Past Events

  • Join the Carney Institute for Brain Science for a conversation about how traditional brain recording techniques (MEG/EEG) are coming together with new computational tools to inform new directions for brain science research. 

    This event will be moderated by Diane Lipscombe, Reliance Dhirubhai Ambani Director of the Carney Institute, and Christopher Moore, associate director of the Carney Institute, and it will feature Stephanie Jones, associate professor of neuroscience at Brown University, and Frederike Petzschner, who will join the Carney Institute this year as a fellow. 

    Biology, Medicine, Public Health, CCBS, Psychology & Cognitive Sciences, Research
  • This two-week workshop, organized by Carney’s Center for Computational Brain Science, will provide the basic tools for understanding, developing and applying models to brain science questions, from high-level cognition (how do I choose where to eat lunch?), to neural mechanisms (how do our neurons decide whether an animal is a dog or a lion?).

    This workshop is designed for researchers across fields, backgrounds and levels of experience: computation “novices” with no experience and those with more computational experience who have not yet mastered the science of model selection and parameter estimation, or wish to learn more on specific classes of models.

    Week 1

    Week 1 will cover methods and challenges of using computational models for hypothesis testing and quantitative fitting of behavioral data and brain-behavior relationships. Topics include model validation and selection, posterior predictive checks, maximum likelihood, hierarchical estimation, neural regressors, etc. We will have daily lectures and discussion, as well as hands-on coding tutorials, and advanced sessions providing a deeper understanding of complex modeling topics, pitfalls and concepts, for participants already familiar with basic techniques.

    Week 2

    In Week 2, participants will have a chance to participate in a collaborative modeling challenge, using a novel dataset that integrates across multiple aspects of cognition and perception, including cross-species neural data. Prizes will be given for models with best predictive power, rigor, creativity and innovation.

    Computational experience is not required.

    For details on last years’ workshops, visit the Center for Computational Brain Science website . View last year’s syllabus . We will cover most of the same basic topics, with a few tweaks and additions (to be determined based on participant input).

    Participation is limited to 20. Please use this form to sign up.

    CCBS, Psychology & Cognitive Sciences, Research
  • Join the Carney Institute for a weekly informal gathering on methods for brain science, featuring rotating topics selected by the Brown brain science community. Vote for your preferred topic using this form.

    This week’s topic is animal behavioral monitoring. We will be joined by David Sheinberg, professor of neuroscience at Brown.

    Please note, this workshop requires you to be logged into Zoom through your Brown account. Click to learn more .

    Biology, Medicine, Public Health, CCBS, CTN, Psychology & Cognitive Sciences, Research
  •  Carney Methods Meetups

    Join the Carney Institute for a weekly informal gathering on methods for brain science, featuring rotating topics selected by the Brown brain science community. Vote for your preferred topic using this form.  

    This week’s topic is Deep sequencing platforms/technologies. We will be joined by Christoph Schorl, assistant professor of biology (research) at Brown and facility director of the Brown Genomics Facility. 

    Please note, this workshop requires you to be logged into Zoom through your Brown account. Click to learn more .

    Biology, Medicine, Public Health, CCBS, CTN, Psychology & Cognitive Sciences, Research
  • Jun
    29
    All Day

    Brown Unconference

    Zoom

    The first Brown Unconference is a remote gathering which provides an opportunity for researchers across campus to come together and explore advances in computational sciences at the intersection of data science and AI with other sciences including biology, physics, chemistry, engineering, neuroscience and cognitive science.

    Our goal is to foster an accessible and welcoming environment open to members of the Brown community across all disciplines and levels of expertise. We want to celebrate Brown’s uniqueness and help foster collaborations across disciplines. Students and postdocs are especially encouraged to present their research to the broader community. The Unconference will include opportunities to meet researchers across scientific interests, hear from invited speakers, and receive feedback from diverse points of view.

    We encourage submissions at all points of the scientific process.

    Important Dates

    • Abstract Submission Deadline: June 15, 2020
    • Conference: June 29-30, 2020

    Schedule
    We will host the following events distributed across the two days of the conference. Please find instructions on how to get involved in the next section. The detailed schedule will be published closer to the conference.

    • Lightning talks: 2-3 minute talks (2 slides max) – for those who may be in the early stages of their research, to introduce themselves, share their interests, pitch projects, or simply network with other members of the conference.
    • Short talks: 12 minute talks – for those ready to present their research in an informal setup. Presented research can be in progress and data can be preliminary.
    • Networking & Mind Match: Tailored social and networking programming. The unconference is a safe space to share ideas so feel free to send work in progress. Members of the Brown community from all academic backgrounds are encouraged to submit an abstract!

    Register to Attend
    Register to attend the conference virtually . By registering, you will receive a notification when we announce the schedule with links to the Crowdcast pages.

    Submit an Abstract
    If you’re interested in talking about your research, please submit an abstract .

    Biology, Medicine, Public Health, CCBS, Psychology & Cognitive Sciences, Research
  • Carney Methods Meetups

    Join the Carney Institute for a weekly informal gathering on methods for brain science, featuring rotating topics selected by you, the Brown brain science community! Please vote for next week’s topic using this form .

     

    This week’s topic is “Dynamical Models of Neural Systems”, presented by Bjorn Sandstede, Ph.D. Bjorn is a Professor of Applied Mathematics and is the Director of the Data Science Initiative .

     

    Please note, this workshop requires you to be logged into Zoom through your Brown account. Click to learn more .

