Coaching Skills for Engineers 

Back by popular demand, we are offering our 3 session workshop this IAP. Don’t miss this chance to integrate coaching skills into your toolkit for success.

Open to all grad students

Based on asking open questions and keeping a curious mindset, coaching provides a practical framework for collaboration, mentoring, and communication. 

Over 3 sessions, this hands-on workshop will introduce you to the coaching mindset, reflective brainstorming, and strategies for adopting the coaching approach into your life. 

Come learn how to use the coaching approach to nurture meaningful relationships, develop creative solutions, and foster effective teamwork!

Lunch will be served during each session.

Session 1: Mon January 22, 10:30am-2pm

Session 2: Tue January 23, 10:30am-2pm

Session 3: Wed January 24, 10:30am-2pm

Location: 5-314

Register: https://mailchi.mp/mit/iap-2024-coaching-skills

Brought to you by the Grad Student Coaching Program

Sponsored by the Dept. of MechE, EECS, and the Riccio Graduate Engineering Leadership Program

This boot camp will introduce you to the fundamentals of deep learning. What are deep networks and how do they work? We will start by introducing the key data structures and algorithms used by neural nets. Then we will cover popular architectures that build upon these structures, including convolutional networks, residual networks, and transformers. We will look in detail at how these architectures have been applied to the field of computer vision, and we will also give examples of applications in other areas, such as natural language processing and scientific data analysis. The course will also include a hands on tutorial where you will run and code simple networks in Pytorch in your browser.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

Generative AI presents practical and societal challenges that are swiftly growing as the technology scales and is increasingly used. Generative models — some mimicking human capabilities — can be used alongside people to enhance project outcomes in domains from scientific discovery and education to industrial cases (i.e., material discovery, responsible AI, synthetic data, misinformation, and more). Focusing on the governance and regulatory angles, this workshop will convene scientists, technologists, administrators, industry professionals, and counsel to discuss mechanisms to oversee and guide the development of AI models developed in academia and academic-industry collaboration. In particular, three brainstorming sessions will explore mechanisms for developing responsible AI systems: data, the dataset used to define the models’ learning or the synthetic data generated; foundation models, their capabilities and colossal repository of information; and the impact of scaling models, from the growing number of parameters to democratizing miniaturized models and their increasing geographical and social impact.

Registration will open in early January.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

Artificial intelligence leveraging multiple data sources and input modalities (tabular data, computer vision, and natural language) is poised to become a viable method to deliver more accurate results and deployable pipelines across various applications. This session aims to review progress in a variety of applications, including healthcare, meteorology and education, and discuss future directions.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

Are you done with your experiment and wondering how in the world to analyze the mountain of data you generated? Is your advisor hating on your Excel-drawn plots? Join a bootcamp on data management and build a toolbox worthy of your science! We will include relational data management, data preparation, data cleaning, visualizations, parallelism, the basics of machine learning, and a lot of chances to try things out on your own and ask questions. Introductory (very basic, really) python knowledge assumed. Taught by students from the Data Systems Group at CSAIL.

Registration is now closed.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

The MIT authors of three recent books on design will talk about what design means in their domain, present examples of successful designs, and suggest prospects for the future of design in computing.

Design of Socio-Technical Systems
David Clark, Designing an Internet (MIT Press, 2018)

In this talk I will talk about the design principles of the Internet. I will describe how our understanding of system requirements evolved in the first decades, and how our changing understanding influenced the evolving design.  I will illustrate the space of system requirements and design options by looking at some alternative proposals for how to design an Internet, and the implications of some recent design proposals.

Design of Software Products
Daniel Jackson, The Essence of Software (Princeton University Press, 2021)

I’ll explain how successful innovations in software can usually be traced to just one or two “concepts” that offer new scenarios that, with seemingly small shifts, radically change how an application is used. I’ll give examples from apps such as Zoom, WhatsApp and Photoshop. I’ll also mention how viewing apps through concepts enables use of LLMs for code generation.

Design of Programs

Gerald Jay Sussman, Software Design for Flexibility (MIT Press, 2021)

It is hard to build systems that have acceptable behavior over a larger class of situations than was anticipated by their designers.  The best systems are evolvable: they can be adapted to new situations with only minor modification.  How can we design systems that are flexible in this way?

