aboutme.html

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title: About Me
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            Hello! My name is Arslan.
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            I'm interested in computer science, statistics, and a good story. <br><br>
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            I am a data scientist with experience in statistical modeling, optimization, and machine learning on 
            structured and unstructured data (along with "munging" of aforementioned data). I additionally have experience in data engineering 
            including data modeling (who doesn't love a good star schema?), ETl pipelines, and distributed computing (Spark & Hadoop ecosystems). 
            In my current role as a Data Scientist at Logistics Mangagement
            Institute (LMI) in the Washington, D.C. area, I develop data-driven solutions to help improve the functioning of our federal government.
            <br><br>
            
            In my free time I develop data science and software projects, bike (I currently ride a Cannondale Synapse), and ski (in the winter of course). 
            I am working to develop fluency in French (which I picked up long ago) and in Urdu (my parents' mother tongue).
            <br><br>
            
            Previously, I completed my undergraduate from the University of Virginia in 2019 where I worked on research in biomedical microscopy, which lies 
            at the intersection of data science, engineering, and the biomedical sciences. Being an engineer at heart who is passionate about making an impact using technology,
            I also led engineering teams as part of the University's Solar Electric Vehicle Team to build a single-driver, solar-powered vehicle.
            <br><br>

            I aspire to help build the next generation of intelligent systems that can navigate our data-rich world to make a positive difference. Toward that aim,
            I am currently pursuing an advanced degree in computer science with a specialization in ML through the Georgia Tech Online Master's of Science in
            Computer Science (OMSCS).
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        <h3 class=aboutme-font>Other curiosities...</h3>
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            Check out the following books, blogs, papers, and podcasts that I find interesting/enriching/entertaining that I hope you do too!
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                <li><a href="https://statmodeling.stat.columbia.edu/" target="_blank">Andrew Gelman's Blog</a></li>
                <li><a href="https://www.thisamericanlife.org/" target="_blank">NPR: This American Life Podcast</a></li>
                <li><a href="https://www.wnycstudios.org/podcasts/radiolab" target="_blank">Radiolab Podcast</a></li>
                <li><a href="https://lexfridman.com/" target="_blank">Lex Fridman Podcast</a></li>
                <li><a href="https://www.danpink.com/books/drive/" target="_blank">Drive: The Surprising Truth About What Motivates Us - Daniel H. Pink</a></li>
                <li><a href="https://www.amazon.com/Zero-One-Notes-Startups-Future/dp/0804139296" target="_blank">Zero to One - Peter Thiel</a></li>
                <li><a href="https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable/dp/1449373321" target="_blank">Designing Data-Intensive Applications</a></li>
                <li><a href="https://pages.cs.wisc.edu/~remzi/OSTEP/" target="_blank">Operating Systems: Three Easy Pieces</a></li>
                <li><a href="https://web.stanford.edu/~hastie/ElemStatLearn/" target="_blank">Elements of Statistical Learning</a></li>
                <li><a href="Modern Mathematical Statistics" target="_blank">Modern Mathematical Statistics</a></li>
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