The LTI's degree programs draw from a common set of courses and core skills, but emphasize different types of expertise that prepare you for a wide range of career options. All of our programs provide the hands-on experience and rigorous curriculum that are the hallmark of computer science at Carnegie Mellon.

Ph.D. Programs

Ph.D. in Language and Information Technology

The Ph.D. in LTI focuses on developing the next generation of scientific and entrepreneurial leaders. The first two years of the Ph.D. program are similar to our MLT program. After the second year, you will spend most of your time working closely with your faculty advisor on research that advances the state-of-the-art in computer science.

Ph.D. students are expected to publish papers about original research in the most competitive scientific journals and international conference proceedings, and to present their research at conferences and workshops. Most of our Ph.D. graduates become professors and research scientists, while a few have started their own companies.

In general, students pursuing a Ph.D. in Language and Information Technologies must

  • Pass at least 96 units of graduate-level courses.
  • Satisfy proficiencies in writing, presentation, programming and teaching; and
  • Propose, write and defend a Ph.D. dissertation (thesis).

Students must also attend the LTI Colloquium each semester and satisfy our Research Speaking Requirement.

For a detailed breakdown of the above requirements, download and read the Ph.D. Handbook.

In order to obtain your Ph.D. in Language and Information Technologies, you need to pass 96 units (generally, eight courses) of graduate courses that fulfill these requirements:

  • At least 72 units of LTI courses: Must include one class in each LTI focus area.
  • At least 24 units of SCS courses.
  • At least two lab courses in two different research areas.

Here's a sample of what your five-year schedule might look like.

 

Fall

Spring

Summer

Year 1

Grammars and Lexicons

Algorithms for NLP

Directed Study

Search Engines or Machine Learning for Text Mining

Machine Translation

Directed Study

Required Research

Year 2

Software Engineering for LT (I)

Speech Understanding

Self-Paced Lab

Directed Study

Software Engineering for LT (II)

Self-Paced Lab

Directed Study

Required Research

Year 3

Directed Research

Directed Research

Directed Research

Year 4

Directed Research

Directed Research

Directed Research

Year 5

Directed Research

Directed Research

Directed Research

Carnegie Mellon's School of Computer Science has a centralized online application process. Applications and all supporting documentation for fall admission to any of the LTI's graduate programs must be received by December 15. Incomplete applications will not be considered.

Important Deadlines

Applications are due by noon (12 p.m.) on December 15.

Costs

  • By noon (12 p.m. EST) Dec. 3: $75 for one program, $50 each additional program.
  • From 12:01 p.m. (EST) Dec. 3 to noon (12 p.m.) Dec. 15: $125 for one program, $75 for each additional program.

Requirements

The School of Computer Science requires the following for all Ph.D. applications.

  • GRE scores: These must be less than five years old. The GRE Subject Test is not required, but is recommended. Our Institution Code is 2074; Department Code is 0402.
  • TOEFL scores: Required if English is not your native language. No exceptions. These scores may be more than two years old if you have pursued or are pursuing a bachelor's or graduate degree in the United States. (While the TOEFL is preferred, the IELTS test may also be submitted.) Successful applicants will have a minimum TOEFL score of 100. Our Institution Code is 4256; the Department Code is 78.
  • Official transcripts from each university you have attended, regardless of whether you received your degree there.
  • Current resume.
  • Statement of Purpose.
  • Three letters of recommendation.

For more details on these requirements, please see the SCS Doctoral Admissions page.

In addition to the SCS guidelines, the LTI requires:

  • A short (1-3 minute) video of yourself. Tell us about you and why you want to come to CMU. This is not a required part of the application process, but it's strongly suggested.
  • Any outside funding you are receiving must be accompanied by an official award letter.

No incomplete applications will be eligible for consideration.

For a complete breakdown of the Ph.D. program and its policies, including information about internships, please view the Ph.D Handbook »

For more information about the Ph.D. program, contact Stacey Young.

Dual-Degree Ph.D. in Language and Information Technologies (Portugal Partnership)

The LTI offers a dual-degree Ph.D. in Language and Information Technologies in cooperation with the Instituto Superior Técnico at the Universidade Tecnica de Lisboa. Students jointly enrolled in the LTI Ph.D program spend a year in Lisbon, then two years at Carnegie Mellon taking classes in linguistics, computer science, statistical learning and task orientation.

