Graduate Research Assistant @ Northeastern University

Sep 2016 - Current

CerebroVis

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.

MTS Data Visualization Intern @ Illumio

May 2019 - Aug 2019

Segmentrix

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.

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

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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

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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

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Interactively visualizing summaries of rules and exceptions (W)

Geetika Sharma, Gautam Shroff, Aditeya Pandey*, Puneet Agarwal, Ashwin Srinivasan EuroVA, 2014

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CerebroVis: Topology and Constraint-based Network Layout for the Visualization of Cerebrovascular Arteries

Best Poster at IEEE Vis 2018

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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

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VISTA: Visual Interactive Spatio-Temporal Data Analysis

Honorable Mention for User-Friendly Anomaly Detection VAST 2016

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