Jace
Jace Robinson
robinson.329@wright.edu
Resume: [pdf] (Last updated Feb 2017)
CV: [pdf] (Last updated Feb 2017)
Google Scholar: [Link]
Github: [Link]
Kaggle: [Link]

BIO
I am currently a graduate researcher in the Web and Complex Systems Lab and Kno.e.sis Research Center in the computer science department at Wright State University, working towards a Master's of Science in Computer Science under the advisement of Dr. Derek Doran. My current research interests are in using probabilistic techniques to develop new dynamic network models. Specifically, I really like the idea of directed graphical models to define generative models for a wide range of applied problems. I intend to pursue a Ph.D following the completion of my M.S.

In the past summer of 2017, I worked as an intern at the National Aeronautics and Space Administration (NASA) Glenn Research Center with Debra Goodenow and Jerry Myers. I worked in the human research program to develop a dynamic probabilistic risk assessment tool to quantify the level of risk astronauts face from medical conditions in various mission scenarios.

Previously, I was a federal contractor at the Air Force Institute of Technology at Wright Patterson Air Force Base for a year under the supervision of Dr. Andrew Terzuoli working on a wide range of topics such as parallel programming using CUDA for accelerated algorithms, nonlinear optimization for passive tracking with visualization of confidence bounds, and modeling digital traffic behavior for improved product delivery.

During my undergraduate I was a research assistant for two years with Dr. K.T. Arasu studying in the field of algebraic combinatorics, specifically discovering and identifying properties of Difference Sets. I was also a teaching assistant for a few undergraduate mathematics and computer science courses of Calculus I-II, Discrete Mathematics, and College Algebra.

RESEARCH PROJECTS
Dynamic Network Modeling
Dynamic Network Modeling *current project
For this project we are developing a novel random network model which combines the tools of Stochastic Block Models with State Space Models in order to capture the Seasonal Dynamics of a large networks. An applied example is in the context of a geospatial network. Daily foot and vehicle traffic densities in a city fluctuate in predictable ways throughout the day. We can create a model of these predictable seasonal patterns and use them to define typical behavior for a geospace. Once a model for typical is created, it allows us to automatically detect when something atypical occurs within the geospace, which is often a more valuable question.

So far we have one workshop publication [1] with more to come!

Parallel Iterative Closest Point
Iterative Closest Point for Automated Aerial Refueling
The Iterative Closest Point algorithm is a widely used approach to aligning the geometry between two 3 dimensional objects. The capability of aligning two geometries in real time on low-cost hardware will enable the creation of new applications in Computer Vision and Graphics such as automated aerial refueling between a tanker and jet. This work presents an accelerated alignment variant which utilizes parallelization on a Graphics Processing Unit (GPU) of multiple kNN approaches augmented with a novel Delaunay Traversal to achieve real time estimates.

This work resulted in two conference publications [2] [3].

Nonlinear Optimization
Nonlinear Optimization with Confidence Visualization for Tracking Passive Objects
Angle of Arrival (AOA) measurements can be created from any sensor platform with any sort of optical sensor, location and attitude knowledge to track passive objects. Previous work has created a non-linear optimization (NLO) method for calculating the most likely estimate from AOA measurements. Two new modifications to the NLO algorithm are created and shown to correct AOA measurement errors by estimating the inherent bias and time-drift in the Inertial Measurement Unit (IMU) of the AOA sensing platform.

This work resulted in a conference publication [4].

PUBLICATIONS
[1] Robinson J., Doran D., “Seasonality in Dynamic Stochastic Block Models", Proceedings of the International Conference on Web Intelligence, ACM, 2017. [Link] [arXiv] [slides]

[2] Robinson J., Piekenbrock M., Burchett L., Nykl S., Woolley B., Terzuoli A., “Parallelized Iterative Closest Point for Autonomous Aerial Refueling”, Proceedings of Advances in Visual Computing (Lecture Notes in Computer Science 10072), 2016. [Link]

[3] Burchett L., Robinson J., Piekenbrock M., Nykl S., Woolley B., and Terzuoli T., “Automated aerial refueling: Parallelized 3d iterative closest point”, Proceedings in IEEE (International). Conference in Aerospace & Electronics, 2016. [Link]

[4] Levy D., Roos J., Robinson J., Carpenter W., Martin R., Taylor, C., Sugrue J., Terzuoli A., “Non Linear Optimization Applied to Angle-Of-Arrival Satellite Based Geo-Localization for Biased and Time-Drifting Sensors”, In International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences 41, 2016. [Link]

[5] Robinson J., “Investigation of Algebraic Combinatorics through Difference Sets”, Undergraduate Thesis, Wright State University, 2016.

[6] Phillips B., Robinson J., “Some New Almost Difference Sets Via Finite Fields”, ACM Communications in Computer Algebra 49, 2015. [Link]


© Jace Robinson