Personal profile

Research Interests

Neural Networks; Machine Learning; Intelligent Systems; Reinforcement Learning; Artificial Intelligence; Robotics and Fuzzy Logic

Biography

Dr Abdulrahman Altahhan (DoS) Has a PhD in Machine Learning and Robotics and an MPhil in Fuzzy Expert Systems. Dr Abdulrahman is actively researching in the area of reinforcement learning applied on the robot navigation. He has extensively prepared designed and developed a novel reinforcement learning family of methods and studied their mathematical underlying properties. He has presented in prestigious conferences and venues in the area of machine learning and neural network. Currently he is preparing a new set of algorithms and finding where he is combining deep learning with reinforcement learning in a unique way. His research was influential in investment of a set of state of the art robots in the department that he is hoping to use to support his PhD students and to verify the expected set of algorithms. Dr Abdulrahman is teaching in the Machine Learning, Neural Networks and Big Data Analysis modules in the MSc of Data Science, he is the programme/course director of this new and exciting master.

Area of Expertise:

Machine Learning, Neural Networks, Reinforcement Learning and Robotics

Vision Statement

My ultimate aim is to build a truly autonomous robot that is able to help humans in their everyday and difficult tasks, for example, in the daily care of an elderly or an autistic child, or any physically or mentally disadvantaged person, in a big industrial plant or in a small home downtown. In particular, I am interested in teaching a robot or a system how to behave and act favourably and ethically for the sake of humanity. These aims and many more can be achieved when the frontiers of machine learning, reinforcement learning and neural networks are advanced by first gaining more theoretical insight and mathematical analysis of current methodology and by inviting more inspirational approaches gained by more understanding of how the brain achieves its tasks and how the human behaviour influences its own awareness of the environment around it.

Fingerprint Fingerprint is based on mining the text of the persons scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 3 Similar Profiles
Robots Engineering & Materials Science
Reinforcement learning Engineering & Materials Science
Neural networks Engineering & Materials Science
Feature extraction Engineering & Materials Science
Network architecture Engineering & Materials Science
human being Social Sciences
activity Social Sciences
robots Agriculture & Biology

Research Output 2011 2016

Deep Learning for Emotion Recognition in Faces

Ruiz-Garcia, A., Elshaw, M., Altahhan, A. & Palade, V. 13 Aug 2016 Artificial Neural Networks and Machine Learning – ICANN 2016. Villa, A. E. P., Masulli, P. & Rivero, A. J. P. (eds.). Switzerland: Springer Verlag, Vol. 9887, p. 38-46

Research output: Chapter in Book/Report/Conference proceedingChapter

Network architecture
Feature extraction
Neural networks

Emotion Recognition Using Facial Expression Images for a Robotic Companion

Ruiz-Garcia, A., Elshaw, M., Altahhan, A. & Palade, V. 2016 Engineering Applications of Neural Networks. Jayne, C. & Iliadis, L. (eds.). Switzerland: Springer Verlag, Vol. 629, p. 79-93

Research output: Chapter in Book/Report/Conference proceedingChapter

Robots
Multilayer neural networks
Support vector machines
Robotics
Gabor filters

Manifold locality constrained low-rank representation and its applications

You, C-Z., Wu, X-J., Palade, V. & Altahhan, A. 3 Nov 2016 p. 3264 - 3271

Research output: Contribution to conferencePaper

Supervised learning
Computer vision
Pattern recognition
Signal processing

Self-reflective deep reinforcement learning

Altahhan, A. 3 Nov 2016 p. 4565 - 4570

Research output: Contribution to conferencePaper

Reinforcement learning
Marketing
Servers
Robots

Smartphone Based Human Activity and Postural Transition Classification with Deep Stacked Autoencoder Networks

Hicks, L., Hedley, Y-L., Elshaw, M., Altahhan, A. & Palade, V. 2016 Artificial Neural Networks and Machine Learning – ICANN 2016. Villa, A. E. P., Masulli, P. & Rivero, A. J. P. (eds.). Switzerland: Springer Verlag, Vol. 9887, p. 535-536

Research output: Chapter in Book/Report/Conference proceedingChapter

human being
activity
cell phone
classification
interest

Activities 2013 2016

  • 6 Participation in conference

International Conference on Robotics ICRA 2016

Altahhan, A. (Reviewer)
16 May 201621 May 2016

Activity: Participation in conference

7th IEEE International Conference on Robotics, Automation and Mechatronics (RAM)

Altahhan, A. (Speaker)
15 Jul 201517 Jul 2015

Activity: Participation in conference

22nd International Conference on Neural Information Processing (ICONIP2015)

Altahhan, A. (Speaker)
9 Nov 201512 Nov 2015

Activity: Participation in conference

CDN 2015, an International Workshop on Cloud- Service DataCenter Networks

Altahhan, A. (Technical Committee Member)
17 Aug 201520 Aug 2015

Activity: Participation in conference

Global Education Forum

Altahhan, A. (Speaker)
5 Feb 2014

Activity: Participation in conference