Welcome to my site!
“Knowledge is power, but enthusiasm pulls the switch”
I am a highly passionate and self motivated individual with a strong desire to build a career in academia. I love every single step in research and enjoy creating novel innovations through research to make people’s experience with technology memorable, while also unveiling new research pathways. I also enjoy engaging with students, sharing my knowledge with them and guiding them to develop their computer science competency to drive towards excellence.
I love to read and learn new things! In this process, I also love to share the things I learnt with others. I hope you will enjoy reading my posts as much as I enjoy writing them. Do not forget to like, comment and share them with your friends. Your feedback and engagement will definitely keep me motivated to write new content. If you like to see my posts on specific topics that have not been written yet, suggest me in the comments section.
I am excited everything about research and thoroughly enjoy the experience I get in the process from ideation through launch. My main expertise lies in the areas of Natural Language Processing and Text Mining. In addition, I have also experience in areas such as Semantic Web, Machine Learning, Deep Learning, Network Analysis, Sequence Pattern Mining and Temporal Analysis. I would love to work in research projects with diverse topics, which further broadens my expertise and experience!
Check out my research profile for my publications, awards, grants and projects. I am keen on developing my career as a researcher and definitely interested in opportunities such as research collaborations. Feel free to contact me if you have questions or feedback on my research work!
Latest from the Blog
The performance metrics used to compare classification performance are typically represented using elements in the confusion matrix, which is generated by the machine learning model on a test sample. Figure 1 denotes the template of a confusion matrix for a two-class classification problem, where the class of an instance isContinue reading “Confusion Matrix”
Semantic Web Semantic Web enables machines to browse the knowledge distributed across the Web. Consider a Wikipedia page that provides knowledge to human readers. The knowledge contained in the Wikipedia page is opaque from the perspective of the machines, as they “see” nothing but a presentation markup of the WikipediaContinue reading “Introduction to DBpedia”
The scientific literature is growing at an unprecedented rate and it is estimated that the global scientific output doubles every nine years. To date, scientific digital libraries consist of millions of research publications, with thousands of these being added every day. For instance, consider MEDLINE (https://www.nlm.nih.gov/bsd/medline.html), a popular bibliographical database.Continue reading “Why Literature-Based Discovery?”
Launched on April, 2021 🙂
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