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 Mubbasir Kapadia



 Assistant Professor


 Computer Science Department


 Rutgers University



 PhD, Computer Science


 University of California, Los Angeles



 Email:


Open Positions
  • Postdoc and PhD opportunities in the areas of crowd simulation, character animation, and/or digital storytelling.
  • Project opportunities for graduate and undegraduate students in computer animation and games.

Teaching

Spring 2016, CIS 442/675: Game Science
Spring 2016, CIS 195: Computational Narrative
Fall 2015, CIS 428/523: Computer Graphics
Spring 2015, CIS 673: Simulating and Animating Autonomous Virtual Humans


News

2/28/16: Our paper PRECISION: Precomputing Environment Semantics for Contact-Rich Character Animation has been accepted at ACM SIGGRAPH I3D 2016. This work has received press coverage including Phys.org and EurekaAlert.
2/1/16: Our book Geometric and Discrete Path Planning for Interactive Virtual Worlds has been published!.
1/15/16: Our book Virtual Crowds: Steps Toward Behavioral Realism has been published!.
1/1/16: Our paper Towards an Accessible Interface for Story World Building is published at 8th Workshop on Intelligent Narrative Technologies (INT), 2015.
1/1/16: Our paper Augmented Creativity- Bridging the Real and Virtual Worlds to Enhance Creative Play is published at ACM SIGGRAPH Asia 2015 Symposium on Mobile Graphics and Interactive Applications, 2015.
1/1/16: Our paper Automated interactive narrative synthesis using dramatic theory is published at ACM SIGGRAPH Motion in Games (MIG), 2015.
1/1/16: Our short paper Evaluating and Optimizing Level of Service for Crowd Evacuations is published at ACM SIGGRAPH Motion in Games (MIG), 2015.
1/1/16: Our short paper ACCLMesh: Curvature-Based Navigation Mesh Generation is published at ACM SIGGRAPH Motion in Games (MIG), 2015.
1/1/16: Our paper Authoring Background Character Responses to Foreground Characters is published at the International Conference on Interactive Digital Storytelling (ICIDS), 2015.


Research

Crowd Simulation. We develop models for simulating realistic, believable crowds. To this end, we identify and address fundamental limitations in how individuals in a crowd are represented and controlled. Our research results have widespread application in visual effects, games, urban planning, architecture design, as well as disaster and security simulation.




Crowd Analysis and Optimization. In order to rigorously evaluate and compare crowd models, we have developed tools for quantifying the coverage, quality, and failure of crowd simulators, and its ability to emulate real crowd data. Furthermore, we have developed a framework for automatically optimizing the parameters of a crowd simulation algorithm to meet any user-defined criteria. Our tools can be used to predictively evaluate the optimal crowd behavior in evacuations, and other stressful situations.


Real-Time Multi-Agent Planning. : We develop algorithms for multi-agent motion planning in real-time dynamic environments. Our research investigates the use of novel discrete representations of the environment, and the use of anytime dynamic planners that harness multiple domains of representation. We port these algorithms on the GPU to exploit the benefits of massive parallelization, while preserving the original properties of the approach.


Autonomous Virtual Humans. Our research aims to develop integrated solutions for full-body character animation, planning based control, behavior authoring, and statistical analysis of autonomous virtual human simulations. The far-reaching goal is to provide functional, purposeful embodied virtual humans, that act and interact in meaningful ways to simulate complex, dynamic, narrative-driven, interactive virtual worlds.



Digital Storytelling. : We develop computational tools to assist end users to create and experience compelling, interactive, digital stories. To this end, we have revisited standard representations of interactive narratives and proposed new formalisms that scale independent of story complexity and user interaction. Our computational tools help mitigate the complexity of creating digital stories without sacrificing any authorial precision.




Brief Bio. Mubbasir Kapadia is an Assistant Professor in the Computer Science Department at Rutgers University. Previously, he was an Associate Research Scientist at Disney Research Zurich. He was a postdoctoral researcher and Assistant Director at the Center for Human Modeling and Simulation at University of Pennsylvania, under the directorship of Prof. Norman I. Badler. He was the project lead on the United States Army Research Laboratory (ARL) funded project Robotics Collaborative Technology Alliance (RCTA). He received his PhD in Computer Science at University of California, Los Angeles under the advisement of Professor Petros Faloutsos.

A full curriculum vitae is available here.

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