As a graduate student, one of our goals is to produce research that will be useful to the world, that will be known and used by other people. This usefulness can come in many forms; for example, our work can serve to inspire future research, which will take the topic one step further, or it can be used by people in the industry as part of their work. But for any of this to happen, the methods, results, and takeaways of our research need to be communicated to the world. Of course, most research programs require the student to write a thesis or dissertation, but the reality is that very few people will read it besides the evaluation committee. A thesis or dissertation might eventually be also read by other graduate students that are working on the same topic and want to know the existing literature in details. But other than that, most people would prefer to read a summarized version of the research instead of the whole thesis or dissertation.
Therefore, graduate researchers should also try to publish their results in other formats, so they become more accessible to the general public. Some graduate programs even include publication requirements as part of the students’ obligations, particularly when there is public funding involved. But even when it is not a requirement, publishing one’s research results is not only one of the best ways to ensure that it can be found and used by other people, but it is also a rich experience for the researcher. This especially relates to the involved writing, the publication, and the resulting networking with other people reading and mentioning your work.
There are many different ways, formats, and venues that can be used to publish original research. In general, we can split them into academic publications – whose primary audience is mainly formed by other researchers – and non-academic – which are more directed to the industry and the general public.
In this post, I am going to talk about precision and recall and their importance in information retrieval. First of all, let’s talk about what we mean by information retrieval. Suppose you wake up one morning and decide you want to make muffins for breakfast. You take out your laptop and search for “healthy muffin recipe” on Google. Then, you go through the search results, decide on a recipe and get started on it. This is an example of information retrieval where the search engine (Google in this case) retrieved the results for your search query “healthy muffin recipe”.
Bisection or Binary logic is an example of a simple yet powerful idea in computer science that has today become an integral part of every computer scientist’s arsenal. It stands synonymous to logarithmic time complexity that is no less than music to a programmer’s ears. Yet, the technique never fails to surprise us with all the creative ways it has been put to use to solve some tricky programming problems. This blog-post will endeavour to acquaint you with a few such problems and their solutions to delight you and make you appreciate it’s ingenuity and efficacy. Continue reading
Whether you are ready for chatbots or not, they have been the future we live in now. Chatbots are not robots, but they are supposed to mimic humans. They are a piece of software that you chat with to get things done or be entertained. You have probably used Apple’s Siri, Google Assistant or Microsoft’s Cortana. But chatbots are more than just the built-in personal assistants. They are everywhere now; from ordering pizza to checking flight status
I have run an experiment to use chatbots in higher education in order to drive student engagement beyond the classroom experience. In this post, I am going to share my experience in developing a chatbot teaching assistant, called Koko. Continue reading
What is the meaning of the word understanding? This was a question posed during a particularly enlightening lecture given by Dr. Anupam Basu, a professor with the Department of Computer Science Engineering at IIT Kharagpur, India.
Understanding something probably relates to being able to answer questions based on it, maybe form an image or a flow chart in your head. If you can make another human being comprehend the concept with the least amount of effort, well that means you do truly understand what you are talking about. But what about a computer? How does it understand? Continue reading