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About Me

I am a passionate research scientist with 10+ years of experience in health data science, specializing in extracting valuable insights from complex healthcare datasets using modern machine learning techniques. Skilled in utilizing real-world data (RWD) to infer real-world evidence (RWE) and generate actionable insights. Committed to driving innovative research and making a meaningful impact in public health through data-driven solutions that enhance patient outcomes, support informed decision-making, and contribute to the advancement of personalized medicine.


My primary interest is rooted in the exploration and understanding of the rich contextual information inherent in various real-world datasets. I am particularly drawn to the challenge of deciphering complex patterns and relationships within these datasets, which often hold the key to transformative insights and breakthroughs.

To this end, I have dedicated my efforts to designing efficient inference and learning pipelines. These pipelines are tailored to handle the inherent uncertainties and interdependencies that are characteristic features of large-scale datasets. This approach allows for a more nuanced and comprehensive understanding of the data, leading to more accurate and insightful outcomes.

My experience in computational modeling spans a diverse range of domains. From tackling real-world engineering problems to delving into medical diagnostics, immunology, epidemiology, bioinformatics, and regulatory genomics, my work is defined by its breadth and depth. This diversity of experience allows me to bring a unique perspective and a multifaceted approach to problem-solving, enhancing the quality and impact of my research.

Tag cloud of my research interests
"Being a scientist means living on the borderline between your competence and your incompetence. If you always feel competent, you aren't doing your job."
 Carlos Bustamante (UC-Berkeley)
“Data scientists are involved with gathering data, massaging it into a tractable form, making it tell its story, and presenting that story to others.” 
Mike Loukides
"Numbers have an important story to tell. They rely on you to give them a voice.” 
Stephen Few
“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”
Geoffrey Moore

Higher Eduction

Research Interests

Applied Artificial Intelligence 

2010 - 2014

Ph.D. Engineering 

Major: Intelligent Data Analysis

School of Engineering

University of Warwick           Coventry, United Kingdom

Big Data Analysis

Computational Modelling 

2009 - 2010

MS Electrical Engineering

Major: Control System / Applied Artifical Intelligence

Dalarna University    Borlange, Sweden

Clinical Data Science

Professional Experience

Apr. 2017 - Jul. 2019

Clinical Data Scientist (Postdoc)

Department of Medicine, and

Institute for Genomics and Systems Biology 

University of Chicago

Chicago, IL USA 


Aug. 2014 - Mar. 2017

Computational Biologist (Postdoc)

Dep. of Microbiology and Immunology, 

Dep. of Biostatistics and Computational Biology

University of Rochester Medical Center

Rochester, NY USA 

Machine Learning

Biomedical Data Science


Aug. 2019 - Present

Biomedical Data Scientist (Staff Scientist)

Department of Medicine,

Section of Computational Biomedicine and Biomedical Data Science 

University of Chicago

Chicago, IL USA 


Jan. 2011 - Mar. 2014

Research Assistant / Lab Demonstrator

School of Engineering,

University of Warwick        

Coventry, United Kingdom

Causal Inference

Data Mining


Knowledge Extraction

May 2021 - May 2023 

Master of Public Health (MPH) Major: Epidemiology

Harvard T.H. Chan

School of Public Health

Harvard University         

Boston, MA, USA

Public Health Informatics

2003 - 2008

BS Electrical Engineering 

Major: Telecommunications

National University of Computer and Emerging Science, Pakistan

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