Aditi Mishra

Aditi Mishra

I am a Computer Science PhD student at School of Computing and Augmented Intelligence, Arizona State University, where I work with Dr. Chris Bryan on data visualization.

My interests particularly lie in designing and developing interactive interfaces to enable autonomous agent interpretability and explainability for novice end users. I am also interested in applying machine learning to reconstruct large unstructured scientific datasets.

Email / CV / Research Statement / Google Scholar / Linkedin /

Recent News

[May 2024] My internship work done at Megagon Labs under Dr Sajjadur Rahman Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks has been accepted to this year's ACL Findings.

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[April 2024] On CLIP's ability to identify fake images at large scale: Why are they fake? has been accepted to this year's GenAICHI workshop held in Honolulu, Hawaii.

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[Jan 2024] I have started as a Data Science Intern at Stanford Healthcare, Palo Alto. I am working on leveraging LLMs to summarize patient health records and ways to evaluate generated summaries.

[May 2023] I have started as a Summer Research Intern at Megagon Labs, Mountain View. I am working on leveraging LLMs to rationalize knowledge augmented model's decisions.

[Sept 2022] I have been awarded the Graduate Travel Fellowship Award by ASU.

[March 2022] I have been awarded the SCAI Doctoral Fellowship by ASU.

[Feb 2022] Two of my works - Why? Why not? When? Visual Explanations of Agent Behavior in Reinforcement Learning and News Kaleidoscope: Visual Investigation of Coverage Diversity in News Event Reporting has been accepted in this year's PacificVis held in Tsukuba, Japan.

[May 2020] I started my summer internship at Los Alamos National Lab as a research intern.

Publications

	Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks Aditi Mishra, Sajjadur Rahman, Hannah Kim, Kushan Mitra, Estevam Hruschka, ACL, 2024 Generating and evaluating the proficiency of LLMs in generating rationales grounded on external knowledge for knowledge intensive tasks.
	On CILP’s Ability of Analyzing Fake Images at Large Scale: Why are they fake? Jinbin Huang, Chen Chen Aditi Mishra, Bum-Chul Kwon, Leo Zhicheng Liu, Chris Bryan GenAICHI , 2024 Visual analytic system to interactively explore, understand and summarize the difference in Vision Language Model patterns for real and fake images.
	PromptAid: Prompt Exploration, Perturbation, Testing and Iteration using Visual Analytics for Large Language Models Aditi Mishra, Utkarsh Soni, Anjana Arunkumar, Jinbin Huang, Bum-Chul Kwon, Chris Bryan In Submission, TVCG Providing a visual analytics interface to aid easier prompting alterations for LMs based on linguistic and contextual recommendations.
	ConceptExplainer: Interactive Explanation for Deep Neural Networks from a Concept Perspective Jinbin Huang Aditi Mishra, Bum-Chul Kwon, Chris Bryan IEEE Transactions on Visualization and Computer Graphics, 2022 Explaining deep neural networks using image based concepts extracted from ACE+TCAV.
	Why? Why not? When? Visual Explanations of Agent Behavior in Reinforcement Learning Aditi Mishra, Utkarsh Soni, Jinbin Huang, Chris Bryan In Proceedings of Pacific Visualization Symposium (PacificVis), 2022 [video] Providing a visual analytics interface to question and thus gain trust in an autonomous agent's decision.
	News Kaleidoscope: Visual Investigation of Coverage Diversity in News Event Reporting Aditi Mishra, Shashank Ginjpalli, Chris Bryan In Proceedings of Pacific Visualization Symposium (PacificVis), 2022 [video] A visual analytic system for journalism expert users to be able to identify underlying polarities in different news organizations.
	ChartStory: Automated Partitioning, Layout, and Captioning of Charts into Comic-Style Narratives Jian Zhao, Shenyu Xu, Senthil Chandrasegaran, Chris Bryan, Fan Du, Aditi Mishra, Xin Qian, Yiran Li, Kwan Liu Ma IEEE Transactions on Visualization and Computer Graphics, 2021 ChartStory is meant for crafting data stories from a collection of user-created charts.
	Analyzing gaze behavior for text-embellished narrative visualizations under different task scenarios Chris Bryan, Aditi Mishra, Hidekazu Shidara, Kwan Liu Ma Visual Informatics, 4.3, pp. 41–50, 2020 A study to investigate perception in text-embellished narrative visualizations under Observation, Search and Recall tasks.
	TotemFinder: A Visual Analytics Approach for Image-based Key Players Identification Jinbin Huang, Aditi Mishra, Anjana Arunkumar, Chris Bryan VAST Challenge Workshop in IEEE Visualization Conference (VIS), 2020 (Honorable Mention) [video] An interactive visualization system for the analysis of the VAST 2020 Mini-Challenge 2 (MC2) dataset.
	Filling the Void: Deep Learning-based Reconstruction of Sampled Spatiotemporal Scientific Simulation Data Aditi Mishra, Subhashis Hazarika, Ayan Biswas, Chris Bryan Arxiv, 2021 Deep Learning method to reconstruct a large unstructured scientific dataset.

Website code from Jon Barron