BCSC 433-1
Daniel Gildea
TR 11:05AM - 12:20PM
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An introduction to statistical natural language processing and automatic speech recognition techniques. This course presents the theory and practice behind the recently developed language processing technologies that enable applications such as speech-driven dictation systems, document search engines (e.g., finding web pages) and automatic machine translation. Students taking this course at the 400 level will be required to complete additional readings and/or assignments.
- Location
- Hylan Building Room 101 (TR 11:05AM - 12:20PM)
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BCSC 519-1
Tim Jaeger; Oviya Mohan; Yue Zhang
MW 2:00PM - 3:15PM
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This course discusses statistical concepts and procedures commonly used in brain and cognitive sciences research. It is a peer-led class, meaning that each student will take part in actively teaching some of the concepts. You will be evaluated on your participation in class and the effort in organizing your lessons. Major topics include: 1) linear models, 2) linear mixed effects models and 3) bayesian data analysis. If time permits, we will go over some more advanced topics in statistics, including MCMC, time series analysis, etc. Prerequisites for undergraduates: STAT 212 or equivalent; research experience from BCSC/NSCI 395 or BCSC 206/207; and programming experience in R, Python, or MATLAB. Interested undergraduates should contact Yue Zhang (yzh191@u.rochester.edu) and Oviya Mohan (omohan@u.rochester.edu).
- Location
- Meliora Room 301B (MW 2:00PM - 3:15PM)
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BCSC 520-1
Michele Rucci
TR 3:25PM - 4:40PM
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Provides an interdisciplinary view of modern research into how the human brain solves the problems involved in perception, including how we perceive the three-dimensional structure of the world, how we recognize objects and how visual information is used to control action in the world. Students read contemporary research and, through classroom discussion and critical essays, explore and analyze the questions and debates that define contemporary perceptual science.
- Location
- Meliora Room 269 (TR 3:25PM - 4:40PM)
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BCSC 528-1
Duje Tadin
F 12:00PM - 2:30PM
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Advanced graduate seminar on a chose problem in vision sciences. In previous years, topics have included motion perception, stereopsis, color vision and visuo-motor control. Readings for the course are drawn from the scientific literature in the topic being covered. Students are typically required to lead discussions on papers.
- Location
- Meliora Room 301B (F 12:00PM - 2:30PM)
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BCSC 541-1
Farran Briggs
TR 9:40AM - 10:55AM
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This course takes a bottom-up approach to understanding the neurons and circuits of the sensory systems in the mammalian brain. Thematic topics will include: structural and functional diversity among sensory neuronal populations, common themes across sensory systems such as parallel information processing, coordination among feedforward/feedback circuits, and neuronal plasticity during development of functional domains. The final course module will focus on exploring the neuronal mechanisms of attention, again from a neuron- and circuit-centric perspective. Visual, auditory, and somatosensory systems will be discussed with most emphasis on the visual system as a model for understanding structure/function relationships. The course will also introduce students to modern methodological approaches in systems neuroscience aimed at measuring and manipulating the activity of large populations of neurons while also incorporating information about individual neuronal identity, structure, and circuit connectivity. Prerequisite: BCSC 240/NSCI 201
- Location
- Meliora Room 205 (TR 9:40AM - 10:55AM)
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BCSC 542-1
Melinda Patterson
MW 4:50PM - 6:05PM
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Examines clinical neuropsychology, which bridges neurology, neuroscience, and clinical psychology. Covers history of clinical neuropsychology, principles of neuropsychological assessment, and the interpretation of cognition and behavior as they relate to brain dysfunction. Considers specific neurological syndromes including neurodegenerative, cerebrovascular, toxic, and memory disorders; epilepsy; head trauma; infectious processes; pediatric neuropsychology; psychiatric syndromes; and forensic neuropsychology. Patient presentations (videotape and in-person interviews) supplement lectures. Prerequisite: BCSC 110 or BCSC 240/NSCI 201
- Location
- Meliora Room 203 (MW 4:50PM - 6:05PM)
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BCSC 543-1
Renee Miller
MWF 10:25AM - 11:15AM
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This class covers how the brain controls behavior, and what goes wrong in various diseases, from a neurochemistry perspective. We start by learning about the neurochemicals –neurotransmitters, peptides, growth factors, etc. and move on to their receptors and associated signaling pathways, including gene transcription and epigenetics. An emphasis is placed on primary research literature, experimentation/data analysis and application of knowledge to the interpretation of scientific data. Students will attend research seminars on campus or online and write brief summaries of their understanding. The course culminates in small group presentations about the neurochemistry of diseases of interest, and an individual research review paper on the same topic. Prerequisite: BCSC 240/NSCI 201. BIOL 250 is helpful but not required.
