Ennio Mingolla
Prof. Mingolla works on development and empirical testing of neural network models of visual perception, notably the segmentation, grouping, and contour formation processes of early and middle vision in primates, and on the transition of these models to technological applications. Please see his personal page and his Google Scholar account for more about his research and publications.
Alumni
Girik Malik
Girik graduated with a PhD in Computer Science from Northeastern’s Khoury College of Computer Sciences, focusing on artificial intelligence, neuroscience, psychology and cognitive science. He is interested in computer vision problems, and solving them with deep learning and neuroscience. Please see his personal page and Google Scholar for more about his research and publications.
Harald Ruda
Harald is interested many aspects of vision and decision making processes. He is currently working on understanding the connections between eye-movements, cortical magnification, and how motion is processed in the brain, and also how this understanding can be applied to robots. For his dissertation he focused on modeling the perception of hyperacuity. Please see Google Scholar and Research Gate for more about his past research and publications.
Gennady Livitz
Gennady earned his PhD in Cognitive and Neural Systems in 2010 from Boston University. His main research interest is in understanding the mechanisms of color perception, particularly how the encoding of unique hues emerges from cone receptor signals as well as the nature of color opponency. He is also interested in computational vision algorithms that could account for visual scene segmentation and interpretation. Due to his software engineering background his approach to these problems lays at the intersection of research and engineering. Apart from his research interests, he enjoys art and likes to travel.
Matthew Mage
Matthew is an undergraduate Mechanical Engineering/Computer Science major. Outside of his research he enjoys photography and music.
William Kalfus
William is an undergraduate Computer Engineering/Physics major. In his free time, he enjoys working on various robotics and programming projects, reading, and listening to music.
Lena Sherbakov
Lena Sherbakov received her PhD in Computational Neuroscience from Boston University in 2014, where she studied biologically-inspired computer vision. Her primary research interest is in modeling the role of eye movements in artificial vision systems that integrate recognition, fixation selection, memory and learning, and attention processes into one comprehensive model running in real-time. A corollary interest to achieve the construction of such a visual system is high-performance computing, specifically neural-like computational platforms that leverage the parallelism of graphic processing units (GPUs). Lena received her M.S in Applied Mathematics from the University of Washington and her B.S. degrees at the College of William and Mary in Mathematics and Physics. She has previously worked for a biotech start-up and a research laboratory developing predictive mathematical models of human physiology and analyzing MRI scans, respectively. Lena’s broad scientific interest is in unifying theories of higher cognitive processes.
Guillaume Riesen
Guillaume completed his BS in Cognitive Neuroscience at Brown University in 2012, where his undergraduate thesis involved implementing binocularity in a model of early visual processing. He then spent a year working in Professor Wulfram Gerstner’s Laboratory of Computational Neuroscience at EPFL in Switzerland as a Fulbright Scholar. There he produced a model of pinwheel development in orientation maps of the primary visual cortex. He is currently exploring the impact of occlusion on the human ability to subitize (count objects rapidly and accurately), and the relationship between afterimages and spatial induction in color vision. His research interests include improving the biological plausibility of models of visual processing and implementing such models in real or virtual robotic environments.