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MIT Interdisciplinary Doctoral Program in Computational Science and Engineering

• CSE PhD Overview
• Dept-CSE PhD Overview
• CSE Doctoral Theses
• Program Overview and Curriculum
• For New CCSE Students
• Terms of Reference

MIT Interdisciplinary Doctoral Program in Computational Science and Engineering (Dept-CSE PhD)

• Dept-CSE PhD Program of Study Form   (version date 05Feb2024)
• Checklist for Dept-CSE PhD Students (version date 05Sep2023)

Dept-CSE PhD Participating Departments

The interdisciplinary doctoral program in Computational Science and Engineering ( CSE PhD + Engineering or Science ) at MIT allows enrolled students to specialize at the doctoral level in a computation-related field of their choice through focused coursework and a doctoral thesis. This program is offered through a number of participating departments, namely

• Civil and Environmental Engineering (Course 1) ,
• Mechanical Engineering (Course 2) ,
• Materials Science and Engineering (Course 3) ,
• Chemical Engineering (Course 10) ,
• Earth, Atmospheric and Planetary Sciences (Course 12) ,
• Aeronautics and Astronautics (Course 16) ,
• Mathematics (Course 18) ,
• Nuclear Science & Engineering (Course 22) .

Program Outline

Once admitted, doctoral degree candidates are expected to complete the host department’s degree requirements (including qualifying exam) with CSE deviations relating to coursework, thesis committee composition and thesis submission that are specific to the Dept-CSE program and are discussed in more detail below.

Academic Performance

Dept-CSE PhD students are required to complete at least five graduate-level subjects, totaling no less than 60 credit units, in computational science and engineering selected from the approved list of Computational Concentration Subjects . Dept-CSE PhD students may not use more than 12 units of credit from a “meets with undergraduate” subject to fulfill the CSE curriculum requirement. Subjects taken with the graduate P/D/F grading option, or subjects specifically designated as P/D/F in the MIT Bulletin, cannot be used to satisfy the Dept-CSE PhD curricular requirement of five graduate-level subjects, totaling no less than 60 credit units, in computational science and engineering*.

In addition to departmental academic performance expectations, Dept-CSE students are expected to maintain a grade point average (GPA) of at least 4.5 (out of 5) in CSE subjects and an overall GPA of at least 4.2 (out of 5) during the course of their studies.

*ChemE-CSE students are required to complete at least four subjects in computational science and engineering, in addition to 10.34, for a total of no less than 57 credit units.

Department of Civil and Environmental Engineering

A complete description of the doctoral program in Civil and Environmental Engineering can be found at https://cee.mit.edu/resources/ . Deviations associated with the CEE-CSE degree (“1.CSD”) are as follows.

Coursework Requirements

The CEE-CSE doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM degree can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by their thesis committee.

Thesis Committee Composition

The thesis committee composition requirements are identical to those of Course 1, with the additional requirement that that either the advisor be a CCSE member or the committee contain at least two CCSE members.

Thesis Submission

In addition to approval from the Chair of Course 1 Graduate Program Committee, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

Thesis Fields

Course 1 will award degrees under the thesis fields “Civil Engineering and Computation” and “Environmental Engineering and Computation.”

Department of Mechanical Engineering

A complete description of the doctoral program in Mechanical Engineering can be found at http://meche.mit.edu/academic/graduate . Deviations associated with the CSE degree are as follows. MechE-CSE PhD candidates (“2.CSD”) are expected to pass the ME qualifying exam in Computational Engineering (present thesis in computational engineering and take computational engineering subject exam).

The MechE-CSE doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM degree can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by their thesis committee.

The thesis committee composition requirements are identical to those of Course 2, with the additional requirement that  either the advisor be a CCSE member or the committee contain at least two CCSE members.

In addition to approval from the ME Graduate Officer, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

Thesis Field

Course 2 will award degrees under the thesis field “Mechanical Engineering and Computation.”

Department of Materials Science and Engineering

A complete description of the graduate program in the Department of Materials Science and Engineering (DMSE) can be found via https://dmse.mit.edu/graduate/programs . Deviations associated with the DMSE-CSE degree (“3.CSD”) are as follows.

