I'm currently on the job market for machine learning/natural language processing scientist positions in the industry.
May 2020: Internship work on Machine Translation covered by Slator.
Mar 2020: Gave a talk on 'Detecting Population-Level Societal Events from News Articles' at MASC-SLL, University of Maryland, College Park.
Feb 2020: Check out my DAC student spotlight!
Jan 2020: Selected as a recipient of Twitch (Amazon) Research Fellowship 2020!
Nov 2019: Paper about adapting generic Black-Box MT systems to specific domains accepted to AAAI 2020!
July 2019: Excited to present our paper on event detection using multi-aspect attention at the DLRL Summer School in Edmonton, Canada!
May 2019: I'll be spending another summer at Netflix working on Neural Machine Translation.
Jan 2019: 1 paper accepted to The Web Conference 2019!
Jan 2019: Best paper award at IUI 2019!
May 2018: I'll be spending the summer at Netflix working on Neural Machine Translation hosted by Ritwik Kumar, Boris Chen and Vinith Misra.
Aug 2017: Our submission for automatic narrative generation from a large collection of documents selected for the final round of ODNI Xpress Challenge!
April 2017: I'll be joining Discovery Analytics Centre as a PhD student in summer advised by Dr. Naren Ramakrishnan!
April 2017: The undergraduate students that I supervised and worked with on the PhotoSleuth project won 1st place at VTURCS Spring Symposium.
Nov 2016: Presented our paper and poster on understanding human performance in image geolocation at the GroupSight workshop at HCOMP 2016!


I am a PhD candidate in the Computer Science department at Virginia Tech's College of Engineering, advised by Prof. Naren Ramakrishnan.
My research falls under the umbrella of Natural Language Processing, Deep Learning and Data Mining.

Currently, I am affiliated with Discovery Analytics Centre (DAC) . Before joining DAC, I have worked at the Crowd Intelligence Lab at Virginia Tech where I was involved in building intelligent systems combining crowdsourcing and AI.

I've spent two wonderful summers('18 & '19) at Netflix where we concieved a novel machine learning solution for a practical problem. Prior to joining grad school, I double majored in Computer Science and Mathematics from Birla Institute of Technology and Science (BITS), Pilani. During my undergrad I have dabbled with Computer Graphics leading to my Masters thesis titled 'A Comparative Study of Rendering Techniques' where I implemented and compared the performance of Ray Tracing and Reyes Image Rendering techniques. After graduating I joined Dreamworks Animation as a Technical Director on the feature film Penguins of Madagascar (2014) and later moved to an engineering role in R&D. Some of the places I have interned at during my undergrad include Dreamworks Animation (spring '14), GlobalLogic (summer '11 & '12) and Harish Chandra Research Institute (mid-summer '12). I was a recipient of the MITACS Globalink Research Internship grant in summer '13 which I spent in Memorial University of Newfoundland, Canada.

My research is graciously supported by DARPA and NSF.


  • Reviewer TKDD Journal

  • Reviewer EMNLP 2020

  • Reviewer Rep4NLP Workshop, ACL 2020

  • Program Committee: Rep4NLP at ACL 2020

  • Reviewer ACL 2020

  • Sub-Reviewer KDD 2019

  • Student Volunteer at CVPR 2016, Las Vegas.

