M.S. Language Technologies @ 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 Profs. Maxine Eskenazi and Alan Black as part of the DialRC group.
Some recent news:
I recently had a publication accepted to NIPS 2018! My paper introduces the Middle-Out Decoder which uses self-attention to generate sequences from the middle-out rather than left-to-right.
This summer, I was a Scientist Intern in Alexa AI. I worked on conversational speech recognition, developing approaches to effectively utilize conversational context for ASR. I got good results and a paper is currently in the works.
In my last year at UBC, I (along with Thomas Liu and Raunak Kumar) started the UBC ML Club. I've started to clean-up/publicize some of the tutorials we made. Here's one on captioning and another on CycleGANs.
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!
Shikib Mehri, Leonid Sigal. "Middle-Out Decoding," In Neural Information Processing Systems (NIPS), 2018
Shikib Mehri, Giuseppe Carenini. "Chat Disentanglement: Identifying Semantic Reply Relationships with Random Forests and Recurrent Neural Networks," In International Joint Conference on Natural Language Processing (IJCNLP), 2017
A student in the Language Technologies Institute at Carnegie Mellon University. I am supervised by Profs. Maxine Eskenazi and Alan Black
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.
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 NIPS 2018.
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.
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.
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.
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.
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.
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.
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.
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.
Implemented functionality to detect incorrectly configured network switches and to change the assignment strategies for linerate capable ports in order to decrease downtime.
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.
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.
CRA Outstanding Undergraduate Researcher Award.
Won 2nd place and crowd favourite at StartUp-Weekend Vancouver, for AlbertAI, a personal assistant that revolutionizes education.
Third place at LumoHacks for our application which utilized NLP to identify reddit/twitter users at risk of depression, and alert their friends.
Excellence scholarship for continuing students.
Charles and Jane Banks Scholarship.
Received the science scholar distinction due to stellar academic performance.
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.
Placed 3rd at the 2017 Division 2 ACM-ICPC competition in the Pacific Northwest Region.
Obtained fourth place (first amongst undergraduate submissions) DataSense VanData competition. My submission can be found here.
Have received the Dean's List distinction every term I've been at the University of British Columbia.