Like many engineers Christine grew up breaking, and on rare occasions fixing, her toys. While she decided on engineering early, it was only in her junior year of college that she was inspired to be a roboticist. The inspiration was sparked by the DARPA Grand Challenge and nurtured by her mentors. Christine graduated from San Jose State University with a dual engineering degree and a passion for computer vision. She is currently pursuing this passion under the advisement of Dr. Kostas Daniilidis at the University of Pennsylvania.
Chris did his undergraduate work at Lafayette College, where he did research on attention and its impact on performance using a brain-computer interface. After graduating with a B.S. in Neuroscience and a B.A. in Art, he went on to work as a research assistant in Frank Tong's lab at Vanderbilt, where he was involved in projects examining visual attention and fMRI imaging of hippocampal activity. As a PhD student in the Department of Psychology, Chris is interested in how spatial representations are constructed in the brain, how those spatial representations are used in other cognitive domains and how the mechanics of this spatial system can be applied in machine navigation.
Gedas got his bachelor's degree in Computer Science and Mathematical Finance at Dartmouth College. During his junior year at Dartmouth, Gedas started doing computer vision and machine learning-related research in the Visual Learning Group under Lorenzo Torresani's supervision. At Penn, Gedas is currently working on shape recognition projects with Jianbo Shi. Gedas' research involves applying machine learning techniques such as deep learning and spectral graph theory to solve complex computer vision problems. Additionally, Gedas is interested in broader ideas behind human vision and various ways to use them to enhance pattern recognition in the machines. His website can be found at: http://www.seas.upenn.edu/~gberta/.
Jennifer got her bachelor's degree in Mathematics at the University of Pennsylvania. During her sophomore year she started doing research in the lab of Dr. Ted Abel studying how aging affects short- and long-term memory. As a Neuroscience PhD student Jennifer is studying auditory perception with Dr. Maria Geffen, specifically focusing on identifying neural circuits that underlie changes in perception after aversive learning.
Alex got his introduction to robotics through a high school Battlebots team. His interests range from high-level robot control to sensors and electrical circuit design. In his undergraduate studies at Swarthmore College, he majored in engineering and minored in cognitive science. He worked there on several robotics and electrical engineering projects. His current research in the Haptics lab with Katherine Kuchenbecker is related to robotic understanding of surface textures using both visual and tactile sensors. Outside the lab, Alex can be found dancing and reading science fiction. His website is here.
Ben received an A.B. in cognitive science from Vassar College, where he worked with Jan Andrews and Ken Livingston on research investigating categorical perception effects in people. He is now a psychology PhD student in the lab of Johannes Burge, where he studies motion perception in humans. In particular, he is interested in how natural variation (noise) in light signals from moving stimuli interacts with noise internal to people (such as variations in neuron firing patterns, or decisional processes) to affect how speed is perceived. He primarily uses psychophysical and computational methods.
Ariana earned a BA in Psychology and Philosophy from New York University where she used psychophysics to examine visual attention mechanisms in the Carrasco lab. After graduating, she worked as an RA in the Shim Lab at Dartmouth College where she conducted psychophysical and neuroimaging projects on top-down/feedback processing in human vision. Now as a Psychology PhD student, Ariana uses neuroimaging with machine learning methods to elucidate how and by what properties visual information is stored in specialized areas of the brain and leveraged in object recognition and categorization. Some research-oriented questions that entice her are: How are visual features integrated and represented in the brain? How can behavioral demands influence the encoding of visual information? How do perceptual and conceptual neural networks interact during object and scene perception? Here is her site.
As a part-time learner, part-time teacher, and part-time world traveler, Naomi completed her undergraduate degrees in mechanical engineering in Spanish at the University of Cincinnati (UC) in Cincinnati, Ohio. After revamping the UC Robotics Team as team president during her senior year, Naomi realized how much potential robots have as teaching and motivational tools. Her senior project was a musical robot that brought together minds and talents from all over the university, and she hopes to continue working on robotic performers and robotic teaching tools as a IGERT fellow and graduate student in the Mechanical Engineering and Applied Mechanics PhD program at the University of Pennsylvania. Besides researching robotics, Naomi is a member of the Penn Band and a Graduate Associate in the Stouffer College House.
Adam is interested broadly in how the brain processes sensory information. His research focuses on the auditory system, and he is particularly interested in the relations between acoustic-stimulus regularities and population-level neural activity, and how neural activity at the population level relates to changes in auditory perception. Additionally, he is interested in how the study of auditory perception can be used to improve speech/sound recognition/segregation systems.
As a doctoral student in Psychology at Penn, Alon is investigating cognitive and neural representations of actions and events, examining representations of events in language as a window into the kinds of information about events that are encoded in perception and memory. He uses behavioral and neuroimaging methods, including eyetracking and fMRI, to study these issues. He received his BA in music from Wesleyan University, and subsequently worked for several years as a research assistant in the departments of psychology at Temple University and at Penn, focusing on the acquisition of language by infants and toddlers, and on scene perception. He is also an avid soup-maker (just ask him about French Onion).