After completing the majority of their academic requirements, students return to Portugal for the next two years to conduct extensive research, ultimately leading to a dissertation topic that will be publicly defended. One adviser from each institution co-supervises their student’s progress and helps to define their final thesis topic.

Students participating in the dual-degree program will spend their first year in Portugal, followed by two years in Pittsburgh to complete their coursework. They will complete a maximum of eight courses with a proper balance of focus areas (linguistics, computer science, statistical/learning and task orientation). After that, they will return to Portugal for their last two years, pursuing research and completing their dissertation. For more, see the Carnegie Mellon | Portugal page.

While in the dual Ph.D. program, your schedule may look like this.

 

Fall

Spring

Summer

Year 1
(In Portugal)

Classes and Directed Study

Classes and Directed Study

Required Research

Year 2
(In Pittsburgh)

Grammar and Lexicon

Structured Prediction

Directed Study

Language and Statistics

2 Self-Paced Labs

Directed Study

Required Research

Year 3
(In Pittsburgh)

Directed Research

Directed Research

Directed Research

Year 4
(In Portugal)

Directed Research

Directed Research

Directed Research

Year 5
(In Portugal)

Directed Research

Directed Research

Directed Research

Students applying to the dual degree program must apply through Carnegie Mellon's online application. In addition to the requirements listed below, prospective students must also contact both Isabel Trancoso and LTI_Portugal_Admissions@cs.cmu.edu when applying.

Carnegie Mellon's School of Computer Science has a centralized online application process. Applications and all supporting documentation for fall admission to any of the LTI's graduate programs must be received by December 15. Incomplete applications will not be considered.

Important Deadlines

Applications are due by noon (12 p.m.) on December 15.

Costs

  • By noon (12 p.m. EST) Dec. 3: $75 for one program, $50 each additional program.
  • From 12:01 p.m. (EST) Dec. 3 to noon (12 p.m.) Dec. 15: $125 for one program, $75 for each additional program.

Requirements

The School of Computer Science requires the following for all Ph.D. applications.

  • GRE scores: These must be less than five years old. The GRE Subject Test is not required, but is recommended. Our Institution Code is 2074; Department Code is 0402.
  • TOEFL scores: Required if English is not your native language. No exceptions. These scores may be more than two years old if you have pursued or are pursuing a bachelor's or graduate degree in the United States. (While the TOEFL is preferred, the IELTS test may also be submitted.) Successful applicants will have a minimum TOEFL score of 100. Our Institution Code is 4256; the Department Code is 78.
  • Official transcripts from each university you have attended, regardless of whether you received your degree there.
  • Current resume.
  • Statement of Purpose.
  • Three letters of recommendation.

For more details on these requirements, please see the SCS Doctoral Admissions page.

In addition to the SCS guidelines, the LTI requires:

  • A short (1-3 minute) video of yourself. Tell us about you and why you want to come to CMU. This is not a required part of the application process, but it's strongly suggested.
  • Any outside funding you are receiving must be accompanied by an official award letter.

No incomplete applications will be eligible for consideration.

Master's Programs

Master of Language Technologies

The MLT program prepares students for a research career in academia or industry. In this program, you’ll be immersed in research for two full years. During the academic year, your time will be evenly split between taking courses and doing research with your faculty advisor. Your summer will be devoted entirely to research. Many MLT grads continue on to Ph.D. programs at CMU and other top institutions, while others pursue careers at companies emphasizing research and rapid innovation.

The MLT program lasts two years (24 months), and students must complete two summers of research. Students should usually expect to graduate in August of their second year.

MLT students take 120 or more course units (about 10 courses), at least 72 of which are LTI courses, and 24 of which are School of Computer Science (SCS) courses. Most of these are 12-unit courses, although lab courses are typically 6 units. Our courses generally assume knowledge of programming and data structures. The remaining units may also be taken from the LTI, or with approval from the faculty advisor, any other senior- or graduate-level course offered at CMU or Pitt.

Directed research is another integral part of the MLT program; MLT students carry out directed research during their studies, with guidance from their faculty advisors.

Students may also choose to complete an optional MLT thesis. Guidelines can be found in the MLT Handbook.

Here's an example of how your two years in the MLT program may break down.