The DMSE-CSE doctoral program of study consists of at least five graduate subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . The CSE five-course requirement can be satisfied through courses that simultaneously satisfy the DMSE core, post-core electives, and/or minor requirements. CSE subjects that a student may have applied towards a MIT SM degree may also be applied towards a DMSE-CSE doctoral major field of study requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by Thesis Committee.

The Thesis committee composition requirements are identical to those of DMSE, with the additional requirement that that either  the advisor be a CCSE member  or  the committee contain at least two CCSE members.

In addition to approval from the Chair of the Departmental Graduate Program Committee, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

DMSE will award degrees under the Thesis field “Computational Materials Science and Engineering”.

Department of Chemical Engineering

A complete description of the doctoral program in Chemical Engineering can be found at  http://web.mit.edu/cheme/academics/grad/advising.html#phdscd . Deviations associated with the ChemE-CSE degree are as follows.

ChemE-CSE students (“10.CSD”) are expected to complete the ChemE core curriculum with a CSE minor consisting of at least four graduate level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects .  The minor subjects shall not include 10.34, which is already part of the Chemical Engineering core curriculum. Subjects taken as part of an MIT SM program can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by the student’s thesis committee.

The thesis committee composition requirements are identical to those of Course 10, with the additional requirement that  either  the committee chair be a CCSE member  or  the committee contain at least two CCSE members.

Course 10 will award degrees under the thesis field “Chemical Engineering and Computation.”

Department of Earth, Atmospheric and Planetary Sciences

Once admitted, doctoral degree candidates are expected to complete the Course 12 degree requirements as outlined at https://eapsweb.mit.edu/academic-resources/grad-resources , except those relating to coursework in the Major Field of Study, Thesis Committee Composition and Thesis Submission that are specific to the EAPS-CSE program and are discussed in more detail below.

Degree candidates are expected to pass the qualifying exam in Course 12.

The EAPS-CSE (“12.CSD”) doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . The specific subjects will depend on the student’s thesis topic and background, and will be approved by the Thesis Committee. Subjects taken as part of an MIT SM program can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute.

The Thesis committee composition requirements are identical to those of Course 12, with the additional requirement that either the advisor be a CCSE member or the committee contain at least two CCSE members.

In addition to approval from the Examination Committee, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

Course 12 will award degrees under the Thesis field ” Computational Earth, Atmospheric and Planetary Sciences “.

Department of Aeronautics and Astronautics

A complete description of the doctoral program in Aeronautics and Astronautics can be found at http://aeroastro.mit.edu/graduate-program/doctoral-degree . Deviations associated with the AeroAstro-CSE degree are as follows. AeroAstro-CSE PhD candidates (“16.CSD”) are expected to pass the Aerospace Computational Engineering track qualifying exam in Course 16.

The AeroAstro-CSE doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM program can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by thesis committee.

The thesis committee composition requirements are identical to those of Course 16, with the additional requirement that either the advisor be a CCSE member or the committee contain at least two CCSE members.

Course 16 will award degrees under the thesis field “Computational Science and Engineering” to students matriculating in/before September 2023 and “Aerospace Engineering and Computational Science” for students matriculating after September 2023.

Department of Mathematics

A description of the plan of study for the Applied Mathematics option of the PhD degree in Course 18, can be found at http://math.mit.edu/academics/grad/timeline/plan.php . Deviations associated with the Math-CSE degree (“18.CSD”) are as follows.

The Math-CSE doctoral program of study consists of at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM degree can be counted toward this requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by the Chair of the Applied Mathematics Committee in the Mathematics department and CCSE.

The thesis committee composition requirements are identical to those of Course 18, with the additional requirement that either the advisor be a CCSE member or the committee contain at least two CCSE members.

Course 18 will award degrees under the Thesis field “Mathematics and Computational Science”.

Department of Nuclear Science & Engineering

NSE-CSE PhD candidates (“22.CSD”) must satisfy all NSE requirements for doctoral students, including passing the 22.15 module final exam with a satisfactory grade and completing an NSE Field of Specialization requirement. A complete description of the NSE doctoral program  and its requirements can be found at: http://web.mit.edu/nse/education/grad/phd.html .

