I am currently a Fulbright Scholar at Princeton University, Department of Computer Science, RBC Fellow and PhD candidate at the Department of Computer Science (DCS), University of Toronto (UofT) and Vector Institute of AI.
My research interests include natural language understanding (NLU), (multi-modal) semantic representation, probabilistic graphical models (PGMs), artificial general intelligence (AGI). My research philosophy is driven by the imminent need for 'non-expert' human users communicating meaningfully with ubiquitous AI agents using natural language interfaces across modalities (text, speech, or gesture). What does it mean to achieve true language understanding for AI agents? Can we do better than trial-and-error (supervised) model training? Most recently, I've been exploring the 'Symbol Grounding Problem' (Harnad) and semantic multi-modal representation using PGMs.
Past: MIT CSAIL; IBM Redbooks (Research Triangle Park, Raleigh), IBM Research, SWG; MBA @ Rotman School of Management, UofT; Research @ Creative Destruction Lab; Founder @MutuoHealth, @Finatechal;
I have an eclectic mix of research experience in various ML sub-domains like NLP, Computer Vision and Reinforcement-Learning. My over-arching research interest/goal lie in endowing AI agents with the ability to autonomously acquire skills for executing complex multi-modal tasks. Specifically, how can AI agents learn from 'non-expert' human feedback using natural interfaces like speech, text, gestures etc.
Selected publications and current papers (in progress) can be found here:
Published as Mobile Enterprise Thought Leader, IBM Redbooks, Research Triangle Park, Raleigh, NC:
Saqur, R. (2014, February 5). Mobile web app: Five practices for handling device orientation changes. IBM Developer Works, The Mobile Frontier. link
Saqur, R. (2014, Jan 20). Four reasons for using Node.js to simulate mobile business services layer. IBM Developer Works, The Mobile Frontier. link
Saqur, R. (2013, November 27). IBM Worklight: Using LESS for smarter styling. IBM Developer Works, The Mobile Frontier. link
Industry Relevant R&D Work::
Saqur, Raeid (2016). Richr, RichrPro iOS Apps. Apple AppStore. (R&D work at Finatechal Inc.) Apple iTunes
Saqur, Raeid (2017) Richr Android App. Google PlayStore. . (R&D work at Finatechal Inc.) Google Playstore
Saqur, Raeid (2016). Open-source library: objective-C iOS Homekit scaffolding for IoT devices. (R&D work at Ecobee Inc.) Github
Saqur, Raeid (2015). HomeKit and Alexa enabled Ecobee3 Smart Thermostat with voice command interface. (R&D work at Ecobee Inc.) Apple iTunes
Saqur, Raeid (2014). Bell OrderMax Guided Process for Order Completion. 65% efficiency increase in 6000 call-centers globally, resulting in $2M decreases bottom line. (R&D work at IBM Canada).
Saqur, Raeid (2013). Pioneering work on mobile Cheque Deposit, Cheque-InTM, on iOS and Android platforms and contributing to open-source Tesseract OCR engine. (R&D work at IBM Canada).
Saqur, Raeid (2012). TD Waterhouse Wealth management SDK and Mobile Web Brokerage. Awarded ‘Best of IBM’ award in recognition of industry impact and innovation. (R&D work at IBM Canada)
Saqur, Raeid (2011). First ever hybrid embedded web carousel for native mobile apps. Aeroplan.
Saqur, Raeid (2009). IBM WBP merger algorithm and visualizer. (Engineering Intern at IBM SWG).
Please see archive course website here (Fall 2020 site requires UofT internal portal access). My focus topics/areas: Linear filters, edge detection, image semantic segmentation, deep learning
Please see course website here. My focus topics/areas: Game Tree Search, Bayes Nets/HMMs
NLP using classical techniques with segue to modern elements
Intro to theory of computation using algorithm analysis and provability
First Canadian lecturer leading Quantopian’s vision of inspiring talented people everywhere to write investment algorithms. Lectured workshops with 60+ professionals doing hands-on coding in python of advanced quantitative topics like using text extraction and sentiment analysis using machine learning.
Graduate lecturer for Prof.JanMahrt-Smith’s class teaching graduate level quantitative finance to MBA & Fin. Engineering students
Random (and definitely not exhaustive) listings:
I consider myself as a generalized specialist. I think meta-learning or the ability to learn fast is my biggest strength above anything and everything else.
I have played 3 sports semi-professionally: soccer, cricket and chess (if you allow chess to be considered as a sport i.e. ). I am an aficionado of politics, algorithmic trading, macro-economics, and human psychology (besides the usual tech geek stuff like Star Wars and GPUs :) .