 

Fall

Spring

Summer

Year 1

Grammars and Lexicons

Algorithms for NLP

Directed Study

Search Engines or Machine Learning for Text Mining

Machine Translation

Self-Paced Lab

Directed Study

Required Research

 

Year 2

Software Engineering for LT (I)

Speech Understanding

Self-Paced Lab

Directed Study

Software Engineering for LT (II)

Directed Study

Elective

Required Research

 

Carnegie Mellon's School of Computer Science has a centralized online application process. Applications and all supporting documentation for fall admission to any of the LTI's graduate programs must be received by December 15. Incomplete applications will not be considered.

Important Deadlines

Applications are due by noon (12 p.m.) on December 15.

Costs

  • By noon (12 p.m. EST) Dec. 3: $75 for one program, $50 each additional program.
  • From 12:01 p.m. (EST) Dec. 3 to noon (12 p.m.) Dec. 15: $125 for one program, $75 for each additional program.

Requirements

The School of Computer Science requires the following for all Ph.D. applications.

  • GRE scores: These must be less than five years old. The GRE Subject Test is not required, but is recommended. Our Institution Code is 2074; Department Code is 0402.
  • TOEFL scores: Required if English is not your native language. No exceptions. These scores may be more than two years old if you have pursued or are pursuing a bachelor's or graduate degree in the United States. (While the TOEFL is preferred, the IELTS test may also be submitted.) Successful applicants will have a minimum TOEFL score of 100. Our Institution Code is 4256; the Department Code is 78.
  • Official transcripts from each university you have attended, regardless of whether you received your degree there.
  • Current resume.
  • Statement of Purpose.
  • Three letters of recommendation.

For more details on these requirements, please see the SCS Master's Admissions page.

In addition to the SCS guidelines, the LTI requires:

  • A short (1-3 minute) video of yourself. Tell us about you and why you want to come to CMU. This is not a required part of the application process, but it's strongly suggested.
  • Any outside funding you are receiving must be accompanied by an official award letter.

No incomplete applications will be eligible for consideration.

For a complete breakdown of the MLT program and its policies, including information about internships, please view the MLT Handbook»

For more information about the MLT program, contact Stacey Young.

Master of Science in Intelligent Information Systems (MIIS)

The MIIS degree focuses on recognizing and extracting meaning from text, spoken language and video. As an MIIS student, you’ll receive the department’s deepest exposure to content analysis and machine learning. In addition to completing the program’s coursework, you’ll work on directed study projects with your faculty advisor for two semesters; participate in a summer internship; and collaborate with your peers on a semester-long, group-oriented capstone project. This combination of classroom instruction, professional experience, and using new skills in significant projects with world-class colleagues will help prepare you for a successful career in industry or government. Our alumni have gone on to exciting careers at places like Apple, IBM and Google, and most have job offers within six weeks of graduation. Read more about our alumni on our intranet page.

The Intelligent Information Systems degree offers students the flexibility to create their own course of study in consultation with their advisor. Students must take at least 84 units (typically seven courses) of qualifying and elective courses that satisfy human language, machine learning, and language technology applications breadth requirements.

MIIS students gain three types of practical experience: 24 units of software development supervised by their advisor (equivalent to two courses); a one-semester internship (which can be waived for students that have sufficient prior professional experience); and a 42-unit capstone project done with classmates. This combination of working closely with CMU faculty, professional experience and group-oriented work with peers helps MIIS students broaden their skills quickly.

A typical MIIS student completes the program in four semesters (fall through fall, with a summer internship), but it can be completed in three if an internship is not required.

Part-time and distance education options are available in some cases. Students interested in these options should discuss them with the program director before they apply.

For a full list of requirements, read the MIIS Handbook.

Here are some example schedules for completing the MIIS program.

Example Course of Study #1

This schedule would satisfy course requirements for a student interested in text mining, text analytics and question-answering systems.

Fall 1

Spring

Summer

Fall 2

Machine Learning

Search Engines

Design and Engineering of Intelligent Systems\ Directed Study

Language and Statistics

Natural Language Processing

Question Answering

Directed Study

MIIS Capstone Planning Seminar

Internship

Machine Learning for Text Mining

MIIS Capstone Project

Example Course of Study #2

This schedule would satisfy course requirements for a student interested in voice-based computer applications.

