Subho (Subhojeet Pramanik)

Subho (Subhojeet Pramanik)

MSc Student

RLAI, University of Alberta

" The truly unique feature of our language is not its ability to transmit information about men and lions. Rather, it’s the ability to transmit information about things that do not exist at all. As far as we know, only Sapiens can talk about entire kinds of entities that they have never seen, touched or smelled. " — Yuval Noah Harrari

Hey there, I am a MSc student at the University of Alberta working on Reinforcement Learning and Artificial Intelligence. I am currently co-supervised by Adam White and Marlos Machado; and affliated with RLAI Lab and Alberta Machine Intelligence Institute (Amii). My long term research goal is to define and understand the computational principles behind Intelligence.

My current MSc research is centered around understanding how an agent in a complex environment perceives a stream observations. In a real-world setting an agent’s immediate observation is not very informative (non Markovian), and the true-state of the world is always mammoth compared to the agent. In my research, I’m exploring how an agent can build short and long-term memories from a stream of observations which can then be used to generate an agent’s perception at a given time (an approximate Markov-state). The agent then uses its immediate perception for prediction or control.

Previously I had worked with IBM Cloud as an ML Engineer and also collaborated with IBM Research over various research projects in representation learning and Deep Learning. I’m also an avid coder, and have experience in deployment of several machine learning algorithms at scale in IBM and Kone.

Contact: spramanik [at] ualberta [dot] ca, email [at] subho [dot] in


  • Reinforcement Learning
  • Representation Learning
  • Deep Learning


  • MSc in Computer Science (thesis based, Fully funded), 2021 - 2023

    University of Alberta

  • B.Tech in Computer Science and Engineering, 2015 - 2019

    Vellore Institute of Technology



Graduate Teaching Assistant

University of Alberta

Sep 2019 – Present Edmonton, Canada
  • Teaching Assistant for CMPUT174: Introduction to Computation 1.


  • Teaching Assistant for CMPUT365: Introduction to Reinforcement Learning (Instructor: Adam White)

AI/ML Developer

IBM, Cloud

Sep 2019 – Jul 2021 Bangalore, India

Primarily assigned as an AI/ML Developer for IBM App Connect:

  • Part of the newly minted AI team responsible for Research → Development → Productionization of Mapping Assist feature for IBM Appconnect, Cloud Pak for Integration release.
  • Introduced a novel unsupervised technique for database schema matching, and deployed the same using ONNX+FastAPI+Docker pipeline.

Actively collaborating with IBM Research:

  • Worked towards a AAAI, 21 submission to learn a generic document representation by leveraging multi-page, multi-modal text & visual information in real-world PDF documents. (Mentors: Dr. Sameep Mehta, Shashank Mujumdar, Hima Patel)


IBM, Watson IoT

Jan 2019 – Jul 2019 Bangalore, India

Intern at the IBM Watson TRIRIGA Building Insights team.

  • Researched on methods to formulate and predict HVAC efficiency and the factors that cause HVAC degradation. Proposed a decision tree based approach for HVAC failure detection and root-cause analysis. (Mentors: Alex J Joseph, Sattwati Kundu)
  • Actively collaborated with Priyanka Agrawal from IBM Research towards a research publication: OmniNet: A unified architecture for multi-modal multi-task learning

Founding Partner

Cognibit Solutions LLP

Jan 2018 – Jan 2019 Remote & Finland

Responsibilities include:

  • January 2018 - December 2018 (Remote contract work with Kone Corporation, Finland): Achieved record accuracy in predicting elevator door failures and scheduling service needs from elevator sensor logs.
  • January 2019 (On-site collaboration with Kone R&D team and IoT team at Finland): Deployed the developed predictive maintenance solution on IBM Kubernetes platform.

Visiting Researcher

Kone Corporation

May 2017 – Jun 2017 Hyvinkää, Finland

Selected amongst hundreds of competitors in Kone IBM hackathon for a two month sponsorship to Kone in Finland as a visiting researcher.

  • Performed predictive modeling of customer callouts with elevator log data using LSTM which acheived record accuracy.
  • Performed statistical modeling & diagnostics of Kone’s german elevator data extracted from the Remote Maintenance Program which yielded commercially valuable insights.

Mentors: Dr. Olli Mali, Jani Hautakorpi