Shreeraj Jadhav

PhD Candidate

Department of Computer Science

Stony Brook University

Email: sdjadhav  [at]  cs [dot]  stonybrook [dot] edu

 

Education

MS in Computing, University of Utah

BE in Mechanical Engineering, University of Pune

Publications

3D Virtual Pancreatography

Shreeraj Jadhav, Dmitriev Konstantin, Joseph Marino, Arie Kaufman

IEEE Transactions on Visualization and Computer Graphics, 2020

 

FeatureLego: Volume Exploration Using Exhaustive Clustering of Super-Voxels

Shreeraj Jadhav, Saad Nadeem, Arie Kaufman

IEEE Transactions on Visualization and Computer Graphics, 2019

 

Visualization of Neuronal Structures in Wide-Field Microscopy Brain Images

Saeed Boorboor, Shreeraj Jadhav, Mala Ananth, David Talmage, Lorna Role,

Arie Kaufman

IEEE Transactions on Visualization and Computer Graphics, 2018

 

A Quantized Boundary Representation of 2D Flows

Joshua Levine, Shreeraj Jadhav, Harsh Bhatia, Valerio Pascucci, Peer‐Timo Bremer

Computer Graphics Forum, 2012

 

Consistent Approximation of Local Flow Behavior for 2D Vector Fields using Edge Maps

Shreeraj Jadhav, Harsh Bhatia, Peer-Timo Bremer, Luis Gustavo Nonato,

Valerio Pascucci

Topological Methods in Data Analysis and Visualization II, 2012

*Best Paper Nomination*

 

Flow Visualization with quantified Spatial and Temporal Errors using Edge Maps

Shreeraj Jadhav, Harsh Bhatia, Peer-Timo Bremer, Guoning Chen, Joshua Levine,

Luis Gustavo Nonato, Valerio Pascucci

IEEE Transactions on Visualization and Computer Graphics, 2011

 

Edge Maps: Representing Flow with Bounded Error

Harsh Bhatia, Shreeraj Jadhav, Peer-Timo Bremer, Guoning Chen, Joshua Levine,

Luis Gustavo Nonato, Valerio Pascucci

IEEE Pacific Visualization Symposium, 2011

*Best Paper Award*

 

Research Statement

I apply the tools of computer graphics, virtual reality, geometric and image analysis to solve problems in scientific and medical visualization. My interests are in research and development of software systems and prototypes for automatic and visual analysis of spatial data that lead to higher impact on the scientific and medical workflow.