Beaver Works

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AI Challenges
Jan/05 Wed 10:00AM–12:00PM
Jan/12 Wed 10:00AM–12:00PM
Jan/19 Wed 10:00AM–12:00PM
Jan/26 Wed 10:00AM–12:00PM

This will be a project-based IAP course that aims to develop new AI for a series of problems. Students will work closely with MIT faculty/staff in small teams and will be provided with data, project ideas, and computing resources. There will be numerous opportunities for successful and interested students to continue their research with ongoing research projects after the IAP course through UROPs, theses projects, etc.

email vijayg@ll.mit.edu if you are interested in attending this course.

AI challenges such as ImageNet, CIFAR, Graph Challenge, Moments in Time have resulted in major advances in image recognition, graph processing, and video action recognition. These and many other challenge problems are characterized by: 1) open datasets, 2) clear problem statements and 3) baseline implementations. Inspired by these challenges, through the USAF-MIT AI Accelerator, we are developing challenge problems to bring AI innovations to domains such as:

1) Datacenter Monitoring: Develop AI that can detect failures and workload characteristics in an operational datacenter
2) Reinforcement Learning Applications: Develop AI for aerial vehicles for games and novel environments
3) Magnetic Navigation: Develop AI for aerial vehicles for navigation in GPS denied environments by leveraging novel ML techniques alongside physical modelling.
4) Flight Maneuvers: Develop AI to detect good and bad flight paths from a flight simulator.

This will be a project-based IAP course and our team will provide significant guidance to students in developing AI capabilities for the above domains. Students will work closely with MIT faculty/staff in small teams and will be provided with data, project ideas, and computing resources. There will be numerous opportunities for successful and interested students to continue their research with ongoing research projects after the IAP course through UROPs, theses projects, etc.

 

Hands on Full Duplex Radio - IAP
Jan/25 Tue 01:00PM–03:00PM
Jan/26 Wed 01:00PM–03:00PM
Jan/27 Thu 01:00PM–03:00PM

Design, build and test your own full-duplex radio with real-world hardware/software engineering!

 

Full-duplex technology is revolutionizing the wireless world! This system concept is fundamentally different that traditional radios that divide transmission and reception in either time and/or frequency. Future networks will leverage this emerging technology to improve efficiency and enhance mobile user experiences. This course will introduce students to the various self-interference cancellation techniques that enable full-duplex operation in wireless systems and will allow them to create their own full-duplex radios through hands-on engineering with real-world hardware/software.

Email Ken Kolodziej to register for the class.

Hands on Holography IAP
Jan/19 Wed 09:00AM–12:00PM
Jan/21 Fri 09:00AM–12:00PM
Jan/24 Mon 09:00AM–12:00PM
Jan/26 Wed 09:00AM–12:00PM
Jan/28 Fri 09:00AM–12:00PM

This course will explore the fascinating applications of holography. What is holography? It is not merely art; holography encompasses a variety of measurement and recording techniques at the intersection of wave-propagated interference and diffraction. Consequently, it enjoys utility and relevance across physics domains, from low radio frequencies through optical wavelengths, to X-ray and beyond. This course will demystify holography by covering fundamental theory coupled with hands on laboratory sessions. During the laboratory sessions students will create their own computer generated holograms and a traditional optical hologram to take home.  

Email: gregory.balonek@ll.mit.edu for information on how to register.

Introduction to Defense Contracts
Jan/11 Tue 02:00PM–04:00PM

The Department of Defense is the largest customer in the world, spending approximately $500 billion in contracts every year.  It is also one of the most complex with unique laws, regulations, and policies that can be daunting for companies to navigate.  Learn what the Department of Defense needs, the legal framework in which the military buys technology and services, and important considerations for businesses.  If you are designing your startup's business model, looking to expand your market, curious about government contracts, or fascinated about how a toilet seat can cost $10,000, this class is for you.

This class is offered twice. Please sign up for only one session.

Email abowne@mit.edu to register

To attend go to: https://mit.zoom.us/j/7817098838

Introduction to Defense Contracts
Jan/14 Fri 02:00PM–04:30PM

The Department of Defense is the largest customer in the world, spending approximately $500 billion in contracts every year.  It is also one of the most complex with unique laws, regulations, and policies that can be daunting for companies to navigate.  Learn what the Department of Defense needs, the legal framework in which the military buys technology and services, and important considerations for businesses.  If you are designing your startup's business model, looking to expand your market, curious about government contracts, or fascinated about how a toilet seat can cost $10,000, this class is for you.

This class is offered twice. Please sign up for only one session.

