Nawshad Farruque, PhD

Area of Study / Keywords

Artificial Intelligence Machine Learning Natural Language Understanding

About

Currently I am a Postdoctoral AI research Fellow at Edmonton Police Service. I earned my PhD in Artificial Intelligence from the University of Alberta. During PhD, my focus was on explainability friendly modelling of clinical depression through people's temporal language usage. The main challenge was to develop underlying clinical concept aware machine learning and NLP models when there is too little data to train these models. 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-label Classification and Information Retrieval), Explainable AI (Syntax Tree Guided Semantic Explanation), Computational Linguistics/NLP (Distributional Semantics) and Computational Psychiatry (valid and reliable modelling of clinical depression). Currently I am working on extracting knowledge from large unstructured datasets from varied sources with provenance and further leverage it for several downstream NLP tasks, such as Question Answering and Reasoning. I am in general interested in solving fundamental problems in Natural Language Understanding and apply those to important real life problems. 

I am looking for potential research collaboration in the areas listed below.

Research

Currently I am working on:

• Knowledge Extraction and Reasoning.
• LLM based RAG systems.
• LLM evaluation.
• LLM explainability.

During PhD level studies, 

• I developed:
  • embedding mapping algorithms (ECML, 2019) that help learn better representation for depressive language detection.
  • explainable Zero-shot Learning (ZSL) models (ICMLA, 2021) for depression symptoms detection task which are precursor to the recent prompt based models.
  • LLM Driven Semi-supervised Learning (SSL) framework (LRE, 2024) for robust modelling of Depression symptoms from text.
  • Deep Temporal (DT) model (NLPJ, 2024) for clinical depression detection over social media users' timeline, which works more like a PHQ-9 depression questionnaire.
  • My Depression Level Detection model (LT-EDI@ACL, 2022) stood 3rd out of 30 teams participating from all over the world in the competition for developing machine learning models for depression level detection through Reddit posts.
  • I have few works on Depressive Emotions detection (CICLing, 2019) and their sequential modelling (NAACL, 2021).
  • I have contributed in the papers on developing a framework for explainable AI (MLKE, 2021), Covid-19 misinformation detection through social media using transfer learning (ICTAI, 2021) and Legal Information Extraction (JURISIN, 2018).
• I implemented:
  • a Knowledge Graph based Question Answering system and delved deep into analyzing the algorithm and architecture of PROSPERA which is a Knowledge Graph based reasoning system.
  • a fast search engine for text, based on Broder et al.'s paper.
• I advised:
  • a team for depression detection from social media in their NLP graduate course.
• Reach:
  • My works got several citations and coverage in media.
• Achievements:
  • I was awarded Doctoral Recruitment scholarship for two terms during my PhD.
  • I was awarded a major interdepartmental award, named GRA Rice scholarship.
  • My PhD dissertation was nominated for outstanding PhD thesis.

During Master's:

• I implemented efficient distributed spatial semi-join algorithms for faster spatial query processing.
• I was awarded full scholarship for pursuing master's.
• I was awarded Bangladesh-Sweden trust travel grant.

Community Service

• I am a rolling reviewer of ACL.
• I have been invited as a reviewer/worked as a reviewer for: ACL, EMNLP, ECML-PKDD, EACL, IPM Journal, AIIM Journal.
• Served as a external reviewer in: IJCAI, CIKM, AAAI conferences.

Grants:

• I played major role in securing MITACS (Accelerate and Elevate), GRA Rice and DRDC grants during my academic career, total worth of ~ 1M CAD.

Teaching

• I taught senior year course in algorithm design for computer networks during my PhD at the University of Alberta.
• 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.

Google Scholar

DBLP