Apply     Visit     Give     |     Alumni     Parents     Offices     TCNJ Today     

School of Science Colloquium: Dr. Jana Gevertz and Dr. Edward Kim

School of Science Colloquium Date: Tuesday, February 5
Time: 4:00pm – 5:00pm
Location: Science Complex P-101

Dr. Jana Gevertz, Department of Mathematics and Statistics
“Mathematical Oncology: Using Mathematics to Understand Cancer”
Abstract: Mathematical oncology is a field in which tools from applied and computational mathematics are used to better understand cancer initiation, progression, and treatment. In this talk, I will provide a brief introduction to cancer, and motivate the role of mathematical techniques in the study of cancer. The basics of the mathematical model I have developed will be explained, and its properties will be studied. I will then demonstrate how computer simulations of the mathematical model can be used to explore the anti-tumor activity of several vascular (blood vessel)-targeting compounds and chemotherapeutic agents. Further, I will illustrate how optimization techniques can be applied to the mathematical model to identify a novel treatment protocol that maximizes cancer cell death in the simulated tumors. I will conclude with some current and future directions.

Dr. Edward Kim, Department of Computer Science
“Towards semantic image understanding and retrieval”
Abstract: Take a second to think about a photograph of a landscape, scene, landmark, or person. You can probably imagine the scene, colors, and layout, but if you wanted to search for the image or a similar image there is no effective way to describe the scene to a search engine. This is because effectively searching through a large collection of images is a very difficult problem. Current technology from leading image search platforms (think of google image search, Flickr, Facebook), primarily rely on text (filenames, titles, metadata, and user provided tags) to match your search queries rather than analyzing the actual image content. I would like to present my work towards building a framework for true content based image retrieval utilizing large scale Semantic Web resources available to the public.