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181 - 190 of 204 results for: MS

MS&E 494: The Energy Seminar (CEE 301, ENERGY 301)

Interdisciplinary exploration of current energy challenges and opportunities, with talks by faculty, visitors, and students. May be repeated for credit.
Terms: Aut, Win, Spr | Units: 1 | Repeatable for credit
Instructors: Weyant, J. (PI)

MS&E 495: Sustainable Energy Interdisciplinary Graduate Seminar (CEE 372, ENERGY 309)

Graduate students will present their ongoing research to an audience of faculty and graduate students with a diversity of disciplinary perspectives regarding sustainable energy.
Terms: Win, Spr | Units: 1 | Repeatable 6 times (up to 6 units total)

MS&E 802: TGR Dissertation

Terms: Aut, Win, Spr, Sum | Units: 0 | Repeatable for credit

NENS 222: Dance, Movement and Medicine: Immersion in Dance for PD (DANCE 100)

Combining actual dancing with medical research, this Cardinal Course investigates the dynamic complementary relationship between two practices, medicine and dance, through the lens of Parkinson's disease (PD), a progressive neurological disease that manifests a range of movement disorders. "Dance for PD" is an innovative approach to dancing --and to teaching dance --for those challenged by PD. Course format consists of: 1. Weekly Lecture/Seminar Presentation: Partial list of instructors include Ms. Frank, Dr. Bronte-Stewart and other Stanford medical experts & research scientists, David Leventhal (Director, "Dance for PD") and Bay Area "Dance for PD" certified master teachers, film-maker Dave Iverson, Damara Ganley, and acclaimed choreographers Joe Goode, Alex Ketley, Judith Smith (AXIS Dance). 2. Weekly Dance Class: Stanford students will fully participate as dancers, and creative partners, in the Stanford Neuroscience Health Center's ongoing "Dance for Parkinson's" community dance class for people with PD. This Community Engaged Learning component provides opportunity to engage meaningfully with people in the PD community. Dancing together weekly, students will experience firsthand the embodied signature values of "Dance for PD" classes: full inclusion, embodied presence, aesthetic and expressive opportunity for creative engagement, and community-building in action. A weekly debriefing session within Friday's class time will allow students to integrate seminar material with their movement experiences.nnnNO PRE-REQUISITES: No prior dance experience required. Beginners are welcome.
Last offered: Winter 2018 | Repeatable for credit

NENS 250S: Windows Into the Brain: Unlocking Mysteries through Neurologic Disease

Dementia, epilepsy, Parkinson¿s disease, stroke, brain tumors, MS, traumatic brain injury, headaches, and many other neurologic diseases inflict a tremendous toll on the individual and society. In this course, using material adapted from what is taught second-year medical students at the Stanford School of Medicine, we will explore different neurologic ailments to provide a window into the mysteries of brain function (and dysfunction). All that is needed is a solid background in high school biology, and the burning desire to dive deep into the complex and fascinating world of clinical neuroscience. Students will be provided the background neuroanatomy, neurophysiology, and neuropathology that is necessary to understand the underpinnings, presentation, diagnosis, and treatment of some of the most common diseases that affect the central nervous system. Lectures are taught by clinical faculty from the Department of Neurology & Neurological Sciences and will use real cases, neuroimaging, and videos in an interactive and stimulating setting. Students will learn about the cutting-edge technologies used in 2020 in Neurology and Neurosurgery to manage patients with these illnesses. Get ready for an exciting and dynamic sneak peek into medical school and the mysteries of the human brain!

