Atiq Ur Rehman, Post Doc


The main research focus is to develop generic machine learning and swarm intelligence algorithms to analyze high-dimensional datasets.  Specifically,  I  am developing algorithms for unsupervised learning, data preprocessing, and evolutionary optimization methods. My expertise includes building new artificial intelligence models with a real-application focus on computing systems and big datasets.

My current research focuses on developing Swarm Intelligence (SI) based Machine Learning (ML) algorithms for real measurement applications and high dimensional datasets. Mainly, I focus on how SI can improve the decision-making powers of ML methods in real scenarios. Besides developing SI-based ML models, I also enhance the state-of-art SI and ML methods.

I have developed some novel methods and solutions for:
1.    Unsupervised learning in high dimensions.
2.    Global search optimization in high dimensions.
3.    Anomaly detection in high dimensions.
4.    Latency reduction for Electronic Nose System(ENS).
5.    Drift issue in gas sensors for the real deployment of ENS