Jessica graduated from the University of Illinois at Urbana-Champaign with a Bachelorís degree in Nuclear Engineering and a focus in Bioengineering. She was involved in various research projects related to biomedical applications including OCT and biomechanics. She is mainly interested in the field of Bioimaging. In 2015, she joined Pennís Bioengineering PhD program. She is currently working on retinal imaging with adaptive optics and molecular imaging with contrast agents.
Jennifer earned her Bachelor's and Master's degree in Biomedical Engineering at Columbia University. She came to the University of Pennsylvania to pursue a Master's degree in Robotics and a PhD in Computer and Information Science. Jennifer is advised by Dr. Katherine Kuchenbecker and is working to understand robotic touch perception for the development an automatic palpation system for use in minimally invasive surgery. In her free time, Jennifer enjoys dancing and blowing absurdly large bubbles with her hands.
As an undergraduate, Daphne studied computer science and geographic information systems at the University of Toronto. She became interested in computer vision after seeing how research across the university, from the mapping of rainforests to the documentation of archaeological excavations, was being revolutionized by the introduction of computer vision techniques. She is currently being advised by Dr. Kostas Daniilidis and is working on improved multi-view stereo reconstruction algorithms for cultural heritage preservation.
As an undergrad, David studied painting at the University of the Arts in Philadelphia and electrical engineering at The Cooper Union in New York City. David has done research in computer graphics at NCSU: developing an interactive mapping system. At Utah State University he participated in research in computer vision involving the use of light source detection for the purpose of image forensics. He's excited to now be working in perception at the University of Pennsylvania, and looks forward to implementing cognitive theory into the next generation of robots.
Drew is interested in understanding how neural networks represent information efficiently and how this information is transformed in biological perceptual systems. As a doctoral student in the Department of Neuroscience, Drew is working on combined computational and neurophysiological approaches to the study of mammalian auditory and visual neural populations. Before coming to Penn, Drew studied Philosophy, Music Composition, and Mathematics at Texas A&M University and Cognitive Neuroscience at the City University of New York Grad Center. In the long term, he is interested in adapting principles governing biological neural populations to the design and enhancement of intelligent systems.
As a doctoral student in the Department of Psychology, Josh is interested in tackling questions of scene perception, navigation, and spatial cognition in humans: what cognitive and neural systems support our ability to perceive the large-scale environment, and use that information to navigate? What representations and computations are involved? How do such systems develop, and change as a result of abnormal development? To investigate such questions, he draws on theoretical perspectives from multiple fields, including psychology, neuroscience, neuropsychology, cognitive science, and computer vision, and uses a variety of experimental techniques, including psychophysics, neuroimaging, and transcranial magnetic stimulation. Prior to coming to Penn, Josh graduated from Binghamton University (SUNY) with bachelorís degrees in physics, philosophy, and mathematics, pursued graduate work in philosophy at Tufts University, and worked as a research assistant in a cognitive neuroscience lab at MIT.
Having come to psychology from a background in philosophy and engineering, Alexander is interested in both the bigger questions and the implementational details of cognitive science. In particular, he is interested in how memory works, spatial and otherwise. As an undergraduate at Carnegie Mellon University, Alexander studied human memory, with an emphasis on the use of cognitive models. As a graduate student at the University of Pennsylvania, he studies (primarily spatial) memory in mice, also focusing on computational methods. Alexander's long term interests involve building functional computational models of memory and other aspects of cognition that can be implemented in machines, as he believes that building it is the only way to know that you understand it. On the rare occasion he is not working, Alexander can be found being awesome around Philadelphia.
Long Luu took his Bachelor's degree in electrical engineering at The Catholic University of America, where he was involved in some research projects on image and signal processing as an undergraduate and postgraduate research assistant. After that, he was with the Lab for Computational Cognitive Neuroscience at Georgetown University to work on computational models of attentional blink and binocular perception. In 2013, he joined the Department of Psychology at the University of Pennsylvania as a PhD student with interest in the computational models and quantitative methods to study the human brain.
Ammon went to college expecting to be a math teacher, so he is pleasantly surprised to be studying neural circuity in songbirds. He is broadly interested in the underlying mechanisms that drive behavior. He joined Marc Schmidtís lab in 2015 where he is investigating the role of the song circuit in female mating behavior. He intends to develop computer-vision-based behavioral tracking in order to analyze social interactions and accompanying neural activity. He received his B.S. in Biology at Brigham Young University where he focused on evolution, which still fascinates him. When heís not working in the lab, Ammon is likely to be found rock climbing, watching Doctor Who, or pointing out that his name actually rhymes with ďbackgammon.Ē
Stephen Phillips got his Bachelor's of Science at UCLA. His interest in robotics and computer vision started when he did research in the vision lab at UCLA toward the end of his junior year, doing research in visual tracking. Now he is studying under Professor Kostas Daniilidis, doing work on reconstruction and tracking.
