NSERC Discovery Grant

2020 - 2025

• Title: Semantic Web Analysis over the Nova Scotia Open Data
• Amount: $ 156,000
• Research assistants: Devanshika Gosh, Rishi Midha, Tamanna Moharana, Chandrayog Yadav, Karishma Kumar

New Health Investigator Grant - Research Nova Scotia

2022 - 2024

• Title: Identifying Alternate Level of Care (ALC) Patients Levergaing Machine Learning Algorithms
• Amount: $ 97,418
• Research assistants: TBD

Mitacs Globalink - Mitacs

2022

• Title: Graph Neural Network Using Knowledge Graphs
• Amount: $ 4,250
• Interns: Debjit Sarkar and Saloni Rakholiya

CBU RISE grant

2022

• Title: Explainable Clinical Decision Support System using Knowledge Graph
• Amount: $ 7,600
• Research assistants: TBD

Industrial Research Assistance Program (IRAP)

2020 - 2021

• Title: Predicting healing time on a Wound dataset using feature engineering techniques
• Budget: $ 5,000
• Research assistants: Tressy Thomas, Ankit Anand

CBU RISE grant

2021

• Title: Multi-label Text Class Classification Using Knowledge Graphs
• Amount: $ 7,800
• Research assistants: Divya Prabhu, Muhan Kumar Ganta, and Tressy Thomas

Mitacs Research Training Award

2020 - 2021

• Title: Building a Knowledge Graph on Top of Open Statistical Data
• Amount: $ 6,000
• Research assistants: Rishi Midha

CBU RISE grant

2020

• Title: Data Imputation using KNN Algorithm
• Amount: $ 7,400
• Research assistants: Tressy Thomas

Industrial Research Assistance Program (IRAP)

2019 - 2020

• Title: Building a data analytics dashboard on how2trak database in clinical practice
• Amount: $ 5,000
• Research assistants: Devanshika Gosh

Predictive Analytics (MGSC 5125)

2020 - present

• Course objectives:
  • students will learn how to discover interesting things and reveal valuable information from data by selecting a proper model
  • apply machine learning methods to build predictive models and discover patterns in data
  • learn diverse kinds of regressions (linear, nonlinear, and logistic)
  • learn four modeling techniques will be used: k-nearest neighbors, classification, and regression trees .
• Software: Python
• Material for learning:
  • Slides as well as practical examples will be provided alongside the textbook in the class
  • Textbook 1: Abbott, D. Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst. 2014.
  • Textbook 2: Hastie, T., Tibshirani, R., & Friedman, J. The elements of statistical learning: data mining, inference, and prediction (12th Edition). Springer Science & Business Media, 2017.
  • Textbook 3: Witten, I. H., Frank, Eibe, Hall, Mark A. Data Mining: Practical Machine Learning Tools and Techniques. 1884-1970.; Palestro, Christopher J.

Postdoctoral fellow position

For this position, we are looking for a motivated PostDoc candidate who is interested in applying his/her computational skills to real-world healthcare problems. This position will be initially available for one year. The grade of appointment will be accorded based on candidate’s academic qualifications and years of relevant experience.

• Requirements:
  • Ph.D. in computer science, or a related field with a research focus on machine learning
  • Great interpersonal communication, creative thinking, and problem-solving ability
  • Demonstrated record of high-quality publications in the field of machine learning
  • Demonstrated analytical, verbal, and scientific writing skills
  • Demonstrated record of high-performance scientific programming with python
  • Working on the healthcare projects will be an asset.
• Responsibilities
  • Major responsibility of the selected candidate is to develop machine learning models (i.e. neural networks) to solve healthcare challenges. The selected candidate will also be involved in managing, extracting and pre-processing data for various projects.
• Place of work
  • In accordance with Canadian Employment and Immigration guidelines, applicants must be eligible to work in Canada.
  • The applicant must be in Nova Scotia province during the employment.
• How to apply
  • Send an email with subject “postdoc-ML-2022” with the following documents to enayat_rajabi@cbu.ca: CV, cover letter, and two sample publications.
  • Employment start date to be mutually agreed. Please submit your application by 2023/12/31.

PhD position

We are looking for a new enthusiastic and creative PhD student. Candidates should have:

• Requirements:
  • A Masters degree in Computer Science
  • GPA of at least 3.4/4 or equivalent
  • Demonstrated fluency in English (e.g., first language, degrees taught in English, IELTS (all categories of >=7), TOEFL (>=100) or equivalent test results)
  • Experience with databases, data visualization, and data analysis, including familiarity with a scripting language (e.g., Python or R)
  • Knowledge of machine learning and deep learning techniques
  • Ability to work independently and within a team environment
  • Effective oral and written communication, analytical, and interpersonal skills
  Bonus points:
  • Familiarity with knowledge graphs and Semantic Web technologies
  • Passion for working on health-related issues
  • Prior experience in bioinformatics
  • Experience in writing scholarly articles
• How to apply:
  We encourage all qualified applicants to apply. Our lab is strongly committed to diversity and especially welcomes applications from all underrepresented groups. Our values regarding equity and diversity are linked with our commitment to excellence in the pursuit of our academic mission. Applicants should send:
  • Brief cover letter including most relevant experience, and career goals.
  • CV detailing academic training, research to date, and list of publications (if any).
  • Unofficial academic transcripts.
  • A sample publication (if any)
  Qualified applicants will be invited for an interview, and two references will be requested prior to final hiring decisions. Please send applications to somayeh.kafaie@smu.ca