- Location
- Goergen Hall Room 109 (MWF 10:25AM - 11:15AM)
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BCSC 547-1
Ralf Haefner
TR 12:30PM - 1:45PM
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Computational neuroscience studies how the brain can be understood in terms of computations implemented by neural circuits, and in terms of using computational methods to analyze neural and behavioral data. This course for advanced undergraduates and graduate students starts with models of individuals neurons before moving on to networks of neurons and behavior. It provides both a classic signal processing, and a probabilistic perspective on how neurons support the brain’s computations. While primarily lecture-based, an important part of the course are exercises that typically consist on implementing (programming) a model discussed in the class and analyze its behavior. The course also provides the opportunity for a final project but this is not required. The material mostly considers the sensory system and perceptual decision-making. There are no formal prerequisites. However, programming experience and a minimal background in linear algebra (vectors and matrices) and analysis (basic ordinary differential equations) are essential. At the beginning, there will be a very brief introduction to the key biological concepts necessary for the course. In doubt, please email the instructor.
- Location
- Meliora Room 224 (TR 12:30PM - 1:45PM)
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BCSC 570-1
Mujdat Cetin
MW 2:00PM - 3:15PM
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This course provides a broad introduction to augmented and virtual reality (AR/VR) systems. The course involves lectures covering an overview of all aspects of the AR/VR domain, as well as individual work performed by each student aimed at providing more intensive training on various aspects of AR/VR. Topics covered in the lectures include history, conceptual origins, and design/evaluation principles of AR/VR technologies; overview of visual/auditory/haptic AR/VR interfaces and applications; visual perception; optics/platforms/sensors/displays; auditory perception and spatial audio; silicon hardware architecture and materials; graphics and computation; interfaces and user experience design; data processing and machine intelligence for AR/VR; introduction to AR/VR programming tools; societal implications and ethical aspects. At the end of the course, students will have gained familiarity with the techniques, languages, and cultures of fields integral to the convergent research theme of AR/VR. This course is co-instructed by Mujdat Cetin, Michele Rucci, Ross Maddox, Jannick Rolland, Yuhao Zhu, Andrew White, Chenliang Xu, and Zhen Bai.
- Location
- Goergen Hall Room 109 (MW 2:00PM - 3:15PM)
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BCSC 572-1
Mujdat Cetin
TR 9:40AM - 10:55AM
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This is the third course offered as part of the PhD training program on augmented and virtual reality (AR/VR). The goal of the course is to provide interdisciplinary collaborative project experience in AR/VR. The course involves small teams of students from multiple departments working together on semester-long projects on AR/VR with the guidance of one or more faculty involved in the PhD training program. The expected end products of this Practicum course are tangible artifacts that represent what the students have learned, discovered, or invented. Types of artifacts include research papers; patent applications; open-source software; as well as online tutorials and videos for undergraduates, K-12 students, or the general public. Prerequisites: ECE 410-1 or OPT 410-1 or BME 410-1 or BCSC 570-1 or NSCI 415-1 or CSC 413-1 or CVSC 534-1 Instructors: Lead - Mujdat Cetin; Zhen Bai, Jannick Rolland, Michele Rucci
- Location
- Computer Studies Room 426 (TR 9:40AM - 10:55AM)
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BCSC 595-01
Ralf Haefner
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BCSC 595-02
Manuel Gomez-Ramirez
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BCSC 595-03
Duje Tadin
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BCSC 595-04
Robert Jacobs
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BCSC 595-05
Michele Rucci
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BCSC 595-06
Adam Snyder
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BCSC 595-07
Martina Poletti
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BCSC 595-08
Gregory DeAngelis
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BCSC 595-11
Karl Rosengren
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BCSC 595-12
Elise Piazza
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BCSC 595-13
Dora Biro
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BCSC 595-14
Ian Fiebelkorn
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BCSC 598-07
Ralf Haefner
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BCSC 598-1
Melinda Patterson
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BCSC 598-14
Farran Briggs
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BCSC 598-2
Duje Tadin
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BCSC 598-3
Chung-Lin Yang
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BCSC 598-4
Gregory DeAngelis
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BCSC 598-5
Dora Biro
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BCSC 598-6
Robert Jacobs
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BCSC 897-1
Ralf Haefner
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BCSC 995-1
Tim Jaeger
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BCSC 997-1
Michele Rucci
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BCSC 997-2
Duje Tadin
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BCSC 999-01
Ralf Haefner
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BCSC 999-02
Manuel Gomez-Ramirez
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BCSC 999-03
Duje Tadin
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BCSC 999-04
Robert Jacobs
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BCSC 999-05
Michele Rucci
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BCSC 999-06
Adam Snyder
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BCSC 999-07
Martina Poletti
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BCSC 999-08
Gregory DeAngelis
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BCSC 999-09
Rajeev Raizada
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BCSC 999-10
Tim Jaeger
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BCSC 999-11
Jude Mitchell
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