I am a grad student in computer science. Having read many research papers and having worked with an adviser has made me much more aware about best practices concerning presentation and reporting of results in published research.

I have also published a paper when I was a junior in college. Looking back at it now (its been around 2-3 years), compared to the standards set by papers I have read, my work is very sloppy.

More specifically, I have typos in one or two places and an equation is incorrect (I maximize for x when I should be maximizing for x and y). Also, my evaluation is based on very little data (though I do point out that it is very preliminary and further evaluation is needed) and the metrics I have used to evaluate the described technique do not adequately demonstrate that my method is correct or better performing. The evaluation was added after the reviewer comments and therefore was not checked.

Typos aside, as an undergrad, I was ignorant about best practices when it came to reporting results in that specific area. This is partly because me and a friend of mine wrote the paper over the summer without any involvement from our university or professors (I am not making excuses and I do hold myself accountable for these mistakes).

The paper is rather embarrassing since it does not really represent a significant step forward and is presented very sloppily. I love research (I’m planning a career in research) and I feel that it does not accurately reflect my current research rigor. I don’t like it showing up in search results associated with my name.

What would you suggest is the best way to deal with this situation? I’m most worried (been stressing about retractions and the like…) by my lack of sufficient data and invalid metrics, as well as the possibility of future employers seeing it.

Note: I just want to point out that I do not believe that the core idea of the paper is wrong, but the way it is presented along with its evaluation. It’s also been cited a few times (I fully understand that this is no guarantee of validity).

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