Deviations associated with the NSE-CSE degree are as follows. The oral exam committee must include at least two CCSE-affiliated faculty members (one or both of whom may be NSE faculty members). The content of the oral exam must address some aspects related to computation.

In addition to satisfying a NSE Field of Specialization requirement, students pursuing the computation option must take at least five graduate-level subjects in computational science and engineering selected from the approved list of Computational Concentration Subjects . Subjects taken as part of an MIT SM program can be counted toward this requirement. Each of these subjects can be applied towards either the Advanced Subject requirement or the Minor requirement (but not both).  None of these subjects can count towards the Field of Specialization requirement. Doctoral candidates are normally expected to take their major subjects at the Institute. The specific subjects will depend on the student’s thesis topic and background, and will be approved by thesis committee.

The thesis committee composition requirements are identical to those of Course 22, with the additional requirement that either the advisor be a CCSE member or the committee contain at least two CCSE members (who may be NSE faculty members).

In addition to approval from the Chair, Department Committee on Graduate Students, the complete thesis needs to be submitted to and approved by CCSE. Students should provide a copy of the thesis title page to the CCSE academic administrator for review and approval prior to submitting the final thesis.

Course 22 will award degrees under the thesis fields “Nuclear Engineering and Computation” and “Computational Nuclear Science and Engineering”.  Student may choose either; the requirements are identical.

Doctoral candidates in general may petition to change the name appearing on their degree certificates. However, petitions from students in the CSE-participating departments listed above to include the keywords ‘computation’ or ‘computational’ in the degree name will only be approved if the student has satisfied requirements listed above. The PhD thesis field “Computational Science and Engineering” will be reserved for students graduating from the standalone CSE PhD program.

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Doctoral Programs in Computational Science and Engineering

Doctor of philosophy in computational science and engineering, program requirements.

Programs Offered by CCSE in Conjunction with Select Departments in the Schools of Engineering and Science

The interdisciplinary doctoral program in Computational Science and Engineering ( PhD in CSE + Engineering or Science ) offers students the opportunity to specialize at the doctoral level in a computation-related field of their choice via computationally-oriented coursework and a doctoral thesis with a disciplinary focus related to one of eight participating host departments, namely, Aeronautics and Astronautics; Chemical Engineering; Civil and Environmental Engineering; Earth, Atmospheric and Planetary Sciences; Materials Science and Engineering; Mathematics; Mechanical Engineering; or Nuclear Science and Engineering.

Doctoral thesis fields associated with each department are as follows:

• Aerospace Engineering and Computational Science
• Computational Science and Engineering (available only to students who matriculate in 2023–2024 or earlier)
• Chemical Engineering and Computation
• Civil Engineering and Computation
• Environmental Engineering and Computation
• Computational Materials Science and Engineering
• Mechanical Engineering and Computation
• Computational Nuclear Science and Engineering
• Nuclear Engineering and Computation
• Computational Earth, Science and Planetary Sciences
• Mathematics and Computational Science

As with the standalone CSE PhD program, the emphasis of thesis research activities is the development of new computational methods and/or the innovative application of state-of-the-art computational techniques to important problems in engineering and science. In contrast to the standalone PhD program, however, this research is expected to have a strong disciplinary component of interest to the host department.

The interdisciplinary CSE PhD program is administered jointly by CCSE and the host departments. Students must submit an application to the CSE PhD program, indicating the department in which they wish to be hosted. To gain admission, CSE program applicants must receive approval from both the host department graduate admission committee and the CSE graduate admission committee. See the website for more information about the application process, requirements, and relevant deadlines .

Once admitted, doctoral degree candidates are expected to complete the host department's degree requirements (including qualifying exam) with some deviations relating to coursework, thesis committee composition, and thesis submission that are specific to the CSE program and are discussed in more detail on the CSE website . The most notable coursework requirement associated with this CSE degree is a course of study comprising five graduate subjects in CSE (below).

Computational Concentration Subjects

Note: Students may not use more than 12 units of credit from a "meets with undergraduate" subject to fulfill the CSE curriculum requirements

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The PDF includes all information on this page and its related tabs. Subject (course) information includes any changes approved for the current academic year.