Fall 1

Spring

Summer

Fall 2

Machine Learning

Algorithms for NLP

Speech Recognition and Understanding

Directed Study

Applied Machine Learning

Competitive Engineering

Design and Implementation of Speech Recognition Systems

Directed Study

MIIS Capstone Planning Seminar

Internship

Conversational Interfaces

MIIS Capstone Project

Example Course of Study #3

This example would satisfy course requirements for a student interested in text mining, text analytics and question-answering systems who has petitioned to have the summer internship waived.

Fall 1

Spring

Summer

Search Engines

Analysis of Social Media

Design and Engineering of Intelligent Systems

Directed Study

Machine Learning

Natural Language Processing

Question Answering

Directed Study

MIIS Capstone Planning Seminar

Academic Research Practices and Scientific Communities

MIIS Capstone Project

For a complete breakdown of curriculum and requirements, read the MIIS Handbook.

Carnegie Mellon's School of Computer Science has a centralized online application process. Applications and all supporting documentation for fall admission to any of the LTI's graduate programs must be received by December 15. Incomplete applications will not be considered.

Important Deadlines

Applications are due by noon (12 p.m.) on December 15.

Costs

  • By noon (12 p.m. EST) Dec. 3: $75 for one program, $50 each additional program.
  • From 12:01 p.m. (EST) Dec. 3 to noon (12 p.m.) Dec. 15: $125 for one program, $75 for each additional program.

Requirements

The School of Computer Science requires the following for all Ph.D. applications.

  • GRE scores: These must be less than five years old. The GRE Subject Test is not required, but is recommended. Our Institution Code is 2074; Department Code is 0402.
  • TOEFL scores: Required if English is not your native language. No exceptions. These scores may be more than two years old if you have pursued or are pursuing a bachelor's or graduate degree in the United States. (While the TOEFL is preferred, the IELTS test may also be submitted.) Successful applicants will have a minimum TOEFL score of 100. Our Institution Code is 4256; the Department Code is 78.
  • Official transcripts from each university you have attended, regardless of whether you received your degree there.
  • Current resume.
  • Statement of Purpose.
  • Three letters of recommendation.

For more details on these requirements, please see the SCS Master's Admissions page.

In addition to the SCS guidelines, the LTI requires:

  • A short (1-3 minute) video of yourself. Tell us about you and why you want to come to CMU. This is not a required part of the application process, but it's strongly suggested.
  • Any outside funding you are receiving must be accompanied by an official award letter.

No incomplete applications will be eligible for consideration.

For a complete breakdown of the MIIS program and its policies, including information about internships, please view the MIIS Handbook»

Master of Computational Data Science (MCDS)

The MCDS degree focuses on engineering and deploying large-scale information systems. Our comprehensive curriculum equips you with the skills and knowledge to develop the layers of technology involved in the next generation of massive information system deployments and analyze the data these systems generate. When you graduate, you’ll have a unified vision of these systems from your core courses; internship experience; and semester-long, group-oriented capstone project. MCDS graduates are sought-after software engineers, data scientists and project managers at leading information technology, software services and social media companies.

The MCDS program offers two majors: Systems and Analytics. Both require the same total number of course credits, split among required core courses, electives, data science seminar and capstone courses specifically defined for each track. The degree can also be earned in four different ways, depending on the length of time you spend working on it. Regardless of the timing option, all MCDS students must complete a minimum of 144 units to graduate.

Here are the options.

  • Part-Time Timing — a degree of variable time, usually entailing several years.
  • Short Timing — a 12-month degree consisting of fall, spring and summer semesters of study. Each semester comprises a minimum of 48 units. This timing is limited to students who have several previous internships. Students graduate in August.
  • Medium Timing — a 16-month degree consisting of study for fall and spring semesters, a summer internship, and fall semester of study. Each semester comprises a minimum of 48 units. This timing is typical for most students. Students graduate in December.
  • Long Timing — a 20-month degree consisting of study for fall and spring semesters, a summer internship, and a second year of fall and spring study. Each semester comprises a minimum of 36 units. Students graduate in May.

For a complete overview of the MCDS requirements, visit the MCDS website or read the MCDS Handbook».

To earn an MCDS degree, student must pass courses in the core curriculum, the MCDS seminar, a concentration area and electives. Students must also complete a capstone project in which they work on a research project at CMU or on an industry-sponsored project.

