Muhammad Bilal Qureshi received his MS Computer Sciences degree from Information Technology University, Punjab Lahore (ITU) with distinction. He was the gold medalist for his batch. He received full merit scholarship from ITU throughout his MS. Afterwards, he joined the Data Science Lab at ITU to further his MS research.His current research interests include discrimination discovery, discrimination aware data mining, causal analysis, privacy preserving data mining, privacy attach strategies and mining big data.His MS dissertation was related to discrimination aware data mining. Social discrimination is considered illegal and unethical. It is often implicit in observed decisions’ datasets, and anti-discrimination organizations seek to discover cases of discrimination and to understand the reasons behind them. Existing directions adopt simple observational data analysis; however, this can produce biased results due to the effect of confounding variables. Bilal proposes a causal discrimination discovery and understanding approach based on propensity score analysis, which is an effective statistical tool for filtering out effect of confounding variables. Bilal’s research is focused on quantifying causal discrimination or favoritism of each individual in the dataset using a neighborhood-based measure. His approach avoids common pitfalls in observational data analysis and make its results legally admissible. In future, he wants to apply his expertise in discrimination discovery domain to quantify social imbalance prevalent in local and global context.