Prof. Saeed Saeedvand

About

Prof. Saeed Saeedvand is an assistant professor at the Electrical Engineering Department of NTNU, Taiwan currently. His research interest covers Robotic, Machine Learning, Artificial intelligence, and Deep Reinforcement Learning (DRL) algorithms. He started robot development projects in 2009, and he has developed Humanoid Kid-size, Humanoid Adult-size, and mobile robots. 

Address: 5th floor of Electrical Engineering department., College of Science and Technology, No. 129, Section 1, Heping Road, Da’an District, Taipei City, 106.

Office: +886-2-7749-3541

Email: saeedvand@ntnu.edu.tw

Courses at NTNU:

In this course, students will learn Introduction to Reinforcement Learning and its applications, Multi-armed bandits, Markov Decision Processes (MDP), Value Iteration, Policy Iteration, Monte Carlo algorithms, Temporal Difference (TD) evaluation, Q-Learning, SARSA, ESARSA, Introduction to DRL, Policy Gradient, Actor-Critic, State-of-the-art Algorithms (PPO).

In this course, students will learn Introduction to mobile robots as the key part of SLAM, Introduction to Mapping and Localization, Well-known and State-of-the-art approaches for localization and mapping, Recursive Bayesian estimation, Kalman Filter, Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), Histogram Filter Localization Particle filter, Occupancy Grid Mapping, Graph based approaches, Iterative Closest Point (ICP), Hierarchical approaches, Odometry Based approaches, Optimization-based approaches, ORB-SLAM.

Machine learning is one of the interesting fields that is based on learning-based algorithms and it is a part of artificial intelligence. This course introduces the basic principles of machine learning in which prediction and modeling play important roles. Topics in The course: Statistical Learning - Linear regression - Classification and Clustering algorithms - Support Vector Machine (SVM) - Neural Networks and Convolutional Neural Networks (CNNs) - Recurrent Neural Networks (RNNs) - Deep Belief Networks (DBNs) - Transfer Learning - Ensemble learning techniques - Multi-task Learning (MLT) - Decision Tree - State-of-the-art algorithms.

Some Projects Videos:

Adult-size Humanoid Robot (2018)

Robot Localization (2016)

RoboCup Event (2017)

Kid-size Robots (2011)

Reviewer and Referee

Journal Reviewer, IEEE Robot & Automation Letters, IEEE

Journal Reviewer, IEEE Access, IEEE

Journal Reviewer, Journal of Supercomputing (SUPE), Springer

Transaction of the Institute of Measurement and Control

Journal Reviewer, Soft Computing, Springer

Journal Reviewer, Wireless Networks, Springer

Journal Reviewer, Arabian Journal for Science and Engineering, Springer

Journal Reviewer, The Knowledge Engineering Review, Cambridge

Sensors

Mathematics

Applied Science

Diagnostics

Technical Committee member, RoboCup Iran Open competitions, Humanoid Robots League

Technical Committee member, FIRA RoboWorld Cup competitions, Iran, Hurocup League

Some Robotics Achievements

 • First Place in Robot Magic and Music, IROS 2019, Macau

• Third Place in Humanoid Adult-Size Robot League at RoboCup 2017, Nagoya, Japan

• First Place of Humanoid Adult-Size Robot League at IranOpen 2017, Tehran, Iran

• Third Place in Humanoid Adult-Size Robot League at RoboCup 2016, Leipzig, Germany

• First Place in Humanoid Adult-Size Robot League at IranOpen 2015, Tehran, Iran

• Second place in Humanoid Kid-Size Robot League at IranOpen 2012, Tehran, Iran

• First place in Humanoid Kid-Size Robot League at IranOpen 2011, Tehran, Iran

• First place at International Khwarizmi & AUT robotic competitions 2010 (Kid)

• etc.