Carmen Varela, Research Scientist
Enrollment: To sign up, please email: carmenv@mit.edu
Limited to 15 participants
Attendance: Priority will be given to participants that can attend all sessions
Prereq: None. Particularly suitable for postdocs and Jr. faculty
The business and academic worlds are often seen as involving fairly different cultures and work styles. Yet the way successful companies like Google, Apple, or Pixar approach management, creativity, or the organization and motivation of their workforce may be applicable and beneficial to academic scientific practice. Through readings and discussions, we will explore and reflect on the approaches that business schools and companies take to address issues (management, team dynamics, creativity) that are essential components of research practice. The overall goal of these reading/discussion sessions is to work together on a series of business-related readings in order to learn about and discuss strategies used in the business world to address issues that, while important in neuroscience, are often ignored in academic labs and training schools.
Readings will be distributed on Monday each week for group discussion on Thursday. The topics for each Thursday will be as follows:
Week 1. Management and Leadership: Academia vs Business
Week 2. Recruitment, Motivation, and Team Dynamics
Week 3. Creativity and Innovation
Sponsor(s): Brain and Cognitive Sciences
Contact: Carmen Varela, 46-5233, 617-501-6261, carmenv@mit.edu
Jan/11 | Mon | 05:30PM-06:00PM | 46-4062 |
Jan/15 | Fri | 05:30PM-07:00PM | 46-4062 |
Jan/22 | Fri | 05:30PM-07:00PM | 46-4062 |
Jan/29 | Fri | 05:30PM-07:00PM | 46-4062 |
Vikash Mansinghka, Research Scientist
Enrollment: Limited: Advance sign-up required
Limited to 20 participants
Attendance: Participants must attend all sessions
Prereq: Familiarity with Python
Probabilistic inference is a widely-used, mathematically rigorous approach for interpreting ambiguous information using models that are uncertain and/or incomplete. It has become central to multiple fields, from big data analytics to robotics and AI to computational modeling of the mind and brain. However, it currently requires deep technical expertise to use. Models and inference algorithms are difficult to communicate, design, implement, validate, and optimize, and inference often appears to be fundamentally intractable. The emerging field of probabilistic programming aims to make modeling and inference broadly accessible to non-experts, especially to facilitate data analysis, and to enable experts to tackle problems that are currently infeasible, especially in machine intelligence.
This class offers an introduction to probabilistic programming, emphasizing applications to Bayesian data analysis. The course will provide hands-on experience with the Venture and BayesDB platforms. Students will learn how to use probabilistic programming for data exploration, cleaning, confirmatory analysis, and predictive modeling. Students will also be exposed to techniques for writing custom models and inference programs that are suitable for more complex problems.
(Students should be familiar with basic programming and statistical concepts. Familiarity with Python is required)
Sponsor(s): Brain and Cognitive Sciences
Contact: Rax Dillon, N/A, N/A, rax@mit.edu
Jan/05 | Tue | 02:00PM-04:00PM | 46-3015 |
Jan/07 | Thu | 02:00PM-04:00PM | 46-3015 |
Jan/19 | Tue | 02:00PM-04:00PM | 46-3015 |
Jan/26 | Tue | 02:00PM-04:00PM | 46-3015 |
Vikash Mansinghka - Research Scientist
Jan/12 | Tue | 02:00PM-04:00PM | 46-1015 |
Jan/14 | Thu | 02:00PM-04:00PM | 46-1015 |
Jan/21 | Thu | 02:00PM-04:00PM | 46-1015 |
Jan/28 | Thu | 02:00PM-04:00PM | 46-1015 |
Vikash Mansinghka - Research Scientist
Maria Dauvermann, Postdoctoral Associate
Enrollment: Limited: First come, first served (no advance sign-up)
Limited to 15 participants
Attendance: Participants must attend all sessions
Prereq: None
It has been estimated that 18.5% of adults in the U.S. had a psychiatric disorder in 2013. The treatment success rates with traditional pharmacology among every psychiatric disorder are very low. This goes hand-in-hand with the limitations of currently available diagnostic and prognostic tools.
We know that the brain plays a major role in the development of these disorders. Therefore, technologies for potential diagnosis and treatment options have been developed that aim to change the function of the brain. These new technologies for diagnosis and invention approaches are in development but require thorough translational research before they can be safely used in patients.
The aim of the course is to teach about technologies and intervention approaches that move beyond pharmacology as the sole treatment option. Over the course of four sessions, you will learn how brain scientists from different disciplines (biologists, chemists, physicists, psychologists, informaticians, engineers) invent and develop techniques in multiple translational steps as diagnosis and treatment options for patients. You will design and present your own translational study at the end of the course.
Session 1: Currently available techniques and treatment options
Session 2: Promising technologies for diagnosis and treatment options in humans, monkeys and rodents
Session 3: Practical translational research steps across species
Session 4: Design, presentation and discussion of translational studies
Sponsor(s): Brain and Cognitive Sciences
Contact: Maria Dauvermann, 46-2171, 617-324-3599, mariad@mit.edu
Jan/07 | Thu | 01:00PM-03:00PM | 46-4062 |
Jan/08 | Fri | 01:00PM-03:00PM | 46-4062 |
Jan/14 | Thu | 01:00PM-03:00PM | 46-4062 |
Jan/15 | Fri | 01:00PM-03:00PM | 46-4062 |
Maria Dauvermann - Postdoctoral Associate
Greg Hale, Applications/Technical Specialist
Enrollment: Limited: First come, first served (no advance sign-up)
Attendance: Participants welcome at individual sessions
Prereq: N/A
Do you have a dataset that you want to share, an algorithm that predicts diseases from gene mutations, or a neat way to visualize data? Maybe these things want to live and work on the internet. Bring your ideas, and we will look at (maybe even implement!) some of the tools for crossing the chasm from screenshots of your local solution to a working resource the whole world could
use.
