Showmik Debnath

ACADEMIC RESEARCH / PUBLICATIONS M.Acharjee, S.Debnath, S.C.Das, R.M.L.R. Pir, and M.S.R. Kohinoor, “Predictive Modeling for Depression Diagnosis Using Machine Learning and DSM-5 Criteria,” 2024 27th International Conference on Computer and Information Technology (ICCIT), Cox's Bazar, Bangladesh, 20-22 December 2024. (Accepted) Undergraduate Thesis: Showmik Debnath, Murchona Acharjee, Sujoy Chandra Das, Rana M Lutfur Rahman Pir, “Depression Detection in People of Various Age Groups Using Machine Learning Algorithms And Sentiment Analysis In NLP”. ACADEMIC PROJECTS # MoodSnap Depression Detection System ● Machine Learning based system which can detect depression according to DSM-5 criteria. The Model of the system is trained using a real dataset which is collected by ourselves. ● The system is deployed on both web and app platforms, with the app currently in the testing phase. ● This software (App) has been created using the Dart programming language and the Flutter framework, focusing on the MVC architectural pattern. The system’s backend is managed using Python, specifically through the Flask framework. ● The front end of the Web application is built using HTML, CSS, Bootstrap, and Java-Script, and the back end is maintained through Python (Flask). ● A user can check whether he/she has any risk of depression. # Coder’s Combo Social Media Platform for Coders with a Bot System ●Created a Flutter app enabling coders to connect, share knowledge, and access DSA content. ●Added automated blog/tutorial features and messaging system with Firebase backend.