Salaar Liaqat

40 St. George St ยท Toronto, ON, Canada, M5S 2E4

I am a PhD candidate at University of Toronto, studying under the supervision of Eyal de Lara and Alex Mariakakis. My research interests are wearable sensing, with applications to healthcare and assistive technologies, as well as machine learning.


University of Toronto

PhD in Computer Science
Supervisors: Eyal de Lara and Alex Mariakakis

GPA: 3.93/4

February 2020 - Present
Masters in Computer Science
Supervisor: Eyal de Lara

GPA: 3.83/4

June 2018 - February 2020

Simon Fraser University

Bachelors of Science
School of Computer Science: Software Systems

GPA: 3.71/4.33

September 2015 - May 2018


Programming Languages
  • Proficient in C, C++, and Java
  • Proficient in Python and libraries such as NumPy, Pandas, SkLearn, Tensorflow, Keras and Spark
  • Experienced with MatLab, Go Lang, Scheme, Haskell and Ruby
  • Proficient in Android development
  • Proficient in embedded systems and hardware development on Linux and bare metal
  • Strong understanding of database concepts, SQL and NoSQL
  • Experienced in web development, including Flask, VueJS, AngularJS and ASP.NET
  • Strong knowledge in machine learning, natural languge processing and signal processing
  • Solid understanding of computer architecture, multi-threaded programming and distributed systems
  • Experienced in working with teams (2-7) members, scrum and taking leadership roles


Hindsight is 20/20: Retrospective Lessons for Conducting Longitudinal Wearable Sensing Studies

Awarded Best Paper

Salaar Liaqat, Daniyal Liaqat, Tatiana Son, Andrea Gershon, Moshe Gabel, Robert Wu, Eyal de Lara

Remote COPD Severity and Exacerbation Detection Using Heart Rate and Activity Data Measured from a Wearable Device

Abhishek Tiwari, Salaar Liaqat, Daniyal Liaqat, Moshe Gabel, Eyal de Lara, Tiago H. Falk

Sharing is Caring: Exploring machine learning-enabled methods for regional medical imaging exchange using procedure metadata

Salaar Liaqat, Joanna Pineda, Jeevaa Velayutham, Allen Lee, Joshua Reicher, Jason Nagels, Marzyeh Ghassemi, Benjamin Fine


Predicting Low Oxygen Saturation of COVID-19 Patients Using a Random Forest Classifier

Salaar Liaqat, Tiago H. Falk, Teresa To, Nisha Andany, Nisha Patel, Robert Wu, Andrea Gershon, Alex Mariakakis, Eyal de Lara, Daniyal Liaqat

Symptom Burden in Patients of Different Ages with Acute COVID-19 Infection Quarantining at Home

Andrea Gershon, Nisha Patel, Salaar Liaqat, Daniyal Liaqat, Eyal de Lara, Teresa To, Nisha Andany, Tiago H. Falk, Robert Wu

Trends in Oxygen Level During Acute COVID-19 Infection in Patients Quarantining at Home

Andrea Gershon, Nisha Patel, Robert Wu, Salaar Liaqat, Daniyal Liaqat, Eyal de Lara, Alex Mariakakis, Andrew Simor, Philip Lam, Sameer Masood, Nisha Andany, Nick Daneman, Andrienne Chan, Teresa To, Tiago H. Falk

Work Experience

Research Intern

Samsung AI Center - Samsung Research

Worked with the Systems Team and the Vision Team on cloud based machine learning

Summer 2021

Teaching Assistant

University of Toronto

CSC110 (Foundations of Computer Science I): Responsibilities included holding office hours and marking assiggments/projects

Fall 2021

Teaching Assistant

University of Toronto

C4M (Computing for Medicine): Responsibilities included assisting lectures and maintaining assignments

Fall 2020 - Winter 2021

Teaching Assistant

University of Toronto

CSC108 (Introduction to Computer Programming): Responsibilities included holding office hours and marking exams

Fall 2020

Teaching Assistant

University of Toronto

CSC148 (Introduction to Computer Science): Responsibilities included leading lab activies, assisting in lectures and marking exams

Winter 2019, Summer 2019, Fall 2019, Winter 2022


Regional Medical Imagaing Mapping for Procedure Exchange
  • Developed models to enable hospitals with different terminology to map procedures to a single standardized ontology
  • Explored various NLP representations and ML models and achieved over 95% accuracy on a 1500+ class dataset
  • Work featured on SIIMcast podcast and presented on Canada Health Infoway as a webinar to healthcare professionals across Canada
  • Work is being presented at Women in Machine Learning (WiML) at NeurIPS 2019 in Vancouver
  • Work published in AMIA Informatics Summit 2020 in Houston
  • Project was completed as a collaboration between University of Toronto, Trillium Health Partners, Vector Institute, and the Hospital Diagnostic Imaging Repository Services
  • SIIMCast Podcast
  • Canada Health Infoway Webinar
Feb - Dec 2019
Real-Time Audio Captioning with Augmented Reality Smart-Glasses
  • Developed assistive technology to enable people who are deaf or hard of hearing to understand speech
  • Used Moverio BT-300 Smart Glasses to record sound and display captions
  • Developed custom speech detection algorithm to filter sound on glasses
  • Used the Kaldi speech recognition toolkit running on edge server to transcribe speech audio to text in real-time
  • Achieved latency of 1.8s for sentence transcription using the edge system
  • Ran preliminary study and participants found the latency to be usable
  • Report
July 2018 - Nov 2018
Elevator Monitor
  • Developed an elevator monitoring system using two BeagleBone computers
  • BeagleBone would record elevator location using distance sensors
  • Developed and used protocol for radio frequency communication between BeagleBones
  • Second BeagleBone would communicate with first beaglebone and display elevator information on NodeJS site over local network
  • Developed sensing and communication code in C
Sept - Dec 2017
  • Developing a camera and gallery Android application which categorizes photos using machine learning based on image recognition
  • Used image recognition web service and built in image recognition model to allow online and offline functionality
  • Developed search functionality to find pictures using keywords, color, date and logical expressions
Sept - Dec 2017
Gait Analysis
  • Used Android phone to collect accelerometer and gyroscope traces of participants walking
  • Used Python to analyze traces and calculate step count and walking distance
  • Used traces to identify walking patterns of different users using machine learning (Naive Baye) and step detection
  • Completed analyses in Python, using NumPy, Pandas, SkLearn
July - August 2017
Smart Terrarium
  • Created a smart terrarium, in a team of 4, which presented controls to maintain an environment to support plant life
  • Used a temperature, humidity and brightness sensor to record the environment
  • Used a BeagleBone computer to control lights, humidifier and fans to optimize the environment
  • Designed a web application using NodeJS to remotely control and monitor terrarium
  • Programmed the embedded system in C and JavaScript
Sept - Dec 2016
Vending Machine
  • Worked in a team of six to create an embedded system to control a vending machine
  • Allowed users to use NFC to login to accounts and a touch screen interface to dispense snacks from the machine
  • Created using Arduino and Raspberry Pi
Sept - Dec 2015

Awards & Certifications

  • Qualified as Golden Key International Honor Society Member
  • Awarded SFU Alumni Scholarship ($500) in February 2016
  • Awarded Passport to Education Scholarship ($500) in September 2015
  • Distinguished as a National AP Scholar in July 2015