The Robotics and Intelligent Computing (RICE) Lab at LUMS is dedicated to conduct research with primary focus on Applied Soft Computing. The lab is equipped with the state-of-the art software and hardware, with a total strength of over ten members. The members of the Robotics and Intelligent Computing Lab have contributed to fields of Intelligent Speech and Natural Language Processing, Intelligent System Modeling, Simulation and Controls, Data mining and Self Rule Generation, AI, Databases and Aspect Oriented Programming, Neural Networks and Fuzzy Systems, and Robot Design, Planning, and Learning.
Members of the lab have worked on several projects such as automatic Tajweed rule extraction from Quranic Recitations, modeling and simulation of industrial processes, modeling the Indus basin river system, automation of conceptual models in databases and object oriented paradigms, aspect semantic networks, stock market predictions using FIR neural networks, generalized regression neural networks, economic models and knowledge base systems. The lab has developed two working robots indigenously and is in the initial planning stage of developing an automatic assembly line robotic system. Recently, we received an amount of Rs. 4.3 million funded by PTCL on the project Automated Control Programming of Robot though Imitation for the duration of three years.
The members of the lab have established several external research links with reputed researchers of international universities, which include University of Lancaster, UK University of Cardiff, UK, King’s College, UK, Imperial College, UK, and Ohio State University, USA.
For more information regarding the activities at the Robotics and Intellignet Computing Lab, please contact Dr. Mian Muhammad Awais (awais AT lums DOT edu edu pk) or Dr. Shafay Shamail (sshamail AT lums DOT edu DOT pk).
Investigator: Mian Awais
Project Duration: Sep 2005 – Sep 2007
Funded by PTCL ( Rs. 4.3 million )
This project proposes the design and development of a general methodology for automated learning of robot controllers through imitation of other robots and humans. The techniques underlying this methodology are derived from soft computing, including neural networks, fuzzy systems, evolutionary computation, machine learning, and probabilistic reasoning. The results of this research will help local industries automate their processes for enhanced productivity, quality, and cost-effectiveness.
Investigator: Asim Karim and Tariq Jadoon
Project Duration: Sep 2004 – Sep 2006
Funded by PTCL ( Rs. 1.1 million )
This is an on-going 2-year PTCL R&D funded project focusing on the development of an intelligent network intrusion detection system for ISPs and large institutional networks. The scope of the project includes network security architectures based on open-source software, data mining algorithms for anomaly detection, automatic generation of rules and signatures, and performance evaluation.