We have often programmed ourselves into corners and had to expend great effort refactoring code to escape from those corners.  We have now accumulated enough experience to feel that we can identify, isolate, and demonstrate strategies and techniques that we have found to be effective for building large systems that can be adapted for purposes that were not anticipated in the original design. I will illustrate such strategies with examples.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

Join MIT’s Center for Clinical and Translational Research (CCTR) and Prehealth Advising for the opportunity to explore the exciting world of clinical research and learn about the engaging studies our partner research labs are conducting in the CCTR’s facilities through interactive demos. From the exploration of biomarkers in chronic illnesses, to gait analyses for low-cost prosthetics designs, to Phase IV drug studies, the CCTR supports a wide variety of human subject study needs that we can’t wait to share with you.

The Motion Capture Suite & Device Workshop will include:

1. Interactive Demonstrations: Walk through all steps of running a study in the Motion Capture Suite, including calibration, participant prep and instrumentation, and data collection. Observe the real-time rapid-prototyping of a custom research device in the Device Workshop through 3D-scanning and 3D-printing.

https://cctr.mit.edu/what-we-offer/motion-capture-suite

https://cctr.mit.edu/what-we-offer/device-workshop

2. Informative Tour: Explore the Motion Capture Suite, Device Workshop, and other relevant spaces.

Who Should Attend: Students, researchers, and members of the MIT community interested in learning more about the clinical research capacities on MIT’s campus. Geared towards those wanting to explore and get involved in clinical research, including students considering pre-med, current medical or graduate students, and anyone interested in clinical research and translational healthcare technologies.

To register for this event, please email arosser@mit.edu, samyoung@mit.edu if you would like to attend.  

Availaibility is limited, and spaces will be filled on a first-come, first-serve basis

Contact Information: For inquiries, please contact Samantha Young (samyoung@mit.edu) or Akunna Rosser (arosser@mit.edu).

Are you done with your experiment and wondering how in the world to analyze the mountain of data you generated? Is your advisor hating on your Excel-drawn plots? Join a bootcamp on data management and build a toolbox worthy of your science! We will include relational data management, data preparation, data cleaning, visualizations, parallelism, the basics of machine learning, and a lot of chances to try things out on your own and ask questions. Introductory (very basic, really) python knowledge assumed. Taught by students from the Data Systems Group at CSAIL.

Registration is now closed.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

Coaching Skills for Engineers 

Back by popular demand, we are offering our 3 session workshop this IAP. Don’t miss this chance to integrate coaching skills into your toolkit for success.

Open to all grad students

Based on asking open questions and keeping a curious mindset, coaching provides a practical framework for collaboration, mentoring, and communication. 

Over 3 sessions, this hands-on workshop will introduce you to the coaching mindset, reflective brainstorming, and strategies for adopting the coaching approach into your life. 

Come learn how to use the coaching approach to nurture meaningful relationships, develop creative solutions, and foster effective teamwork!

Lunch will be served during each session.

Session 1: Mon January 22, 10:30am-2pm

Session 2: Tue January 23, 10:30am-2pm

Session 3: Wed January 24, 10:30am-2pm

Location: 5-314

Register: https://mailchi.mp/mit/iap-2024-coaching-skills

Brought to you by the Grad Student Coaching Program

Sponsored by the Dept. of MechE, EECS, and the Riccio Graduate Engineering Leadership Program

Generative AI presents practical and societal challenges that are swiftly growing as the technology scales and is increasingly used. Generative models — some mimicking human capabilities — can be used alongside people to enhance project outcomes in domains from scientific discovery and education to industrial cases (i.e., material discovery, responsible AI, synthetic data, misinformation, and more). Focusing on the governance and regulatory angles, this workshop will convene scientists, technologists, administrators, industry professionals, and counsel to discuss mechanisms to oversee and guide the development of AI models developed in academia and academic-industry collaboration. In particular, three brainstorming sessions will explore mechanisms for developing responsible AI systems: data, the dataset used to define the models’ learning or the synthetic data generated; foundation models, their capabilities and colossal repository of information; and the impact of scaling models, from the growing number of parameters to democratizing miniaturized models and their increasing geographical and social impact.