Email abowne@mit.edu to register

To attend go to: https://mit.zoom.us/j/7817098838

Mathematics of Big Data & Machine Learning
Jan/04 Tue 10:00AM–11:55AM
Jan/10 Mon 05:00PM–06:00PM
Jan/11 Tue 10:00AM–11:55AM
Jan/14 Fri 05:00PM–06:00PM
Jan/18 Tue 10:00AM–11:55AM
Jan/24 Mon 05:00PM–06:00PM
Jan/25 Tue 10:00AM–11:55AM

Enrollment: Limited: Advance sign-up required Limited to 35 participants

Attendance: Participants must attend all sessions

Prereq: Matrix Mathematics

Big Data describes a new era in the digital age where the volume, velocity, and variety of data created across a wide range of fields is increasing at a rate well beyond our ability to analyze the data.  Machine Learning has emerged as a powerful tool for transforming this data into usable information.  Many technologies (e.g., spreadsheets, databases, graphs, matrices, deep neural networks, ...) have been developed to address these challenges.  The common theme amongst these technologies is the need to store and operate on data as tabular collections instead of as individual data elements.  This class describes the common mathematical foundation of these tabular collections (associative arrays) that apply across a wide range of applications and technologies.  Associative arrays unify and simplify Big Data and Machine Learning.  Understanding these mathematical foundations allows the student to see past the differences that lie on the surface of Big Data and Machine Learning applications and technologies and leverage their core mathematical similarities to solve the hardest Big Data and Machine Learning challenges.

This interactive course will involve significant interactive student participation and a small amount of homework.   Those students who fully participate and complete the homework will receive a certificate of completion.

The MIT Press book "Mathematics of Big Data" that will be used throughout the course will be provided.

E-mail the instructor to sign up.

 

Instructors:

Jeremy Kepner - Fellow & Head MIT Supercomputing Center - kepner@ll.mit.edu

Hayden Jananthan - Post Doc MIT Supercomputing Center - hayden.jananthan@ll.mit.edu

Signup Deadline: Dec 15

Dates:

Jan 04 Tue 10:00AM-11:55AM Virtual Course Intro and Chapter 1

Jan 10 Mon 05:00PM-06:00PM Virtual Chapters 2 & 4 Team Prep

Jan 11 Tue 10:00AM-11:55AM Virtual Chapters 2 & 4

Jan 14 Fri 05:00PM-06:00PM Virtual Chapters 5 & 6 Team Prep

Jan 18 Tue 10:00AM-11:55AM Virtual Chapters 5 & 6

Jan 24 Mon 05:00PM-06:00PM Virtual Chapters 7 & 8 Team Prep

Jan 25 Tue 10:00AM-11:55AM Virtual Chapters 7 & 8

Practical High Performance Computing: Scaling Beyond your Laptop
Jan/11 Tue 09:00AM–12:00PM
Jan/13 Thu 09:00AM–12:00PM
Jan/18 Tue 09:00AM–12:00PM
Jan/20 Thu 09:00AM–12:00PM

The focus of this workshop is to introduce the role of High Performance Computing in research. Learn how to scale your application to run on HPC Systems available to the MIT Community.

Description
The focus of this workshop is to introduce the role of High Performance Computing (HPC, aka supercomputing) in research. We will discuss the fields where HPC is used and provide concrete examples where we describe the strategies used to scale applications to hundreds of processors. Students will learn when to scale from their laptops to HPC, what challenges that introduces, and how to address those challenges with efficient HPC workflows. The MIT SuperCloud will be used for hands-on examples using C/C++, Julia, Matlab, and/or Python. We will also demonstrate applications using other computing resources on campus, such as the Satori and Engaging clusters. Students should bring an existing research problem/application that they would like to scale as a project.

This is a blended course with asynchronous and live components. Much of the lecture will be available before class in pre-recorded short videos and class time will be spent on hands-on activities and student research project work. Students taking the class for MIT credit are required to complete a short report on their project.

Students looking to take this class for credit should sign up for 12.091/12.S593. Those interested in taking the class not for credit can send email to lauren.milechin@mit.edu.

Prerequisites
Working knowledge of one programming/scripting language. Laptop for hands-on exercises. Participants will get further instruction on how to access MIT Supercloud once registered for the class. Students should bring an existing research problem/application that they would like to scale as a project.

Software Radio
Jan/10 Mon 01:00PM–04:00PM
Jan/12 Wed 01:00PM–04:00PM
Jan/19 Wed 01:00PM–04:00PM
Jan/24 Mon 01:00PM–04:00PM

Learn about software defined radio using GNU Radio during this interactive course.

Software-defined radio (SDR) technology is having a tremendous impact not only in consumer devices but also in the areas of rapid prototyping and research and development. MIT Lincoln Laboratory is offering a course to introduce students to SDR fundamentals and applications. Students will gain hands-on experience with the USRP SDR platform and GNU Radio toolkit, while learning theory and practice of digital signal processing and digital communications. The course will consist of several projects, such as FM radio receivers, digital video transmission and reception, and spectrum sensing, highlighting the flexibility of software radios.

Gain hands-on experience with popular software radio platforms (USRP, HackRF, RTL-SDR,…)
• Learn theory and practice of digital signal processing and digital communications
• Projects include
– FM radio receiver
– Automatic Dependent Surveillance-Broadcast (ADS-B) receiver
– Spectrum sensing / signal detection
– GPS receiver
– Digital modulation