Posts by Collection

portfolio

DR-IRMPC

DR-IRMPC is a risk-constrained infinite-horizon optimal control framework to solve these class of problems in an iterative manner.

PyCM

PyCM is a multi-class confusion matrix library written in Python that is a proper tool for post-classification model evaluation.

Pymilo

Pymilo is an open source Python package to export pre-trained machine learning models in a transparent way.

Nava

Nava is a Python library that allows users to play sound in Python without any dependencies or platform restrictions.

publications

A Q-learning approach for controlling a robotic goalkeeper during penalty procedure

Published in 2nd International Congress on Science and Engineering, 2019

This study was aimed to solve the problem of penalty kick goalkeeping for RoboCup Small Size soccer robots using a Q-learning approach.

Recommended citation: A. Zolanvari, M. Shirazi and M. Menhaj, "A q-learning approach for controlling a robotic goalkeeper during penalty procedure," in II International Congress on Science and Engineering, Hamburg-Germany, 2019. https://shorturl.at/mBEOZ

Data-driven distributionally robust iterative risk-constrained model predictive control

Published in 2022 European Control Conference (ECC), 2022

This paper considers a risk-constrained infinite-horizon optimal control problem and proposes to solve it in an iterative manner. (ECC 2022 Best Student Paper Award Finalist)

Recommended citation: A. Zolanvari and A. Cherukuri, "Data-driven distributionally robust iterative risk-constrained model predictive control," in 2022 European Control Conference (ECC), 2022. https://ieeexplore.ieee.org/abstract/document/9838319

Data-driven distributionally robust optimization over a network via distributed semi-infinite programming

Published in IEEE 61st Conference on Decision and Control (CDC), 2022

This paper focuses on solving a data-driven distributionally robust optimization problem over a network of agents.

Recommended citation: A. Cherukuri, A. Zolanvari, G. Banjac and A. R. Hota, "Data-driven distributionally robust optimization over a network via distributed semi-infinite programming," in 2022 IEEE 61st Conference on Decision and Control (CDC), 2022. https://ieeexplore.ieee.org/abstract/document/9992604

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.