In total, students must complete 144 eligible units of study, including eight 12-unit courses, two 12-unit seminar courses and one 24-unit capstone course. Students must choose at minimum five core courses. The remainder of the 12-unit courses with course numbers 600 or greater can be electives chosen from the SCS course catalog. Any additional non-prerequisite units taken beyond the 144 units are also considered electives.

MCDS students must also pass the undergraduate course 15-513 Introduction to Computer Systems (6 units), typically in the summer before their program commences. The student must pass with a grade of B- or better. Failure to pass the course means that the student takes 15-213 during either the fall or spring semester. Note that in both cases the units do not count toward the 144 eligible units of study.

Some example courses of study are included below.

Example 1: Analytics Major, 16 Months

Fall

Spring

Summer

Year 1

Data Science Seminar

Machine Learning

Machine Learning for Text Mining

Advanced Machine Learning

Design and Engineering of Intelligent Information Systems

Big Data Analytics

Data Science Seminar

Capstone Planning Seminar

Machine Learning with Big Data Sets

Cloud Computing

Information Systems Project

Search Engines

Multimedia Databases and Data Mining

Large Scale Multimedia Analysis

Summer Internship

Year 2

Data Science Analytics Capstone

 

 

Example 2: Systems Major, 16 Months

Fall

Spring

Summer

 Year 1

Computational Data Science Seminar

Advanced Storage Systems

Cloud Computing

Distributed Systems

Machine Learning

Computational Data Science Seminar

Parallel Computer Architecture and Programming

Advanced Databases

Search Engines

Summer Internship

 Year 2

Computational Data Science Systems Capstone

 

 

Operating Systems or Web Applications

Carnegie Mellon's School of Computer Science has a centralized online application process. Applications and all supporting documentation for fall admission to any of the LTI's graduate programs must be received by December 15. Incomplete applications will not be considered.

Important Deadlines

Applications are due by noon (12 p.m.) on December 15.

Costs

  • By noon (12 p.m. EST) Dec. 3: $75 for one program, $50 each additional program.
  • From 12:01 p.m. (EST) Dec. 3 to noon (12 p.m.) Dec. 15: $125 for one program, $75 for each additional program.

Requirements

The School of Computer Science requires the following for all Ph.D. applications.

  • GRE scores: These must be less than five years old. The GRE Subject Test is not required, but is recommended. Our Institution Code is 2074; Department Code is 0402.
  • TOEFL scores: Required if English is not your native language. No exceptions. These scores may be more than two years old if you have pursued or are pursuing a bachelor's or graduate degree in the United States. (While the TOEFL is preferred, the IELTS test may also be submitted.) Successful applicants will have a minimum TOEFL score of 100. Our Institution Code is 4256; the Department Code is 78.
  • Official transcripts from each university you have attended, regardless of whether you received your degree there.
  • Current resume.
  • Statement of Purpose.
  • Three letters of recommendation.

For more details on these requirements, please see the SCS Master's Admissions page.

In addition to the SCS guidelines, the LTI requires:

  • Any outside funding you are receiving must be accompanied by an official award letter.

No incomplete applications will be eligible for consideration.

For a complete breakdown of the MCDS program and its policies, including information about internships, please view the MCDS Handbook»

Master of Science in Biotechnology Innovation and Computation (MSBIC)

The MSBIC degree, offered jointly by the Language Technologies Institute and the Computational Biology Department, educates students in using software and computing technologies to create innovative solutions for the bioscience industries. In this program, you'll apply techniques from areas like machine learning, big data analytics, data mining and information retrieval to solve important problems in biotechnology, the pharmaceutical industry and health care. Because these industries are evolving rapidly, there is a great demand for students who can envision, design, plan and deliver solutions that integrate emerging technologies into effective business solutions. To that end, our program also emphasizes entrepreneurship, and you'll be required to identify opportunities, develop solutions, and create a minimum viable product. Our graduates have gone on to become software developers, data scientists and software engineers in the software, manufacturing or bio-science industries. Several have created their own startups..

Incoming students generally hold undergraduate degrees in computer science, software engineering, bioinformatics or bioengineering. To receive the M.S. degree, all students must take and successfully complete at least 192 units of coursework. All required core courses must be completed with a grade of B or better. Completing the program typically requires a full two years with a capstone project during the last semester.

For full requirements and program details, read the MSBIC Handbook».

