Joining ALFA

 

Rene Reyes Kate Xu Krittamate "Boom" Tiankanon Nicole Hoffman Robert Gold Erik Hemberg Shashank Srikant Una-May O'Reilly Jaeyoon Kim Jamal Toutouh Bryn Reinstadler Alexandra Dima Chathika Gunaratne Tamara Mitrovska

 

Diversity Drives Innovation and Learning

At the Anyscale Learning For All (ALFA) Group, we mean Anyscale Learning for ALL. ALFA is dedicated to cultivating an inclusive culture that supports, promotes, and empowers diverse voices in Computer Science & AI. Our focus is to improve and build machine learning, AI, and data analytics technology that works for everyone.

Representation matters.

We want our research to be representative of everyone who benefits and learns from it. We value people with different experiences, perspectives, and backgrounds - it’s the cornerstone of our approach to learning and research. We celebrate diversity along many axes: race, religion, ethnicity, age, sex, national origin, sexual orientation, gender identity, gender expression, genetic disposition, neurodiversity, disability, veteran status and any other aspect which makes you unique.

 

Contents

MIT Students

 

Join from ouside MIT

 

Short Term Visits

Please note, due to the ongoing situation with COVID-19, MIT has suspended all short term visit appointments until further notice.
This includes remote research.

 

 


MIT STUDENTS


 
 

M.Eng & UROPs

Contact alfa-apply (@) csail.mit.edu to apply
Include:  project of interest by name, relevant courses and grades, relevant experience, expected year of graduation, and CV.
 

 

Synthesizing Software with AI and Formal Program Synthesis Methods

As software proliferates and the need for it explodes, what methods contribute to improving our ability to write and repurpose code? To what extent can software be automatically engineered? Is it possible to describe a task to a software development tool instead of how to implement it? What if an existing code base was the starting point? To what extent is it possible to repurpose it? What tools, formalisms, training data, method hybridizations, and inventions are necessary or helpful? You will learn how we are combining an AI-based approach based on stochastic search heuristics with formal program synthesis methods in the context of these questions. You will contribute to a project with a goal to generate correct software based on a “what is needed” specification.

Prerequisites: 6.009 Fundamentals of Programming, 6.031 Elements of Software Construction, 6.033 Computer Systems Engineering

 

Left of Boom: Sniffing Out Cyber Attacks

In the increasingly adversarial setting of cyberspace, cyber defenders need to be active when protecting their cyber assets. Our question is whether it is possible to figure out what an adversary may be planning in terms of attacking and how we should react and the dynamic of both sides reacting to each other. Our approach will draw upon AI and machine learning.

Prerequisites: Rising Junior, Senior, and MEng

 

CICADA: Coevolutionary Intelligent COAs for Adversarial Decisions against Allies

This project unites game design and intelligent game agents. Our agents are Red and Blue Forces and our framework will allow them to engage in combat. They will be programmed to adaptive maneuver in tactical, strategic and operational ways.

 

COVID-19

Help us with modeling pedestrian movement patterns and signage placement inside buildings to understand the contacts that could result in COVID contagion. Analyze the resulting contact networks as social graphs and inform classical epidemiology compartment SEIR modeling. The outcomes indicate how what we do and how we do it alters COVID spread.

 

Real-time Modeling of Network Activity in the Developing Brain

Understanding how brain cells form functional networks during early life is key to understanding information processing in the developing brain and how this processing is disrupted in neurodevelopmental disorders. The communication between brain cells can be observed in real-time by neuroscientists using two-photon calcium imaging and/or microelectrode arrays. Yet the time necessary for analyzing these large datasets can limit our ability to study network development over time using existing methods. We use machine learning to accelerate this analysis pipeline and to enhance both the signal extraction and feature selection. Multiple opportunities exist for students to apply their interests in machine learning and (real!) neural networks into our analysis pipeline.

 

 


Opportunities to Join from Outside MIT


 

 

Become a PhD Student with ALFA!

  • Funded PhD student research assistantship
  • In machine learning for cybersecurity
  • Location: Massachusetts Institute of Technology
  • Deadline for PhD program application: Mid December
  • Start Date: Fall

See: Grad admissions website for more specific information

We have an opening for a top class PhD student  interested in understanding the adversarial behavior that drives the security arms race between cyber attacks and defenses. This research is focused on Artificial Intelligence (including Machine/Deep Learning) and Mod/Sim  (modeling and simulation)  techniques.  One of our projects, named RIVALS , is focused on extreme DDOS attacks and DDOS-resilient peer to peer networks. Others consider the effectiveness of network enclaves, deception and malware detection. We are supported by the USA Defense Advanced Research Project Agency and the MIT CSAIL Cybersecurity Initiative.
 
Applicants must apply through MIT’s graduate program admissions process for the Department of Electrical Engineering and Computer Science. The admission application deadline is in mid-December. Mention interest in these topics and studying under Dr. O'Reilly in your application (e.g. statement of purpose,)  See  https://www.eecs.mit.edu/academics-admissions/graduate-program/admissions for study starting in September.

For informal inquiries, email alfa-apply (@) csail.mit.edu

 

Postdoc Opportunities

Potential postdocs should contact Una-May O'Reilly through alfa-apply (@) csail.mit.edu It is very important when you contact us to clearly and concisely identify areas of mutual interest and provide information about your background. Having a face to face relationship with a member of ALFA in the group is very helpful.

The group has rotating funding for a modest number of post doctoral associate positions. Others are welcome if they can earn funding from other sources such as research foundations in their own country. Examples are NSERCs in Canada, NSFs from the USA, etc. In these situations, a letter of support may be required during your application process. That can be provided should the project match well with ALFA. In other situations, postdocs apply after they have a scholarship. Be aware that postdoc fellowships that are funded outside MIT are usually (but not always) subject to extra CSAIL specific fees to cover visa processing and/or resources usage which implies either Dr. O'Reilly must cover these costs or your scholarship should. Having an award in hand does not guarantee an invitation to join. We have limited resources and require mutual interests.

 

Short Term Visits

Please note, due to the ongoing situation with COVID-19, MIT has suspended all short term visit appointments until further notice.
This includes remote research.

 

Students

On very rare occasions, outside thesis work can be conducted over a short visit. Note that for these visits, the visitor must cover costs including MIT visiting student fees, CSAIL specific fees to cover visa processing and resources usage, travel to MIT, local accommodations and travel. Most students are funded by their home institution or scholarship for the visit. The cost of a visit depends on the length of stay and time of year, and does not include accommodations and local travel. International students must meet the financial requirements for a visa.

Generally, you must be willing to work on a project of mutual interest, with our software libraries and infrastructure.

Contact alfa-apply (@) csail.mit.edu to apply and for more information

 

Faculty Visitors

We welcome visits from our colleagues in academia. We are most interested in visitors whose research agenda closely aligns with our own or whom we have personally met through conferences, workshop and related travel. Note that visitor fees are not usually imposed upon short term faculty visits.

On very selective occasions, outside thesis work can be conducted over a short visit. Note that for these visits, the visitor must cover costs including CSAIL specific fees to cover visa processing and resources usage, travel to MIT, local accommodations and travel. Generally you must be willing to work on a project of mutual interest, with our software libraries and infrastructure.

Contact alfa-apply (@) csail.mit.edu to apply and for more information

 

 

Unfortunately we don't always have the time to reply to every unsolicited request.
Please don't be offended, we just don't have enough time.

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