OIT 344: Design for Service Innovation

Design for service innovation is an experiential course in which students work in multidisciplinary teams to design new services (including but not limited to web services) that will address the needs of an underserved population of users. Through a small number of lectures and guided exercises, but mostly in the context of specific team projects, students will learn to identify the key needs of the target population and to design services that address these needs. Our projects this year will focus on services for young adult survivors of severe childhood diseases. For the first time ever, children who have cystic fibrosis, rheumatoid arthritis, major cardiac repairs, organ transplants, genetic metabolic disorders, and several forms of cancer are surviving. The first wave of these survivors is reaching young adulthood (ages 18-25). Many aspects of the young adult world are not yet user-friendly for them: applying to and then entering college, adherence to required medication and diet, more »
Design for service innovation is an experiential course in which students work in multidisciplinary teams to design new services (including but not limited to web services) that will address the needs of an underserved population of users. Through a small number of lectures and guided exercises, but mostly in the context of specific team projects, students will learn to identify the key needs of the target population and to design services that address these needs. Our projects this year will focus on services for young adult survivors of severe childhood diseases. For the first time ever, children who have cystic fibrosis, rheumatoid arthritis, major cardiac repairs, organ transplants, genetic metabolic disorders, and several forms of cancer are surviving. The first wave of these survivors is reaching young adulthood (ages 18-25). Many aspects of the young adult world are not yet user-friendly for them: applying to and then entering college, adherence to required medication and diet, prospects for marriage and parenthood, participation in high school or college sports, driving, drinking, drugs, and more. Our aspiration is to develop services to improve these young adults? options for a fulfilling and satisfying life. The course is open to graduate students from all schools and departments: business (MBA1, MBA2, PhD, Sloan), Medicine (medical students, residents, fellows and postdocs), engineering (MS and PhD), humanities, sociology, psychology, education, and law. Students can find out more about this course at: http://DesignForService.stanford.edu; GSB Winter Elective BBL Jan 10th, 12 noon - 1 pm; D-School Course Exposition Feb 3rd, time TBA. Admission into the course by application only. Applications will be available at http://DesignForService.stanford.edu on Jan 13th. Applications must be submitted by Feb 4th midnight. Students will be notified about acceptance to the course by Feb 7th . Accepted students will need to reserve their slot in the course by completing an online privacy training course. Details about online training will be provide to accepted students. The training is related to the protection of our partners' privacy. Application Deadline: Noon, Feb 4th.
Last offered: Spring 2011

OIT 602: Dynamic Pricing and Revenue Management I

In tandem with OIT 603, this course explores the application of stochastic modeling and optimization to two closely related problem areas: (a) dynamic price selection, and (b) dynamic allocation of limited capacity to competing demands. As background, students are assumed to know stochastic process theory at the level of Statistics 217-218, microeconomics at the level of Economics 202N, and optimization theory at the level of MS&E 211, and to have some familiarity with the basic ideas of dynamic programming. Additional dynamic programming theory will be developed as needed for the applications covered. Emphasis will be on current research topics, especially in the realm of airline revenue management.

OIT 603: Dynamic Pricing and Revenue Management II

In tandem with OIT 602, this course explores the application of stochastic modeling and optimization to two closely related problem areas: (a) dynamic price selection, and (b) dynamic allocation of limited capacity to competing demands. As background, students are assumed to know stochastic process theory at the level of Statistics 217-218, microeconomics at the level of Economics 202N, and optimization theory at the level of MS&E 211, and to have some familiarity with the basic ideas of dynamic programming. Additional dynamic programming theory will be developed as needed for the applications covered. Emphasis will be on current research topics, especially involving customized pricing of financial services. OIT 602 is not a prerequisite for OIT 603 but is highly recommended.
Last offered: Spring 2009