The MSBIC degree generally takes four semesters — three semesters of coursework and one semester devoted to the capstone project.

Here's an example of how your coursework might break down.

Semester One

Semester Two

Semester Three

Semester Four

New Technologies and Future Markets

Mathematical Foundations for Data Science

Algorithms and Advanced Data Structures

Fundamentals of Biotechnology

Competitive Engineering

Machine Learning

Big Data Systems in Practice

Software Methods in Biotechnology and Life Science

 

Biotechnology Enterprise Development

Automation of Biological Research

Big Data Analytics

Search Engines

Capstone Project

(48 units)

Applications to the MSBIC program are accepted beginning November 15 and must be submitted by April 1. Your application must include the following.

  • A cumulative grade point average higher than 3.5.
  • Graduate Record Examination (GRE) scores: We require minimum GRE scores of 160 verbal reasoning and 165 quantitative reasoning. These scores must be less than five years old. Send your scores to the School of Computer Science, Carnegie Mellon University; Institute Code: 2074, Department Code: 0402.
  • Scores from the Test of English as a Foreign Language (TOEFL). (For Non-English speaking students) Send your scores directly to Carnegie Mellon University - School of Computer Science; Institutional Code: 4256; Departmental Code: 78. . These scores must be less than two years old. Because English proficiency has a great impact on your success in the program, your TOEFL score should be greater than 100, (with no sub-score less than 22). We also accept scores from the International English Language Testing System (IELTS). Your IELTS score must be at least 7.5.
  • Current resume.
  • Three letters of recommendation.
  • Statement of Purpose. Type or neatly print a concise one- or two-page statement in this format:
    • Part I: Briefly state your objective in pursuing a professional graduate degree in MSBIC. Tell us if you have a particular reason for applying to this degree program.
    • Part II: Describe your background in fields particularly relevant to your objective. List here any relevant academic, industrial or commercial experience.
    • Part III: Include any additional information you wish to supply to the Admissions Committee.
  • Transcripts from all undergraduate and graduate institutions attended.

Please ensure that the GRE and TOEFL scores reach us before the application deadline. No application will be considered complete until we have received these scores. Incomplete applications will not be considered for admission.

Send any off-line material to:

Kathleen Schaich
Administrative / Programming Coordinator
Language Technologies Institute
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213

For a complete breakdown of the MSBIC program and its policies, including information about internships, please view the MSBIC Handbook»

Undergraduate Programs

Undergraduate Minor in Language Technologies

Human language technologies have become an increasingly central component of computer science. Information retrieval, machine translation and speech technology are used daily by the general public, while text mining, natural language processing and language-based tutoring are common within more specialized professional or educational environments. The LTI prepares students for this world by offering a minor that gives you the opportunity to not only learn about language technologies, but to also apply that knowledge through a directed project.

Students interested in the language technologies minor must complete our prerequisite courses with an average grade of B (3.0) or better before applying to the program. (Students who do not meet this average must submit a letter of explanation along with their application.) Prerequisites include:

  • Principles of Imperative Computation (15-122)
  • Functional Programming (15-150)

We also strongly encourage candidates to take

  • Matrix Algebra (21-241) or Linear Algebra (21-341)
  • Probability Theory and Random Processes (36-217)

Students enrolled in the LTI's undergraduate minor are required to take a core course that provides a general introduction to language technologies, with an emphasis on natural language processing (NLP). They also engage in directed research with a faculty member, and can mix and match electives to develop in-depth experience in several specific language technologies.

Course Requirements for Undergraduate Minor

Core Course

Electives (Choose Three)

Project

Grammars & Lexicons (Fall)

Speech Processing (Fall)

Natural Language Processing (Spring)

Search Engines and Web Mining (Fall)

Algorithms for NLP (Fall) Machine Translation (Spring)

Information Retrieval (Spring)

Speech Recognition (Fall)

Speech II (Spring)

Language & Statistics (Spring)

The Nature of Language (Fall)

Linguistic Analysis (Spring)

A semester-long directed research project (Fall or Spring)

Students interested in earning a minor in language technologies must apply for admission no later than September 30 of their senior year. An admission decision will usually be made within one month. Students may petition the LTI undergraduate program director to be admitted to the minor earlier or later in their undergraduate careers. To apply, contact the program's director, Alan Black.

For more information on the undergraduate minor, contact Alan Black.