Shikib Mehri

M.S. Language Technologies (continuing to PhD) @ CMU

Graduate Research Assistant @ DialRC

Currently, I'm a Masters of Language Technologies student at CMU's Language Technologies Institute. I'm working on dialog systems, advised by Maxine Eskenazi as part of the DialRC group.

Some recent news:

  • Doing an internship at Amazon this summer! Excited to be working with Dilek Hakkani-Tur and Mihail Eric.

  • One paper accepted to SIGdial 2020. Details to follow soon.

  • Two papers accepted to ACL 2020. One paper introduces the USR metric and another examines none-of-the-above prediction in dialog retrieval

  • I was accepted to continue my PhD at CMU! Estimated graduation is 2022 - 2023.

  • Won best paper at SIGdial 2019 for our work on Structured Fusion Networks!

  • A paper accepted to EMNLP 2019 titled Multi-Granularity Representations of Dialog. We show that you can learn multipe granularities of representation by controlling the negative candidates during the task of dialog retrieval.

  • Two papers accepted at SIGdial 2019!. I'll be giving a talk on Structured Fusion Networks and will have a poster on our multi-reference dataset. I'll also be giving a talk at the Dialog for Good workshop about our dialog system for seniors, CMU GetGoing.

  • I had a paper accepted to ACL 2019 on dialog-specific pretraining objectives. We introduce several novel pretraining objectives that obtain good performance results and show pretraining to result in better generalizability, less data-hungry models and faster convergence.

  • I had a publication accepted to NeurIPS 2018! My paper introduces the Middle-Out Decoder which uses self-attention to generate sequences from the middle-out rather than left-to-right.

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



  • Aug 2018 - Aug 2020

    Masters of Language Technologies

    A student in the Language Technologies Institute at Carnegie Mellon University. I am supervised by Profs. Maxine Eskenazi and Alan Black

  • May 2018 - Aug 2018

    Scientist Intern

    As a scientist intern on the Alexa AI team, I developed novel approaches for conversational speech recognition, yielding significant improvements in both quantitative and qualitative evaluation. A publication is in the works.

  • Sept 2017 - July 2018

    Research Assistant

    Worked with Prof. Leonid Sigal on video captioning. I developed a novel middle-out sequence decoder, attaining state of the art results. A publication has been accepted to NeurIPS 2018.

  • Jan 2018 - Apr 2018

    Graduate Teaching Assistant

    Teaching assistant for Multi-Modal Deep Learning. Assisted with the design/development of assignments, as well as general TA duties. One of few undergraduates to ever TA a graduate class.

  • June 2017 - Sept 2017

    Data Scientist Intern

    As part of the Windows Feedback Analysis team, I constructed 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 - Aug 2018

    Bioinformatics Research Assistant

    As a member of the Wasserman lab at CMMT, I designed and implemented algorithms for read alignment on a graph based representation of the reference genome.

  • Aug 2016 - May 2017

    Research Assistant

    Worked with Prof. 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. I presented a publication at IJCNLP 2017.

  • 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 office 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

    I recently graduated with a major in Honours Computer Science (with co-op). I graduated with 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


CRA Outstanding Undergraduate Researcher Award.

2nd Place

Won 2nd place and crowd favourite at StartUp-Weekend Vancouver, for AlbertAI, a personal assistant that revolutionizes education.

3rd Place

Third place at LumoHacks for our application which utilized NLP to identify reddit/twitter users at risk of depression, and alert their friends.

Trek Scholar

Excellence scholarship for continuing students.


Charles and Jane Banks Scholarship.

Science Scholar

Received the science scholar distinction due to stellar academic performance.

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.