Topics will depend on the interests of people in the course. We may look at building and hosting web pages, sharing small or large datasets, Amazon Web Services, interactive svg figures in web pages, and writing public API servers. The focus will be on doing these things without too much disruption to your normal research routine, and on building the confidence to go further in your own explorations
in web development.
Sponsor(s): Brain and Cognitive Sciences
Contact: Greg Hale, 46-5169, (908) 797-8281, greghale@mit.edu
Jan/11 | Mon | 03:00PM-04:30PM | 46-5165 |
Jan/12 | Tue | 03:00PM-04:30PM | 46-5165 |
Jan/13 | Wed | 03:30PM-05:00PM | 46-5056 |
Jan/14 | Thu | 03:00PM-04:30PM | 46-5165 |
Jan/15 | Fri | 03:00PM-04:30PM | 46-5165 |
Greg Hale - Applications/Technical Specialist
Greg Hale, Applications/Technical Specialist
Enrollment: Limited: First come, first served (no advance sign-up)
Attendance: Participants welcome at individual sessions
Prereq: N/A
Give version control a try, in a laid back environment that's about you, your experiments, your class projects, etc. Getting over the hump with git can make life a lot easier if you keep multiple copies of files, want to try out experimental changes without fear of breaking things, or collaborate with others. You don't need to take a class to learn git, but it can be nice to have an ice-breaker, so bring along your own homework or personal projects and we can get set up.
We will run three sessions, you probably only need to attend one. But if you come to more than one, you might already feel capable of helping newcomers.
Some start-ups now spend more time looking at Github profiles than CV's. No matter how small your personal projects are, putting them up on Github can be great boost your career.
Sponsor(s): Brain and Cognitive Sciences
Contact: Greg Hale, 46-5169, (908) 797-8281, greghale@mit.edu
Jan/04 | Mon | 03:00PM-04:30PM | 46-5165 |
Jan/06 | Wed | 03:00PM-04:30PM | 46-5165 |
Jan/08 | Fri | 03:00PM-04:30PM | 46-5165 |
Greg Hale - Applications/Technical Specialist
Andrea Tacchetti
Jan/15 | Fri | 10:00AM-05:00PM | 46-3002 |
Enrollment: Unlimited: No advance sign-up
Prereq: None
Neuroscience has made huge advances in the last few years. We now know more about how the brain works than we have ever known before. Likewise, Computer Science and Artificial Intelligence have made enormous steps forward and have become part of our every-day lives. The interaction between Neuroscience and Computer Science has inspired most recent advances in Artificial Intelligence and this interaction has become a critical stepping stone for the understanding of intelligence. We assembled a stellar list of speakers at the intersection of Neuroscience and AI from both sides of Vassar Street who will give an account of how this multi-disciplinary interaction affects their work. The tentative list of speakers includes:
Professor Ed Boyden
Professor Tomaso Poggio
Professor Nancy Kanwisher
Professor Feng Zhang
Professor Bill Freeman
Professor Joshua Tenenbaum
Schedule and other information about the event can be found here: http://cbmm.mit.edu/science-engineering-vassar
Sponsor(s): Brain and Cognitive Sciences
Contact: Andrea, Tacchetti, N/A, atacchet@MIT.EDU
Emily Mackevicius
Enrollment: Unlimited: Advance sign-up required
Attendance: Participants welcome at individual sessions
Prereq: Geared towards BCS grad students & postdocs, others welcome
Each tutorial will consist of a short lecture, and then 'office hours' time to work through practice problems and discuss problems people want help with in their own research. The goal is to get people past the initial learning curve in particular computational topics relevant to BCS, and get people from across the department talking about common computational methods. Food will be provided.
Please sign up for tutorials here: https://docs.google.com/forms/d/11yK-Xqc_1UU29qWAuQLqZjtMXyidLohxGVUIO9MjUjQ/viewform
Materials will be posted here (Currently this site has material for previous BCS computational tutorials. If you sign up, I'll email you when current materials are posted.): https://stellar.mit.edu/S/project/bcs-comp-tut/index.html
Sponsor(s): Brain and Cognitive Sciences
Contact: Emily Mackevicius, ELM@MIT.EDU
Jan/12 | Tue | 04:00PM-06:00PM | 46-3310 |
Taught by: Satrajit Ghosh and Evan Remington
Jan/19 | Tue | 04:00PM-06:00PM | 46-3310 |
Taught by: Emily Mackevicius and Greg Ciccarelli
Jan/21 | Thu | 04:00PM-06:00PM | 46-3310 |
Taught by: Sam Norman-Haignere
Jan/22 | Fri | 02:00PM-04:00PM | 46-3310 |
Taught by: Seth Egger
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