I am a third year CS PhD student in the UNC NLP lab at the University of North Carolina at Chapel Hill, advised by Prof. Mohit Bansal. Previously, I spent 1.5 years as Data Scientist at Sciome LLC, a budding health-informatics startup based out of Durham. I built Information Extraction pipelines for parsing scientific articles and converting the full-text into meaningful, structured data. I collaborated with bioinformaticians and cheminformaticians to develop deep learning models for gene expression extrapolation and toxicological assay image analysis.

I graduated with a Masters in Biomedical & Health Informatics from University of Washington School of Medicine and worked towards a thesis on extraction of clinical timeline from patient discharge summaries under the guidance of Prof. Meliha Yetisgen. At the same time, I was also a Research Assistant advised by Prof. Elaine O. Nsoesie (who has since moved to Boston University) at the Institute of Health Metrics & Evaluation. We developed novel machine learning approaches for public health research problems.

I completed my undergraduate (Integrated B.Tech & M.Tech) in Electronics & Electrical Communication Engineering, with specialization in Visual Info. Processing & Embedded Systems from Indian Institute of Technology, Kharagpur, India in 2015. My broad research interests are in Natural Language Processing, Machine Learning and Deep Learning.

Recent News

• April 2022 : Two new papers on curriculum learning (main track) and video-based multimodal intent discovery (findings) accepted to NAACL! Camera-ready papers coming soon.
• March 2022 : Our paper on contextual code search has been accepted to DL4C workshop at ICLR 2022! Explore and download openly available tool extension here.
• March 2022 : Received internship offers from Facebook Research and AllenAI (PRIOR)!
• August 2021 : Our paper on structured inputs for story visualization has been accepted to EMNLP 2021 for an oral presentation!
• July 2021 : Recognized as Outstanding Reviewer for ACL-IJCNLP 2021
• May 2021 : Our paper on code-generation from structured inputs has been accepted to Findings of ACL 2021!
• February 2021 : Our paper on story visualization has been accepted to NAACL 2021! (paper, code)
• January 2021 : Received internship offer from Adobe Research for Summer 2021!
• December 2020 : Published a preprint on the use of Technology in COVID-Response in African; now accepted to Scientific African. (paper)
• September 2020 : Our research paper "Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension" is accepted to the Findings of EMNLP, 2020. (paper, code)
• August 2019 : Joined the UNC NLP lab this fall for PhD in CS.
• July 2019: Research paper accepted to Journal of the American Medical Informatics Association (JAMIA) Open.
• June 2019: Research paper accepted at the ICML AI for Social Good Workshop 2019, Long Beach, CA.
• March 2019: PhD admits in the Ultrasound Imaging group at Johns Hopkins and NLP/ML group at University of North Carolina, Chapel Hill.
• November 2018: Presented work on biomedical information extraction at the Text Analysis Conference 2018, Gaithersburg, MD.
• August 2018: Research paper accepted to Journal of the American Medical Association (JAMA) Open and covered by leading news outlets.

Publications [Google Scholar] [dblp]

Methods

• Integrating Visuospatial, Linguistic and Commonsense Structure into Story Visualization (Oral)
  Adyasha Maharana and Mohit Bansal
  EMNLP 2021

• Analysis of Tree-based Input and Architecture for Code Generation
  Samip Dahal, Adyasha Maharana, and Mohit Bansal
  Findings of ACL 2021 [paper, code]

• Improving Generation and Evaluation of Visual Stories via Semantic Consistency
  Adyasha Maharana, Darryl Hannan and Mohit Bansal
  NAACL 2021 [paper, code]

• Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension
  Adyasha Maharana and Mohit Bansal
  Findings of EMNLP 2020 [paper, code]

Applications

• Use of Technology and Innovations in the COVID-19 Pandemic Response in Africa
  Adyasha Maharana, Morine Amutorine, Moinina David Sengeh and Elaine O. Nsoesie
  Preprint [paper]

• Detecting reports of unsafe foods in consumer product reviews
  Adyasha Maharana, Kunlin Cai, Joseph Hellerstein, Yulin Hswen, Michael Munsell, Valentina Staneva, Miki Verma, Cynthia Vint, Derry Wijaya and Elaine O Nsoesie
  Journal of the American Medical Informatics Association (JAMIA Open), 2019 [paper]

• Quantifying the Impact of the Built Environment on Neighborhood Crime Rates
  Adyasha Maharana, Quynh C. Nguyen, and Elaine O. Nsoesie
  AI for Social Good Workshop (co-located with ICML), 2019 [paper]

• A Pragmatic Approach to Information Extraction for Systematic Review
  Adyasha Maharana, Arpit Tandon, Eric Wimberley, Mihir Shah, Ruchir Shah and Brian E. Howard
  Text Analysis Conference (TAC), 2018 [paper]

• Use of deep learning to examine the association of the built environment with prevalence of neighborhood adult obesity
  Adyasha Maharana and Elaine Nsoesie
  Journal of the American Medical Association (JAMA Network Open), 2018 [paper, code]

• Clinical Event Detection with Hybrid Neural Architecture
  Adyasha Maharana, Meliha Yetisgen
  BioNLP (co-located with ACL), 2017 [paper]

• Social media as a sentinel for disease surveillance: what does sociodemographic status have to do with it?
  Elaine O. Nsoesie, Luisa Flor, Jared Hawkins, Adyasha Maharana, Tobi Skotnes, Fatima Marinho, and John S. Brownstein
  PLOS Currents Outbreaks 2016 [paper, code]

Teaching

• Digital Signal Processing Laboratory - Spring 2015
  

• Micro-controllers & Microprocessors Laboratory - Fall 2014
  

Professional Service

• Reviewer for JAMA Network Open, Frontiers in Artificial Intelligence, RobustML workshop at ICLR 2021, ACL 2020, EMNLP 2021, ACL 2021, NAACL 2021 and ACL Rolling Review
• Member of Program Committee for Causual Inference + NLP Workshop at EMNLP 2021