Sonia studied cognitive science at Vassar College, where she worked with John Long using biorobotic and biomechanical approaches to study how behavioral selection may have affected the evolution of vertebrae in early fishes. After graduation, she worked for two years at the Howard Hughes Medical Institute's Janelia Farm Research campus on a large group project attempting to create a functional, circuit-level map of the fruit fly brain by running thousands of genetic lines with different lineages of neurons activated or inhibited through assays for basic behaviors. She is excited now to be working with legged robots as a member of Kod*lab at the University of Pennsylvania. Sonia is interested in both high- and low-level perception problems: She is currently working on problems related to high-level mapping and navigation of unknown environments but would also like to explore applications of mechanosensory perception to problems inherent to legged locomotion, such as balance and gait selection.
Mohammad completed his undergraduate studies at Sharif University of Technology, where he obtained a B.S. in Electrical Engineering and a B.S. in Pure Mathematics. He got his Master's degree in Electrical and Computer Engineering from the University of Waterloo, working on perceptual image processing and machine learning. Prior to coming to Penn, he spent a year as a research associate in the Duke-NUS graduate medical school and the Singapore University of Technology and Design, where he was involved in projects about color vision and sensor networks. Currently, as a PhD student in Electrical and Systems Engineering, Mohammad is interested in using techniques from machine learning and sparse representation to study vision.
Noam is interested in how the brain processes sensory information, and how visual representations are combined with cognition to allow us to make perceptual decisions. She is a doctoral student in the Neuroscience Graduate Group, and her research in Nicole Rustís lab is focused on how the brain combines visual and working memory information to solve object search. To do this, she combines neurophysiological approaches (recording from populations of neurons in visual brain areas) with computational analyses. Before coming to Penn, Noam studied Mathematics and Cognitive Science at Washington University in St. Louis.
Sarah is a doctoral student in psychology, and is interested in the relationships between perception, concepts, and language. Some of her big questions are: To what extent is perceptual information necessary in the activation of a concept? How do neural representations of perceptual properties interact with other processes to enable flexible concepts and generative language? She will attempt to answer these questions using neuroimaging (fMRI) and transcranial direct current stimulation (tDCS) methods. Sarah studied psychology, cognitive science, and philosophy at University of Delaware. She has previously examined the relationship of language to color perception, how the brain represents objects as they change during an event, and how figurative language involves the mapping of perceptual properties from one concept to another.
Manuel Spitschan graduated with a first class honours degree (M.A.) in psychology from the University of St. Andrews in Scotland. As a research assistant in the Vision Lab at the School of Psychology, he worked on the representaton of monocular regions in binocular scenes, as well as eye movement control in manual tasks. In 2011, Manuel took part in the UPenn Summer Program in Computational Neuroscience, where he investigated the interaction of texture and luminance variation on surface shape. Manuel is a Psychology graduate student whose research interests include color vision and computational approaches to understanding biological vision.
Nicu first became interested in robotics through a class in middle school wherein he used LEGO Mindstorms to build small robots which achieved simple tasks. While working on his undergraduate degree in Computer Science at the University of Texas at Austin (UT), he became involved with the school's student branch of the IEEE Robotics and Automation Society. As an active member in the club, he led efforts to build entries to various robotics competitions from regional to international. While at UT, he also participated in research on autonomous cars (particularly, autonomous intersection management) and robot soccer. For these efforts, he earned the distinction of Honorable Mention in the Computing Research Association's Outstanding Undergraduate Researcher Award competition for 2011. He is also a member of the UT Austin Villa robot soccer team which won the 2011 world championship. Presently, Nicu is involved with computer vision research including texture detection, and object detection, recognition, and pose estimation. He is also interested in using GPUs to accelerate vision algorithms for use in robotics. In his spare time, Nicu enjoys playing board games and dancing.
(Mabel) Mengzi Zhang
Mengzi did her undergraduate studies at the University of California - San Diego (UCSD), during which she studied abroad at the University of Edinburgh, United Kingdom, where she was introduced to Artificial Intelligence. Her graduate research focus is vision and robotics. She has three years of undergraduate research experience in a number of projects in computer vision, machine learning, and virtual reality with computer graphics, most of which were done at UCSD, with one summer at the University of Washington. Some of the research projects she has done include insect classification, food cuisine classification, virtual reality scientific visualization, improving future teleconference systems, among others; two of which she published conference papers as first-author and co-author in her undergrad. She has also had introductory experience with robotics in Edinburgh, UCSD IEEE MicroMouse, and helping out with FIRST Lego League and First Robotics Competition in the US and UK. In a scope of broader impact, she is interested in bringing more underrepresented young population into the STEM (Science, Technology, Engineering, and Mathematics) fields, including women and the disabled; her efforts were awarded by the Google Anita Borg Scholarship US Finalist award in 2011.
For his undergraduate education, Isaac studied physics and computer science at the University of Maryland in College Park. While there, he worked on computational projects in several different fields, including superconductor-circuits, particle physics, and cosmology. Now a member of the Physics graduate group at the University of Pennsylvania, he is working on computational models of auditory natural scene encoding in the auditory cortex. He is primarily interested in how cortical circuits encode specific features of sound and context in order to represent a salient stimulus.