Aditeya Pandey

PhD Student @ Northeastern University

Boston, MA, US


(857) 930--0481

Aditeya Pandey - Resume

Research Experience

Graduate Research Assistant @ Northeastern University
Sep 2016 - Current
Towards Identification and Mitigation of Task-Based Challenges

BELIV 2020

In this work, we systematically identify and curate the task-based challenges of comparative studies by reviewing existing visualization literature on the topic. Furthermore, for each of the presented challenges we discuss the potential threats to validity for a comparative study. The challenges discussed in this paper are further backed by evidence identified in a detailed survey of comparative tree visualization studies.

Pre-print | Talk Slides | Supplementary Material

CerebroVis is a novel network visualization tool which assists in diagnosis cerebrovascular abnormalities like stenosis and aneurysms. We found that CerebroVis improves the identification of cerebrovascular abnormalities in the brain over existing 3D MRA visualization.

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Evaluationg Glyph Design for Increased Probablistic Categorization Accuracy

In a crowdsourced experiment, we measured the effect of glyph design on an everyday task of categorization. We found that abstract glyphs are more accurate compared to anthropomorphic glyphs in a categorization experiment.

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Picture Penguin: A Multi-Faceted Mobile Photo Navigation System

Multi-faceted data, such as a photo’s location, timestamp, and content, are difficult to navigate, particularly when a user has incomplete knowledge of the data, such as when the date of a photo is unknown. We present Picture Penguin, a novel personal photo navigation system that enables search and filtering through linked and combined views of temporal, geospatial, and photo content information. Picture Penguin scales to large photo collections andreduces complexity through clustering and data summarization techniques, and runs as both a mobile and a desktop application.


MTS Data Visualization Intern @ Illumio
May 2019 - Aug 2019

The Network Infrastructure of computer-based business is expanding every day. Consequently, monitoring and cyber-fencing of these massive networks is a growing concern within organizations. We developed a visualization tool which assists organizations to segment their network, write security policies and monitor network.

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R&D Engineer @ Tata Consultancy Services
Aug 2013 - July 2016
Visual Bayesian Fusion to Navigate a Data Lake

A data-fusion based visual analytics platform for navigating a data lake to derive insights. Our platform allows for rich interactive visualizations, querying and keyword-based search within and across datasets or models, as well as intuitive visual interfaces for value-imputation or model-based predictions.

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Multi-sensor Visual Analytics Supported by Machine-Learning Models

A platform designed to explore multi-dimensional sensor data. Special focus on visualization of temporal sensor data using time-series visualization. Real-time time-series query visualization support, where the similar and frequent patterns can be queried using suitable machine learning algorithms.

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Interactively Visualizing Summaries of Rules and Exceptions

Rules along with their exceptions have been used to explain large data sets in a comprehensible manner. In this work we present a novel hierarchical view of the rules and exceptions in a bubble layout.


Journal Article (J), Conference Paper (C), Workshop Paper (W)
CerebroVis: Designing an Abstract yet Spatially Contextualized Cerebral Arteries Network Visualization (J)
Aditeya Pandey*, Harsh Shukla, Geoffrey S Young, Lei Qin, Amir A Zamani, Liangge Hsu, Raymond Huang, Cody Dunne, Michelle A Borkin To appear in IEEE Transactions on Visualization and Computer Graphics (TVCG)
Paper | Video | Supplemental Material

Visual bayesian fusion to navigate a data lake (C)
Karamjit Singh, Kaushal Paneri, Aditeya Pandey*, Garima Gupta, Geetika Sharma, Puneet Agarwal, and Gautam Shroff 19th International Conference on Information Fusion (FUSION), pp. 987-994. IEEE, 2016
Paper | Video
Multi-sensor visual analytics supported by machine-learning models (W)
Geetika Sharma, Gautam Shroff, Aditeya Pandey*, Brijendra Singh, Gunjan Sehgal, Kaushal Paneri, Puneet Agarwal 2015 IEEE International Conference on Data Mining Workshop (ICDMW), 668-674
Paper | Video
Interactive Visual Analysis of Temporal Text Data (C)
Aditeya Pandey*, Kunal Ranjan, Geetika Sharma, Lipika Dey Proceedings of the 8th International Symposium on Visual Information Communication and Interaction, 2015
Interactively visualizing summaries of rules and exceptions (W)
Geetika Sharma, Gautam Shroff, Aditeya Pandey*, Puneet Agarwal, Ashwin Srinivasan EuroVA, 2014

Awards and Honors

CerebroVis: Topology and Constraint-based Network Layout for the Visualization of Cerebrovascular Arteries
Best Poster at IEEE Vis 2018
Link | News
iFuse: A Visual Data Fusion Approach, by Gunjan Sehgal, Kaushal Paneri, Aditeya Pandey and Garima Gupta, TCS Research
First Prize at Dataview 2016 – comad 2016 machine learning competition
VISTA: Visual Interactive Spatio-Temporal Data Analysis
Honorable Mention for User-Friendly Anomaly Detection VAST 2016