OIT 611: The Drift Method: from Stochastic Networks to Machine Learning

Overview: This course is an introduction to the drift method in sequential decision-making and stochastic systems, a family of simple, yet surprisingly powerful, meta-algorithms that in each step the greedily and incrementally minimizes some potential function. Manifested in various forms, the drift method powers some of the most popular algorithmic paradigms in stochastic networks (MaxWeight, BackPressure), oneline learning, optimization and machine learning (SGD, Langevin dynamics, TD-learning). Using the Drift Method as a unifying theme, we will survey major developments in these areas and answer questions such as: What may explain the method¿s effectiveness? How can we rigorously evaluate its performance? We will develop rigorous probabilistic and optimization methodologies for answering these questions, such as Lyapunov functions and stability theory, state-space collapse, weak convergence and Stein¿s method. In terms of application topics, the course is roughly evenly divided bet more »
Overview: This course is an introduction to the drift method in sequential decision-making and stochastic systems, a family of simple, yet surprisingly powerful, meta-algorithms that in each step the greedily and incrementally minimizes some potential function. Manifested in various forms, the drift method powers some of the most popular algorithmic paradigms in stochastic networks (MaxWeight, BackPressure), oneline learning, optimization and machine learning (SGD, Langevin dynamics, TD-learning). Using the Drift Method as a unifying theme, we will survey major developments in these areas and answer questions such as: What may explain the method¿s effectiveness? How can we rigorously evaluate its performance? We will develop rigorous probabilistic and optimization methodologies for answering these questions, such as Lyapunov functions and stability theory, state-space collapse, weak convergence and Stein¿s method. In terms of application topics, the course is roughly evenly divided between stochastic queueing networks versus optimization + machine learning. Objective: For students to acquire fundamental methodologies that can be applied to tackling problems in dynamic decision-making, stochastic modeling and machine learning. Target Audience: Graduate students / advanced undergraduates with a solid grasp of probability and stochastic processes (Stat 310A / MS&E 321, or equivalent). Strong background and interests in queueing networks is highly recommend.
Terms: Aut | Units: 3
Instructors: Xu, K. (PI)

PSYC 308E: Trauma Psychiatry

VISITING: Open to visitors. TYPE OF CLERKSHIP: Selective 1. DESCRIPTION: The Trauma Psychiatry clerkship teaches how trauma impacts the lives and health of patients; lessons learned are generalizable to all areas of medicine (i.e., "trauma-informed medicine"). Students work with people suffering from PTSD relating to sexual assault, combat or other traumas, and receiving ambulatory-type treatments in an intensive, multidisciplinary setting. Students have direct patient responsibility; provide evidence-based psychopharmacologic, psychotherapeutic, and longitudinal management; facilitate recovery; and gain perspective on trauma in our world and the importance of sensitive/effective treatment for PTSD (7.8% lifetime prevalence). This clerkship will involve both in-person and virtual participation, five days per week with no call or weekend duties. PREREQUISITES: Visiting students must obtain approval from Ms. Quynh Dang prior to applying for this clerkship. Please email requests to qdang@ more »
VISITING: Open to visitors. TYPE OF CLERKSHIP: Selective 1. DESCRIPTION: The Trauma Psychiatry clerkship teaches how trauma impacts the lives and health of patients; lessons learned are generalizable to all areas of medicine (i.e., "trauma-informed medicine"). Students work with people suffering from PTSD relating to sexual assault, combat or other traumas, and receiving ambulatory-type treatments in an intensive, multidisciplinary setting. Students have direct patient responsibility; provide evidence-based psychopharmacologic, psychotherapeutic, and longitudinal management; facilitate recovery; and gain perspective on trauma in our world and the importance of sensitive/effective treatment for PTSD (7.8% lifetime prevalence). This clerkship will involve both in-person and virtual participation, five days per week with no call or weekend duties. PREREQUISITES: Visiting students must obtain approval from Ms. Quynh Dang prior to applying for this clerkship. Please email requests to qdang@stanford.edu. None for internal students. PERIODS AVAILABLE: 1-16, full-time for three weeks, 2 students per period. CLERKSHIP DIRECTOR: James Armontrout, M.D. CLERKSHIP COORDINATOR: Quynh Dang, 650-725-2769, 401 Quarry Rd, Rm. 2204. REPORTING INSTRUCTIONS: Where: Please report to Menlo Park building 351 on the first day. Let nursing know you are a medical student and will be working with Psychiatrist James Armontrout. During the pandemic, if possible please email James Armontrout (james.armontrout@va.gov) the week before so that he can provide you with mobile contact numbers and any relevant videoconferencing links before your rotation starts; Time: 8:00 a.m. CALL CODE: 0. OTHER FACULTY: A. Franciscus. LOCATION: VA Menlo Park.
Terms: Aut, Win, Spr, Sum | Units: 5
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