanics Meeting.

In this project a rather brilliant observer called Thau observer or Lipschitz observer is proposed and designed to estimate the states of a special form of nonlinear systems. All the details regarding the observer design and its simulation are given in "Kian Khaneghahi - Fault Midterm - Q4.pdf" report file.

Prior-based patch-level representation learning for electric vehicle battery state-of-charge estimation across a wide temperature scope

Grad Course (2021), CE 295 – Data Science for Energy

Artificial Intelligence > Machine Learning > Deep Learning