Laboratory for Imaging, Networks, and Control (LINC)

Welcome to the LINC Lab!  This site hopefully details research on-going in our group as well as adventures outside of work.  In particular, we are focused on a variety of projects with a common underlying theme that focuses on the intersection of geometry, statistics, and control. As such, we are interested in applying generalized mathematical techniques to a myriad of problems in complex networks, risk analysis, computer vision, mathematical oncology, shape analysis, systems biology, and machine learning.  While such areas are seemingly far apart, the LINC group leverages such interdisciplinary knowledge to attack old problems in a new light (i.e., geometry of cancer).  Note:  We are recruiting! If you are an interested PhD student starting (or plan) to attend Stony Brook University and possess a strong mathematical and computational background, feel free to email about potential opportunities within our group.  Please see the positions and projects page for further information

Lab Director

Dr. Romeil Sandhu is the director of the LINC lab.  He is currently an Assistant Professor at Stony Brook with appointments in Biomedical Informatics, Computer Science, and Applied Mathematics & Statistics Departments.  He received his Ph.D., M.S., and B.S. all from Georgia Tech.

Lab Focus

We are focused on three major areas.  While the range of applications encompasses a broad spectrum, the underlying emphasis of our works is pinned in areas of discrete geometry, statistics, and control.  This allows us to take an “outside” view while still adhering to the underlying issues of the application at hand. These areas are highlighted below.

Network Geometry

We are currently interested in studying how we can exploit the underlying geometric properties of dynamical complex systems in order to alter their collective behavior.  We utilize a variety of applications to illustrate generality.

Systems (Cancer) Biology

Combating biological complexity is at the heart of many questions in systems biology.  The LINC group is focused on unraveling such complexity in order to design effective targeted therapy strategies for next-gen cancer treatment.

Control-Based Computational Imaging

The LINC group is also dually focused on computational computer vision, interactive control-based imaging, and machine learning.  Applications range from tracking, shape reconstruction, to discrimination methods required for medical imaging.