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amr-samples-metamodels-package

This repository contains data for training and testing metamodels (Kriging, RBF,...) that are used in a new surrogate based optimization (SBO) process called adaptive model refinement. The resulting trained metamodels are also included in this package.

backtrader-for-backtesting

These are the code snippets used in the Backtrader for backtesting guide on the AlgoTrading101 website

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

big-mrta

cadapplication

A collection of MATLAB codes/GUI for CAD Application Course

cpp-cheat-sheet

C++ Syntax, Data Structures, and Algorithms Cheat Sheet

e-puck2-library

This e-puck2-library provides the main functions to actuate and read the sensors of the e-puck2 in the Python programming language.

nd013-c1-vision-starter

Starter Code for the Course 1 project of the Udacity Self-Driving Car Engineer Nanodegree Program

optimizing-bio-inspired-riblets-openfoam

This repository contains key software artifacts of the Open-FOAM based CFD framework that computes the drag coefficient of a NACA-0012 airfoil with bio-inspired surface riblets. This package also provides the framework to introduce your own optimization code for minimizing drag by varying the shape of the surface riblets. For further information about the methods underlying this software package, refer to our paper: Lulekar, S. S., Ghassemi, P., Alsalih, H., and Chowdhury, S., An Adaptive-Fidelity Design Automation Framework toExplore Bio-inspired Surface Riblets for Drag Reduction, AIAA Journal. 2020. AIAA. The following sections provide further information on the usage of this software package:

pemf-1

Predictive Estimation of Model Fidelity (PEMF) is a generalized approach to predict surrogate model error. PEMF takes as input a model trainer, sample data on which to train the model, and hyper-parameter values to apply to the model. As output, it provides an estimate of the median or maximum error in the surrogate model.

personal_data_science_projects

pnplot

It is a code package that I prepared to prepare plots with appropriate style (color, font, line size, etc) for scientific publications. It is based on Python's Seaborn and Pandas packages.

scopp

Scalable Coverage Path Planning of Multi-Robot Teams for Monitoring Non-Convex Areas

uav-noise-experimental-data-and-modeling

A data set of experimental recordings of the acoustic sound pressure level field around a hovering UAV, and a Sequential Physics Infused machine learning model to predict the acoustic field based on the data.

uberkeley-cs285-drl-homework-fall2022

Assignments for Berkeley CS 285: Deep Reinforcement Learning (Fall 2022)