Shikib Mehri

Honours Computer Science @ UBC

Data Science Intern @ Microsoft

Currently, I'm a Data Science Intern at Microsoft working deep learning for natural language understanding of Windows customer feedback. I've been getting a taste of the CNTK framework for deep learning, and am finding it to be a nice alternative to my go-to framework, PyTorch.

Recently, I submitted a paper describing my novel thread disentanglement pipeline, which achieved state of the art results. I did this work in collaboration with Dr. Giuseppe Carenini.

I'm also currently working at the Wasserman lab at CMMT on read alignment with a graph-based representation of a reference genome. I'm enjoying designing and implementing a number of interesting algorithms for this project, and am excited about our pipeline being near completion.

I've been spending some of my (limited) free time on some personal projects as well. Recently, I experimented with adding an attention mechanism to a dual encoder LSTM which predicts the probability of a message following a sequence of messages.

I'm also working on expanding my deep learning knowledge to speech-based models and am currently working on implementing a state of the art speech-to-text model.

Feel free to contact me if you have an interesting opportunity, you're interested in my work or you just want to chat about NLP or deep learning!


  • June 2017 - Sept 2017

    Data Scientist Intern

    As part of the Windows Feedback Analysis team, I've been constructing a number of deep learning based classification and semantic similarity models for the purposes of natural language understanding.

  • Jan 2017 - Mar 2017

    Software Engineering Intern

    On the Machine Translation team, I worked on the implementation of a number of subword Neural Machine Translation models to ultimately improve post and comment translation on Facebook.

  • Aug 2016 - Present

    Bioinformatics Research Assistant

    As a member of the Wasserman lab at CMMT, I've been working on designing and implementing algorithms for read alignment on a graph based representation of the reference genome.

  • Aug 2016 - May 2017

    NLP Research Assistant

    Worked with Giuseppe Carenini on the problem of thread disentanglement in multiparticipant chats. My approach employed novel strategies (including leveraging a weakly-supervised LSTM classifier) to attain state of the art results. A publication is currently under review.

  • Sept 2014 - Aug 2015
    Jan 2016 - Aug 2016
    Sept 2016 - Dec 2016

    Computer Science Teaching Assistant

    Taught CPSC 110, CPSC 213 (Computer Systems), CPSC 313 (Operating Systems), CPSC 304 (Databases). I ran labs containing 30+ students, lectured in tutorials, invigilated exams, held ofice hours and graded assignments and exams.

  • May 2016 - July 2017

    Software Engineering Intern

    On the Ads Targeting Modeling team, I worked on generating/evaluating user-interest mappings. I also constructed an incredibly accurate classification model to predict the correct categorization of a given interest.

  • Oct 2015 - June 2017

    Co-founder & CTO

    As the Chief Technology Officer of IntelliMed, a funded startup, I led developers in building an application which automates the process of writing pharmacy medication reviews for patients.

  • Sept 2015 - Dec 2015

    Software Engineering Intern

    Implemented functionality to detect incorrectly configured network switches and to change the assignment strategies for linerate capable ports in order to decrease downtime.

  • September 2013 - May 2018

    Honours Computer Science

    Entering my fifth year of studying Honours Computer Science (with co-op). I have a 4.20 cumulative GPA as well as a 4.33 in-major GPA.

  • Sept 2011 - May 2013

    University Transition Program

    One of 20 students to attend this rigorous, highly-accelerated program that condenses five years of highschool into two. I completed the program at the age of 14, leading to an early entrance to university.

Select Accomplishments

Science Scholar

Received the science scholar distinction due to stellar academic performance.


Was a finalist at the DataSense Salary Prediction competition. My submission can be found here.

2nd Place

Placed second at the Microsoft machine learning competition, where participants were required to use Azure ML to train/evaluate a model which predicts who'd survive on the Titanic.

1st Place

Won the Telus/IEEE Datathon. Our application, SaferSurrey used machine learning in combination with crime data from the Surrey RCMP to identify the safest route home through dangerous parts of the city. We won $3000 from the competition, as well as the opportunity to pitch our idea to the Surrey RCMP.

3rd Place

Placed 3rd at the 2017 Division 2 ACM-ICPC competition in the Pacific Northwest Region.

Prize Winner

Won the RapidAPI sponsor prize at DubHacks for our application CMPR.

4th Place

Obtained fourth place (first amongst undergraduate submissions) DataSense VanData competition. My submission can be found here.

Dean's List

Have received the Dean's List distinction every term I've been at the University of British Columbia.