Computational Science and Engineering PhD

77 Massachusetts Avenue Building 35-434B Cambridge MA, 02139

617-253-3725 [email protected]

Website: Computational Science and Engineering PhD

Application Opens: September 15

Deadline: December 1 at 11:59 PM Eastern Time

Fee: $90.00

Note: Applicants interested in Computer Science must apply to through the Electrical Engineering and Computer Science PhD program .

Terms of Enrollment

Fall Term (September)

Standalone Program:

• Doctor of Philosophy (PhD) in Computational Science and Engineering

Joint Program:

• Doctor of Philosophy (PhD) in Civil Engineering and Computation
• Doctor of Philosophy (PhD) in Environmental Engineering and Computation
• Doctor of Philosophy (PhD) in Mechanical Engineering and Computation
• Doctor of Philosophy (PhD) in Computational Materials Science and Engineering
• Doctor of Philosophy (PhD) in Chemical Engineering and Computation
• Doctor of Philosophy (PhD) in Computational Earth, Atmospheric and Planetary Sciences
• Doctor of Philosophy (PhD) in Aerospace Engineering and Computational Science
• Doctor of Philosophy (PhD) in Mathematics and Computational Science
• Doctor of Philosophy (PhD) in Nuclear Engineering and Computation
• Doctor of Philosophy (PhD) in Computational Nuclear Science and Engineering

Affiliated Departments

• Aeronautics and Astronautics
• Chemical Engineering
• Civil and Environmental Engineering
• Earth, Atmospheric, and Planetary Studies
• Materials Science and Engineering
• Mathematics
• Mechanical Engineering
• Nuclear Science and Engineering

Standardized Tests

Graduate Record Examination (GRE)

• General test not required for Fall 2024 admission cycle
• Institute code: 3514
• Department code: 0000

International English Language Testing System (IELTS)

• Minimum score required: 7
• Electronic scores send to: MIT Graduate Admissions

TOEFL exam may be accepted in special cases. Waivers are not offered.

Financial Support

The CCSE PhD is an interdisciplinary program that collaborates with eight affiliated departments. As financial support may vary by department, CCSE graduate students are encouraged to contact their home department for more information.

Application Requirements

• Online application (including Subjects Taken section)
• Statement of objectives (limited to one page)
• Three letters of recommendation
• Transcripts
• English proficiency exam scores
• CV or resume
• GRE scores (not required for Fall 2023 admission cycle)

Special Instructions

The Computational Science and Engineering (CSE) PhD program allows students to specialize at the doctoral level in a computation-related field of their choice through focused coursework and a doctoral thesis. Applications from candidates who have a strong foundation in core disciplinary areas of mathematics, engineering, physics, or related fields are strongly encouraged.

Applicants interested in Computer Science: Please explore the offerings of the  Department of Electrical Engineering and Computer Science.

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• Office: 32-G738

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• (617) 253-6871
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• (617) 253-0454
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• (617) 253-4591
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• 617-253-4645
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• (617) 253-6022
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• [email protected]
• Office: 32-G666

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• (617) 253-5388
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Thomas D. and Virginia W. Cabot Professor, [CS and AI+D]

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• (617) 452-3402
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Daniel Jackson

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• (617) 258-8471
• Office: 32-G704

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• (617) 253-7149
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• (617) 258-6167
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• (617) 324-6027
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Aleksander Mądry

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Wojciech Matusik

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• (617) 324-8432

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• Office: 32-211

Anand V Natarajan

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• 408-910-4116

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• (617) 253-4177
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• (617) 253-4607
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Jonathan Ragan-Kelley

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• 801-913-0101
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Manish Raghavan

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• (617) 715-5368‬
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Srini Raghuraman

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Martin Rinard

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• (617) 258-6922
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Ronald Rivest

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• [email protected]
• (617) 253-5880
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Ronitt Rubinfeld

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• (617) 253-0884
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Daniela Rus

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• (617) 258-7567
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Daniel Sanchez

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• (617) 715-4886
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Arvind Satyanarayan

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• (617) 258-0697
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Julian Shun

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• (617) 258-0669
• Office: 32G-736

Armando Solar-Lezama

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• (617) 324-8356
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Justin Solomon

Associate Professor of EECS, [AI+D and CS]

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• (617) 324-6738
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Michael Stonebraker