Registration will open in early January.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

The MIT authors of three recent books on design will talk about what design means in their domain, present examples of successful designs, and suggest prospects for the future of design in computing.

Design of Socio-Technical Systems
David Clark, Designing an Internet (MIT Press, 2018)

In this talk I will talk about the design principles of the Internet. I will describe how our understanding of system requirements evolved in the first decades, and how our changing understanding influenced the evolving design.  I will illustrate the space of system requirements and design options by looking at some alternative proposals for how to design an Internet, and the implications of some recent design proposals.

Design of Software Products
Daniel Jackson, The Essence of Software (Princeton University Press, 2021)

I’ll explain how successful innovations in software can usually be traced to just one or two “concepts” that offer new scenarios that, with seemingly small shifts, radically change how an application is used. I’ll give examples from apps such as Zoom, WhatsApp and Photoshop. I’ll also mention how viewing apps through concepts enables use of LLMs for code generation.

Design of Programs

Gerald Jay Sussman, Software Design for Flexibility (MIT Press, 2021)

It is hard to build systems that have acceptable behavior over a larger class of situations than was anticipated by their designers.  The best systems are evolvable: they can be adapted to new situations with only minor modification.  How can we design systems that are flexible in this way?

We have often programmed ourselves into corners and had to expend great effort refactoring code to escape from those corners.  We have now accumulated enough experience to feel that we can identify, isolate, and demonstrate strategies and techniques that we have found to be effective for building large systems that can be adapted for purposes that were not anticipated in the original design. I will illustrate such strategies with examples.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

This boot camp will introduce you to the fundamentals of deep learning. What are deep networks and how do they work? We will start by introducing the key data structures and algorithms used by neural nets. Then we will cover popular architectures that build upon these structures, including convolutional networks, residual networks, and transformers. We will look in detail at how these architectures have been applied to the field of computer vision, and we will also give examples of applications in other areas, such as natural language processing and scientific data analysis. The course will also include a hands on tutorial where you will run and code simple networks in Pytorch in your browser.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.

Join MIT’s Center for Clinical and Translational Research (CCTR) and Prehealth Advising for the opportunity to explore the exciting world of clinical research and learn about the engaging studies our partner research labs are conducting in the CCTR’s facilities through interactive demos. From the exploration of biomarkers in chronic illnesses, to gait analyses for low-cost prosthetics designs, to Phase IV drug studies, the CCTR supports a wide variety of human subject study needs that we can’t wait to share with you.

The Motion Capture Suite & Device Workshop will include:

1. Interactive Demonstrations: Walk through all steps of running a study in the Motion Capture Suite, including calibration, participant prep and instrumentation, and data collection. Observe the real-time rapid-prototyping of a custom research device in the Device Workshop through 3D-scanning and 3D-printing.

https://cctr.mit.edu/what-we-offer/motion-capture-suite

https://cctr.mit.edu/what-we-offer/device-workshop

2. Informative Tour: Explore the Motion Capture Suite, Device Workshop, and other relevant spaces.

Who Should Attend: Students, researchers, and members of the MIT community interested in learning more about the clinical research capacities on MIT’s campus. Geared towards those wanting to explore and get involved in clinical research, including students considering pre-med, current medical or graduate students, and anyone interested in clinical research and translational healthcare technologies.

To register for this event, please email arosser@mit.edu, samyoung@mit.edu if you would like to attend.  

Availaibility is limited, and spaces will be filled on a first-come, first-serve basis

Contact Information: For inquiries, please contact Samantha Young (samyoung@mit.edu) or Akunna Rosser (arosser@mit.edu).

Artificial intelligence leveraging multiple data sources and input modalities (tabular data, computer vision, and natural language) is poised to become a viable method to deliver more accurate results and deployable pipelines across various applications. This session aims to review progress in a variety of applications, including healthcare, meteorology and education, and discuss future directions.

Part of the Expanding Horizons in Computing IAP series presented by the MIT Schwarzman College of Computing. See the full list of activities at computing.mit.edu/ExpandingHorizons.