Contact
Postdoctoral Fellow, Faculty of Science - Computing Science
- nawshad@ualberta.ca
Overview
Area of Study / Keywords
Artificial Intelligence Machine Learning Natural Language Understanding
About
I am a Machine Learning and Software Development veteran with around 15 years of experience in Machine Learning R&D and Software Development Industries/Facilities. I earned my PhD in Artificial Intelligence from the University of Alberta. My PhD supervisors were Profs. Randy Goebel and Osmar Zaiane and PhD Supervisory Committee included Lili Mou. During PhD, my focus was on developing domain models which require small data to learn. More specifically, my area of interest was on modelling linguistic pattern of depressed individuals so to ground it to a valid depression rating scale score (used by clinicians for monitoring their patients) and analyze this score temporally on their language usage history. This required bringing innovations in several areas of Computing Science, such as Machine Learning (Non-linear regression on embedding space, Zero-shot Learning, Semi-supervised Learning and Deep Temporal Modelling), Data Mining (Multi-class-multi-label Classification and Information Retrieval), Explainable AI (Syntax Tree Guided Semantic Explanation), Computational Linguistics (Distributional Semantics) and Computational Psychiatry (valid and reliable modelling of Clinical Depression). I am in general interested in fundamental problems in Natural Language Understanding and their application to real life problems that matter.
Research
- I proposed embedding mapping algorithms that help learn better representation for depressive language detection.
- I proposed explainable Zero-shot Learning (ZSL) models for depression symptoms detection task which are precursor to the recent prompt based models.
- I proposed an LLM Driven Semi-supervised Learning (SSL) framework for developing robust models for Depression symptoms detection task.
- I developed a Deep Temporal (DT) model for clinical depression detection over social media users' timeline.
- My Depression Level Detection model from Reddit posts, stood 3rd out of 30 teams participating from all over the world.
- I have few works on Depressive Emotions detection and their sequential modelling.
- My work got several citations and coverage in media.
Teaching
- I taught senior year course in algorithm design for computer networks during my PhD.
- I taught Database Management System, Computer Architecture, Operating Systems, Cryptography and Introductory Computer Science courses while I was a master's student at the University of Lethbridge.