Adjunct Professor of CS and Engineering, [CS]

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Gerald Sussman

Panasonic Professor, [CS and EE, AI+D]

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• (617) 253-5874
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Vivienne Sze

Professor, [EE and CS, AI+D]

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• 617.324.7352
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Peter Szolovits

Professor of Computer Science and Engineering; [AI+D and CS]

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• (617) 253-3476
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Vinod Vaikuntanathan

Ford Foundation Professor of Engineering, [CS and AI+D]

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• (617) 324-8444
• Office: 32-G696

Andrew Wang

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• Office: 38-648

Ryan Williams

Professor of EECS, [CS and AI+D]

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• Office: 32-G638

Virginia Vassilevska Williams

Professor, [CS and AI+D]

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• Office: 32-G640

Mengjia Yan

• [email protected]
• 617-258-0719
• Office: 32G-840

Nickolai Zeldovich

Joan and Irwin M. (1957) Jacobs Professor, [CS]

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• (617) 253-6005
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MIT senior Christine Soh integrates computer science and linguistics

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Christine Soh fell in love with MIT the summer before her senior year of high school while attending the Women’s Technology Program run by MIT’s Department of Electrical Engineering and Computer Science. That’s when she discovered that learning to program in Python is just like learning a new language — and Soh loves languages. Growing up in Colorado, Soh spoke both English and Korean; she learned French and Latin in school. This June, Soh will graduate from MIT, where she has happily combined her passions by majoring in computer science and engineering (Course 6-3) and linguistics (Course 24). She plans to begin working toward a PhD in linguistics next year. With fluency in both technical and humanistic modes of thinking, Soh exemplifies a "bilingual" perspective. "Dual competence is a good model for undergraduates at MIT," says engineer/historian David Mindell, who encourages MIT students to "master two fundamental ways of thinking about the world, one technical and one humanistic or social. Sometimes these two modes will be at odds with each other, which raises critical questions. Other times they will be synergistic and energizing."   The challenge of natural language and computation “The really cool thing about language is that it’s universal,” says Soh, who has added ancient Greek, Chinese, and the programming language Java to her credits since that summer. “I can have a really interesting conversation with anybody, even if they don’t have a linguistics background, because everyone has experience with language.” That said, natural language is difficult for computers to comprehend — something Soh finds fascinating. “It’s really interesting to think about how we understand language,” she says. “How is it that computers have such a hard time understanding what we find so easy?” Tools from computational linguistics to improve speech Pairing linguistics with computer science has allowed Soh to explore cutting-edge research combining the two disciplines. Thanks to MIT’s Advanced Undergraduate Research Opportunities Program, Soh got the chance to explore whether speech analysis software can be used as a tool for the clinical diagnosis of speech impairments.

“It’s very difficult to correctly diagnose a child because a speech impairment can be caused by a ton of different things,” says Soh. Working with the Speech Communication Group in MIT’s Research Laboratory of Electronics, Soh has been developing a tool that can listen to a child’s speech and extract linguistic information, such where in the mouth the sound was produced, thus identifying modifications from the proper formation of the word. “We can then use computational techniques to see if there are patterns to the modifications that have been made and see if these patterns can distinguish one underlying condition from another.” A natural leader