  • Publications

    Simplify-then-Translate: Automatic Preprocessing for Black-Box Translation
    Sneha Mehta, Bahareh Azarnoush, Boris Chen, Avneesh Saluja, Vinith Misra, Ballav Bihani, Ritwik Kumar
    In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI '20)
    Event Detection Using Hierarchical Multi-Aspect Attention
    Sneha Mehta, M. Raihanul, Huzefa Rangwala, Naren Ramakrishnan
    In Proceedings of the 30th Web Conference 2019 (WWW '19)
    Low Rank Factorization for Compact Multi-Head Self-Attention
    Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan
    Arxiv Preprint
    Supporting Historical Photo Identification with Face Recognition and Crowdsourced Human Expertise
    Vikram Mohanty, David Thames, Sneha Mehta, Kurt Luther
    In Proceedings of International Joint Conference on Artificial Intelligence - Pacific Rim International Conference on Artificial Intelligence (IJCAI'20)
    [to appear]
    PhotoSleuth: Combining Human Expertise and Face Recognition to Identify Historical Portraits
    Vikram Mohanty, David Thames, Sneha Mehta, Kurt Luther
    In Proceedings of the 24th International Conference on Intelligent User Interfaces (IUI'19)
    An Exploratory Study of Human Performance in Image Geolocation
    Sneha Mehta, Chris North, Kurt Luther
    Workshop on Human Computation for Image and Video Analysis @ The Fourth AAAI Conference on Human Computation and Crowdsourcing (HCOMP'16)
    Photo Sleuth: Identifying Historical Portraits with Face Recognition and Crowdsourced Human Expertise
    Vikram Mohanty, David Thames, Sneha Mehta, Kurt Luther
    In Special Issue of ACM Transactions on Interactive Intelligent Systems (TIIS)
    [to appear]

    Selected Projects

    Siamese Network for Binary Visual Question Answering
    We study the performance of a siamese network based deep neural architecture on the task of binary(Yes/No) visual question answering. Comparing the performance of a siamese network based VQA model to a non-siamese VQA model we find that having a pairwise loss helps perform better than a loss from a non-siamese VQA network.
    Sneha Mehta, Yash Goyal (Project advisor: Prof. Devi Parikh).
    Extracting Topics from Tweets and Webpages
    We develop the topic analysis component of a robust Information Retrieval system for search and retrieval of large-scale tweets and webpages built on top of Solr, a general purpose open-source search engine. Our contribution enables semantic search and retrieval of tweets and webpages based on topics.
    Sneha Mehta, Radha Krishnan Vinayagam (Project advisor: Prof. Edward Fox).
    Birds in a Forest
    We employ a random forest approach for bird species identification. First we train 25 SVMs to predict 25 bird features for our dataset images. Then we train a random-forest to identify the specific bird species. We used the CUB-200-2011 bird dataset for this task.
    Sneha Mehta, Aditya Pratapa, Phillip Summers (Project advisor: Prof. Bert Huang).
    Targeted Summary Generation
    Given a question, our narrative generation pipeline generates a natural language response to that question from the given dataset of articles and the associated metadata. (This was a submission to the ODNI Xpress challenge where it was a finalist.)
    Sneha Mehta, Rupen Paul Khandpur
    TD Transfer
    The aim of this tool is to simplify the transfer of data between different studio locations of the world. Some of the features include directory view indicating synced and out-of-sync files, scheduling transfers, transfer status, weather, analytics etc. This is built on top of Python Twisted (Asynchronous Event Framework) and xmlrpc protocol. (This was work done during an internship at Dreamworks Animation).
    Sneha Mehta, Utkarsh Sinha
    Seam Carving
    Seam-carving is a dynamic programming based algorithm for content-aware image resizing developed by Ariel Shamir. In the above example, the algorithm reduces the width of the image by finding and removing vertical seams of pixels (pixels with the least information content) between the girl and the cliff edges.
    Image Warping
    Creating image panorama by image warping based on homographies. In the first example (left), the image on the bottom is the panorama created by warping (by computing a homography matrix) and stitching together the three images above. In the second example(right), a photo of mine was warped and merged onto a billboard in a Times Square image.


    Automatic Question Generation
    Given a sentence automatically generate reading comprehension style factual questions from that sentence, such that the sentence contains answers to those questions.


    Invited to VT Alumni Event, Arlington Virginia, Nov 2019 (Story).


    An interview summarizing my early life as an athlete.
    Copyright © Sneha Mehta (Me) 2015. All rights reserved.