    Biology, Medicine, Public Health, CCBS, Graduate School, Postgraduate Education, Psychology & Cognitive Sciences, Research
  • “Information and randomization in exploration and exploitation,” featuring:

    Robert Wilson, Ph.D.

    Assistant Professor

    University of Arizona

    Abstract: The explore-exploit dilemma is a fundamental behavioral dilemma faced
    by any organism that can learn. Should we explore new options in the
    hopes of learning something new or exploit options we already know to
    be good. In this talk I will present evidence that people use two
    distinct strategies for solving the explore-exploit dilemma: directed
    exploration, in which information seeking drives exploration by
    choice, and random exploration, in which behavioral variability drives
    exploration by chance. In addition I will present initial evidence
    showing that these two types of exploration rely on dissociable neural
    systems.

    Contact [email protected] for the Zoom meeting password.

    CCBS, Psychology & Cognitive Sciences, Research
  • May
    6
    10:00am

    CCBS Seminar

     

    Anna Schapiro, Ph.D.

    University of Pennsylvania

    “Learning distributed representations in the human brain”

     Join via Zoom: https://brown.zoom.us/j/95275026350

    Please note, this seminar requires you to be logged into Zoom through your Brown account. Click to learn more .

    Abstract: The remarkable success of neural network models in machine learning has relied on the use of distributed representations — activity patterns that overlap across related inputs. Under what conditions does the brain also rely on distributed representations for learning? There are benefits and costs to this form of representation: it allows rapid, efficient learning and generalization, but is highly susceptible to interference. We recently developed a neural network model of the hippocampus that proposes that one subregion (CA1) may employ this form of representation, complementing known pattern-separated representations in other subregions. This provides an exciting domain to test ideas about learning with distributed representations, as the hippocampus learns much more quickly than the neocortical areas that have often been proposed to contain these representations. I will present modeling and empirical work that provide support for the idea that parts of the hippocampus do indeed learn using distributed representations. I will also present ideas about how hippocampal and neocortical areas may interact during sleep to further transform these representations over time.

    CCBS, Psychology & Cognitive Sciences, Research
  • Nowadays the technology to create videogames and impressive photorealistic scenes is for everyone to reach. Frameworks such as Unity 3D Engine are easy to understand and work with or without any coding experience. So Why not using it to visualize data? You will learn basics on game objects components, UI design and concepts of volume rendering. Just bring your laptop with Unity Engine installed.

    CCBS
  •  

    This workshop will provide a high-level overview of the main areas in machine learning with emphasis on supervised and unsupervised ML. We will review the strengths and limitations of ML, describe the bias-variance tradeoff which is one of the most important concepts in ML. Finally, we will review the main steps in a typical ML workflow and the most common problems to avoid.

    CCBS
  • Mar
    13

    GitHub Actions is a relatively new service by GitHub that allows you to run tests, deploy code, and more all from within your repo. This workshop will cover some of the basic use cases of GitHub Actions as well as show some of the more creative ways it can be used to automate your workflows. Attendees should be familiar with Git and GitHub.

     

    Instructor: Mary McGrath 

    CCBS
  • Mar
    6
    12:00pm

    DSCoV Workshop: Intro to PyTorch

    164 Angell Street

    Intro to PyTorch, by Minju Jung

     

    Nowadays, PyTorch is one of the most popular deep learning libraries. In this tutorial, I will cover the basic operations of PyTorch and building a neural network model for image classification. The basic knowledge of deep learning and coding experience with python are required.

    CCBS
  • Data Science Computation and Visualization Workshop

     

    EXPLORATORY DATA ANALYSIS WITH PANDAS IN PYTHON, PART TWO with Andras Zsom

    Exploratory data analysis (EDA) is the first step of any data science project. In the second part of this pandas tutorial, I’ll walk through various visualization types you can use to better understand the properties of your data at a glance using pandas. Coding experience with python is required but no experience with the pandas package is necessary to follow the tutorial.

     

    Friday 2/28 @ 12pm

    Carney Innovation Space, 4th Floor

    164 Angell Street

    Pizzas and sodas will be served. Sponsored by the Data Science Initiative and organized by the Center for Computation and Visualization.

    CCBS
  • Data Science Computation and Visualization Workshop

     

    EXPLORATORY DATA ANALYSIS WITH PANDAS IN PYTHON, PART ONE with Andras Zsom

     Exploratory data analysis (EDA) is the first step of any data science project. In the first part of this pandas tutorial, I’ll walk through how to read in csv, excel, and sql data into a pandas data frame, how to select specific rows and columns based on index or condition, and how to merge and append various data frames. Coding experience with python is required but no experience with the pandas package is necessary to follow the tutorial.

     

    Friday 2/14 @ 12pm

    Carney Innovation Space, 4th Floor

    164 Angell Street

    Pizzas and sodas will be served. Sponsored by the Data Science Initiative and organized by the Center for Computation and Visualization.

    CCBS
  • Nov
    22
    12:00pm

    DSCoV: DataLad

    164 Angell Street

    Data Science Computing and Visualization Workshop (DSCoV)

    Topic: DataLad
    Instructor: Yaroslav Halchenko


    DataLad provides a data portal and a versioning system for everyone, DataLad lets you have your data and control it too. For details, see https://www.datalad.org/ .

    Friday, November 22 , 12:00 PM
    164 Angell Street, 4th Floor Innovation Space
    Organized by CCV; Sponsored by DSI

    CCBS