Even if the team isn’t able to find such patterns, Soh says the tool could be used by speech pathologists to learn more about what linguistic modifications a child might need to make to improve speech. In December, Soh presented a poster on this work at the annual meeting of the Acoustical Society of America and was honored with a first-place prize in her category (signal processing in acoustics). Exploring such real-world applications for computational linguistics helped inspire Soh to apply to doctoral programs in linguistics for next year. “I’ll be doing research that will be integrating computer science and linguistics,” she says, noting that possible applications of computational linguistics include working to improve speech-recognition software or to make machine-produced speech sound more natural. “I look forward to using the knowledge and skills I’ve learned at MIT in doing that research.” “Christine’s unique interests, energy, and deep interests in both linguistics and computer science should enable her to accomplish great things,” says Suzanne Flynn, a professor of linguistics who has had Soh as a student. “She is a natural leader.”   From field methods to neurolinguistics Looking back at her time at MIT, Soh recalls particularly enjoying two linguistics classes: 24.909 (Field Methods in Linguistics) which explores the structure of an unfamiliar language through direct work with a native speaker (in Soh’s year, the class centered on Wolof, which is spoken in Senegal, the Gambia, and Mauritania), and 24.906 (The Linguistic Study of Bilingualism). In the latter class, Soh says, “We looked at neurolinguistics, what’s happening in the brain as the bilingual brain developed. We looked at topics in sociolinguistics: In communities that are bilingual, like Quebec, what kind of impact does it have on society, such as how schools are run? … We got to see a spectrum of linguistics. It was really cool.” Building community at MIT Outside class, Soh says she found community at MIT through the Asian Christian Fellowship and the Society of Women Engineers (SWE), which she served last year as vice president of membership. “SWE has also been a really awesome community and has opened up opportunities for conversation about what it means to be a woman engineer,” she says. Interestingly, Soh almost didn’t apply to MIT at all, simply because her brother was already at the Institute. (Albert Soh ’18 is now a high school teacher of math and physics.) Fortunately, the Women’s Technology Program changed her mind, and as she nears graduation, Soh says, "MIT has been absolutely fantastic.”  

Story prepared by MIT SHASS Communications Editorial and Design Director: Emily Hiestand Senior Writer: Kathryn O'Neill  

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Five MIT PhD students named inaugural Amazon Fellows

Awarded by the Science Hub, the fellowship will provide support to pursue research in the fields of artificial intelligence and robotics.

Five MIT PhD students have been honored with Amazon fellowships to help pursue their research in the fields of artificial intelligence and robotics.

Awarded by the Science Hub , the students will receive funding to conduct independent research projects at MIT.

A collaboration between MIT and Amazon established in October 2021 , the Science Hub supports research, education, and outreach efforts in areas of mutual interest. Administered at MIT by the Schwarzman College of Computing, the hub aims to expand participation in AI, robotics, and other fields, and ensure the benefits of this research are shared broadly.

From equitable design to neuroscience, the inaugural recipients of the fellowship are investigating AI and robotics research across a multi-discipline of areas.

Robotics Fellows

Aparna Balagopalan is a PhD student in the Department of Electrical Engineering and Computer Science (EECS) in the Healthy ML group. Balagopalan’s research broadly focuses on developing fair, interpretable and robust models by carefully re-evaluating and surfacing assumptions in machine learning-based measurements in socially-relevant contexts.

Anastasia Ostrowski is a PhD student and design researcher at the MIT Media Lab in the Personal Robots Group. She completed her bachelor’s and master’s degrees in biomedical engineering from the University of Michigan with a focus on engineering design processes and idea generation. Currently, she is exploring how to support equitable design of robots through Design Justice, co-design, and participatory design approaches in the human-robot interaction field, working with roboticists, co-designers, and policy-makers.

Alexa Fellows

Ekin Akyürek is a PhD student studying artificial intelligence through natural language processing and machine learning, working with Jacob Andreas. Akyürek works to improve sequence models – workhorse of language processing and understanding. Despite the remarkable success of most enhanced versions of these models (e.g. GPT-3), they cannot always adapt to the new information the user provides without additional engineering and data collection efforts. His work aims to enable neural sequence models to generalize new tasks by just reading the new instructions given by the user and maybe a very few number of demonstrations.

Mycal Tucker is a PhD student in the Department of Aeronautics and Astronautics, working with Julie Shah, the H.N. Slater Professor of Aeronautics and Astronautics and head of the Interactive Robotics Group at CSAIL. Tucker focuses on explainability and interpretability of robotics and AI systems, or how complex computer and robotic systems can explain their policies and state to humans who have no special training. His research manifests itself as custom-built neural models, probes to understand the linguistic properties of natural language processing models, and representation learning for human understanding.

Greta Tuckute is a PhD student in the Department of Brain and Cognitive Sciences, working with Ev Fedorenko, an associate professor of neuroscience and an investigator with the McGovern Institute for Brain Research. Tuckute works at the intersection of neuroscience, artificial intelligence, and cognitive science. She is interested in understanding how language is processed in the human brain, how the representations learned by humans compare to those of artificial systems, and how we can leverage insights about the brain within the field of artificial intelligence.

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