Division of Science





Department of Mathematics
The City College of New York
160 Convent Avenue
New York, NY 10031

Phone: (212) 650-5346
Fax: (212) 650-6294

CCNY Data Science, Networks, and Biology Seminar

All talks

  • Thursday, May 18, 2017, 03:30PM, NAC 4/156

    Basilis Gidas (Division of Applied Mathematics, Brown University), Classification and Clustering of Stop Consonants via Nonlinear Transformations for Prediction in Stochastic Processes

    An effort to develop a framework in speech recognition alternative to that of HMM (Hidden Markov Models), lead us to the study of classification and clustering of the six stop consonants /p, t, b, d, k, g/ -- an outstanding problem in phonetic theories. The stop consonants differ from one another in two phonetic features: Place of articulation (closure of the vocal track) and voicing (the onset of phonation or VOT). The former divides them into labials /p, b/, alveolars /t, d/, and velars /k, g/. Voicing divides them into voiced /b, d, g/ and voiceless /p, t, k/. We developed a procedure for the classification and clustering with three powerful components: (i) a wavelet transform of the acoustic signal, (ii) a nonlinear transformation of the wavelet transform, and (iii) a nonlinear discrimination rule based on the nonlinear transformation of step (ii). Part (ii) lead to some interesting mathematical problems: (a) the existence of the nonlinear transformations is reduced to the study of the spectrum of certain singular integral operators on Hardy type spaces and certain spaces of entire functions of exponential type; (b) the estimation of the nonlinear transformations on the basis of data is an interesting nonparametric statistical learning problem; it involved some mathematical tools not very common in statistics. The main goal of the talk will be to present the overall algorithmic classification procedure as well as some the above mathematical and statistical estimation problems.

  • Thursday, May 04, 2017, 03:30PM, NAC 4/156

    Prof. Marilyn Gunner (CCNY Physics), Proton pumping and electron tunneling: physical principles to power the cell

    Cells store energy in a proton gradient. Protons are pumped through membrane embedded proteins from the N-side of the membrane, with fewer protons, to the more positive P-side. The energy to build the gradient comes from sunlight in photosynthesis or from energy liberated by redox chemistry such as in the reduction of oxygen in cytochrome c oxidase. The proton gradient fuels the transfer of ions and substrates across the membrane needed for cell signaling and metabolism and the production of ATP, the universal energy currency for biochemical reactions. I will describe the basic rules needed to pump protons, how electron tunneling can be used to carry out reactions to build the gradient and how in F1/FO ATPase the proton gradient is used to fuel mechanical work.

  • Thursday, March 30, 2017, 03:30PM, NAC 4/156

    Prof. Lucas Parra (CCNY Biomedical Engineering), On Brainwaves and Videos and Video Games

    What are the immediate neural response of the brain to natural stimuli, in particular audiovisual narratives and video games? To answer this question we record EEG while subjects are exposed to the identical audiovisual narratives and measure inter-subject correlation, which captures how similarly and reliably different people respond to the same natural stimulus. We find that inter-subject correlation of EEG is strongly modulated by attention, correlates with long term memory, and provides a quantitative estimate for "audience engagement". In children and adolescents watching videos we find changes with age and gender that are consistent with an increase in diversity of brain responses as they mature. During video game play, which are unique experiences that preclude correlation across subjects, we measure the strength of stimulus-response correlations instead. We found that correlation with both auditory and visual responses drive the correlation observed between subjects for video and that they are are modulated by attention in video game play. Importantly, the strongest response to visual and auditory features had nearly identical neural origin suggesting that the dominant response of the brain to natural stimuli is supramodal.

  • Wednesday, November 30, 2016, 03:30PM, NAC 7/219

    Jonathan Levitt (CCNY Biology), The spatial organization of interareal connections in mammalian visual cortex

    ​The mammalian cerebral cortex contains a number of distinct areas that mediate visual perception. There are several dozen distinct visual areas in primates, over half of the entire cortical mantle. Neurons in each of these regions are arranged topographically; neighboring neurons respond to visual stimuli that fall on adjacent regions of the retina (i.e. different regions of visual space). However, the precise map of visual space differs in each of these areas. These visual cortical areas in the adult mammalian brain are linked by a network of interareal feedforward and feedback circuits that are broadly topographic – source and target neurons sit in largely corresponding regions of the visual field map. A major interest of my laboratory is to characterize the organization of these anatomical circuits linking different areas. I will describe studies on the topographic precision and general organization of these circuits in the adult brain, and how they refine from an immature state postnatally.

  • Wednesday, November 09, 2016, 03:30PM, NAC 7/219

    Yingli Tuan (CCNY Electrical Engineering), Computer vision technologies to assist blind persons

    In this talk, I will introduce our research of applying computer vision technologies to assist visually impaired or blind persons. In particular, this talk will focus on scene text detection extraction and indoor navigation. Text information widely exists in natural scene and serves as a significant indicator for many vision-based applications. Automatic extracting text information from natural scene images is still a challenging task due to complex background outliers and variations of text patterns. We have developed a prototype navigation system in Android platform by combining computer vision and robotics SLAM technologies to assist blind users in navigating across multiple floors.

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