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[Curriculum Vitae]
[Google Scholar]
Dheeru Dua |
| Email: | ddua (at) uci (dot) edu |
| dheerudua (at) google (dot) com |
About Me
I am a Research Scientist at Google Deepmind. Prior to that, I completed my doctoratate in the Computer Science Department at University of California, Irvine, where I was advised by Dr. Sameer Singh and Dr. Matt Gardner. During my PhD, I was supported by HPI fellowship. I also obtained a Master's degree from Carnegie Mellon University, Pittsburgh. I have had the privilege to intern at Amazon (AWS) in summer 2020, Facebook AI reasearch (FAIR) in summer 2021 and Google Research in summer 2022.
Publications
- D. Dua, E. Strubell, S. Singh, P. Verga To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering [pdf] American Conference of Computational Linguistics (ACL). 2023
- D. Dua, S. Gupta, S. Singh, M. Gardner Sucessive Prompting for Question Decomposition [pdf] Empirical Methods in Natural Language Processing (EMNLP). 2022
- D. Dua, S. Bhosale, V. Goswami, J. Cross, M. Lewis, A. Fan Tricks for Training Sparse Translation Models [pdf] North American Conference of Computational Linguistics (NAACL). 2022
- D. Dua, P. Dasigi, S. Singh, M. Gardner Learning with Instance Bundles for Reading Comprehension. [pdf] Empirical Methods in Natural Language Processing (EMNLP). 2021
- D. Dua, C. N. dos Santos, P. Ng, B. Athiwaratkun, B. Xiang, M. Gardner, S. Singh Generative Context Pair Selection for Multi-hop Question Answering. [pdf] Empirical Methods in Natural Language Processing (EMNLP). 2021
- D. Dua, S. Singh, M. Gardner Benefits of Intermediate Annotations in Reading Comprehension. [pdf] Association of Computational Linguistics (ACL). 2020
- A. Gottumukkala, D. Dua, S. Singh, M. Gardner Dynamic Sampling Strategies for Multi-Task Reading Comprehension. [pdf] Association of Computational Linguistics (ACL). 2020
- D. Dua, Y. Wang, P. Dasigi, G. Stanovsky, S. Singh, M. Gardner DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. [pdf] North American Conference of Computational Linguistics (NAACL). 2019
- Z. Zhao, D. Dua, S. Singh. Generating Natural Adversarial Examples. [pdf] International Conference on Learning Representations (ICLR). 2018
- J.S. Kang, R. Logan, Z. Chu, Y. Chen, D. Dua, K. Gimpel, S. Singh, N. Balasubramanian PoMo: Generating Entity-Specific Post-Modifiers in Context. [pdf] North American Conference of Computational Linguistics (NAACL). 2019
- D. Dua, A. Gottumukkala, A. Talmor, M. Gardner, S. Singh. ORB: An Open Reading Benchmark for Comprehensive Multi-Dataset Evaluation of Reading Comprehension. [pdf] Workshop on Machine Reading and Question Answering (MRQA). 2019
Masters Projects
- Performed relation classification using distantly-supervised MultiR algorithm with features extracted by doing random walks on the Freebase graph. Achieved better results over state of the art systems at sentential and aggregate predictions.
- Built an event extraction system using passive- agressive conditional random fields for TAC KBP 2015.
- Used reinforcement learning approaches, DQN with MCTS guided policy for abstractive document summarization
- Worked on the NTCIR Question Answering task as a part of my Master's thesis and experimented with various components, some of which are listed below.
- Wikipedia link graph, which was used to continually search and retrieve relevant documents to answer the questions.
- Markov Logic Networks, which was used to build a sequence of events and use link-prediction for answering timeline based questions and as an event and entity graph for lookup.
- A UIMA based workflow which wrapped all the components.
Company Projects
- Designed and developed a torch-based framework for fast development and deployment of neural network models into production.
- Used Bing's knowledge graph to surface information cards about various frequently queried entities
- Developed an integration test framework which performed various image comparison techniques (using pHash, RMSE, Template matching algorithms) to test information cards deployed in production
Education
| PhD(CS) | MS(LTI) | B.Tech(CS) | High School |
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