Publications

• LRS-DAG: Low Resource Supervised Domain Adaptation with Generalization Across Domains. [Talk]
  Rheeya Uppaal
  In the New in ML Workshop of the Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019).
• Multi-resolution Attention with Signal Splitting for Multivariate Time Series Classification.
  Rheeya Uppaal, Bryon Kucharski, Bhanu Pratap Singh, Iman Deznabi, Madelina Fiterau.
  Time Series Workshop of The Thirty-sixth International Conference on Machine Learning (ICML 2019).
• Overcoming Practical Issues of Deep Active Learning and its Applications on Named Entity Recognition.
  Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, Andrew McCallum.
  In the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2020) (Journal Track)
• Long Document Summarization in a Low Resource Setting using Pretrained Language Models
  Ahsaas Bajaj, Pavitra Dangati, Kalpesh Krishna, Pradhiksha Ashok Kumar, Rheeya Uppaal, Bradford Windsor, Eliot Brenner, Dominic Dotterrer, Rajarshi Das, Andrew McCallum
  In the ACL-IJCNLP Student Workshop, 2021.
• Exploring Robust Vehicle Detection and Tracking Methods for Various Illumination Settings using Infrared Thermographic Images
  Rheeya Uppaal.
  In the International Journal of Research in Advent Technology, Special Issue National Conference NCPC, 2016.
• Leveraging One's Impact Through Digital Persona and Image Management for Enhanced Effectiveness and Competitive Advantage.
  Kuiljeit Uppaal, Rheeya Uppaal
  Elsevier, 2018.
• Exploring the Facets of Colonization of the Red Planet – Mars.
  Rheeya Uppaal
  In the Student Conference on Emerging Technologies and Innovations, 2014.

Projects and Unpublished Works

• Multi-resolution Networks For Flexible Irregular Time Series Modeling (Multi-FIT)
  Bhanu Pratap Singh, Iman Deznabi, Rheeya Uppaal, Bryon Kucharski, Bharath Narasimhan, Akhila Josyula, Madelina Fiterau.
  Unpublished.
• Combating Unbalanced Datasets with Generative Adversarial Networks
  Rheeya Uppaal.
  Presented at the Women in Data Science Central Massachusetts Conference (WiDS 2018).
• Transfer Learning for Question to Answer Ranking Problems in New Domains
  Rheeya Uppaal
  Work done as part of industrial independent study with Microsoft Research Montreal.
• Exploring Matching Networks for One Shot Learning
  Rheeya Uppaal
  Class Project for UMass CS674: Intelligent Visual Computing.
• Character Identification in Multi-party Dialogue settings using Convolutional Neural Networks
  Rheeya Uppaal
  Class Project for UMass 585: Introduction to Natural Language Processing.
• Using Region based Convolutional Neural Networks to create a system to detect, track and classify vehicles from video footage.
  Rheeya Uppaal
  Work done as part of an internship with Prof Balaraman Ravindran at the Indian Institute of Technology, Madras.
• Facial Recognition using Convolutional Neural Networks
  Rheeya Uppaal
  Work done as part of an internship with Prof Virendra Singh at the Indian Institute of Technology, Bombay.