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You need 36 total credits to graduate. Each course grants 3 credits and a thesis grants 6 credits.

Congratulations to Prof. Santosh Nagarakatte, who has received an unrestricted research gift from Intel Corporation. The gift, for an amount of $62,000, funds his research on developing correctly rounded math libraries in the RLIBM project. It will also enable the technology transfer of ideas and techniques from the RLIBM project to Intel's math libraries and prototypes.  Prof. Nagarakatte's papers on the RLIBM project have been previously recognized with the PLDI 2021 Distinguished Paper Award and the POPL 2022 Distinguished Paper Award. His Ph.D. student Jay Lim's dissertation on this topic was recognized with the 2022 ACM SIGPLAN John C Reynolds Outstanding Dissertation Award.  Congratulations to Prof. Santosh Nagarakatte and the members of the RLIBM project on this research gift!

Vision/Visualization/Graphics Concentration Details SubjectMathematical FoundationAlgorithmic FoundationTools/Syst for Massive DataKnowledge DiscoveryVisualization Required Courses: 6 Total: Stat581/501*(FoMath)A 512/513A  518(OS), 527/539 B 520/530(AI)B  526 Elective Courses:  508/509   550, 543  535, 536 523 Elective Courses:     546   534(Vision) Independent Studies: Up to three credits of Independent Studies (604, 605, 606). Course Table     UGrad Basic Core Advanced Non CS & Seminars M.S. Category A Algorithm   334 / 512 501 513 521 529 596 514 522 711 : 558 Complexity   452 / 508 509  538 540   Numerical 324 510       Statistics   954 : 581     960 : 563 960 : 565 960 : 588 M.S. Category B Arch     505 507   OS/DS   518  519 545   Networking     552 553 67x : Cloud Computing Cm/PL 415   515 516 67x  Parallel Prog Security   544   546 547 67x : Cryptography DB 336 527  539  541    AI   520 530 532 533 598   ML     535   543   550 536     Graphics 428   523   67x : Game Science Vision\InfoVis     534   526 580 332 : 561 332 : 562 332 : 570   Robotics     560 562  

Systems/Security Concentration Details SubjectMathematical FoundationAlgorithmic FoundationTools/Syst for Massive DataKnowledge DiscoveryVisualization Required Courses: 6 Total: 507(CA), 518(OS)B 512/513A  519(OS), 552(Networks)B 520/530(AI)B   Elective Courses:   514, 521(LP) 515(Compilers), 527/529(DB), 543(MDS), 544(Sec) 533(NLP) 523(Graphics), 526(DIVA) Elective Courses:     550(MDM), 67x(Smart Cities) 535/536(Pattern,ML), 560(CpRob) 534(Vision)  Independent Studies: Up to three credits of Independent Studies (604, 605, 606). Course Table     UGrad Basic Core Advanced Non CS & Seminars M.S. Category A Algorithm   334 / 512 501 513 521 529 596 514 522 711 : 558 Complexity   452 / 508 509  538 540   Numerical 324 510       Statistics   954 : 581     960 : 563 960 : 565 960 : 588 M.S. Category B Arch     505 507   OS/DS   518 519 545   Networking     552 553 67x : Cloud Computing Cm/PL 415   515 516 67x  Parallel Prog Security   544   546 547 67x : Cryptography DB 336 527   539   541   AI   520 530 532 533 598   ML     535   543   550 536     Graphics 428   523   67x : Game Science Vision\InfoVis     534   526 580 332 : 561 332 : 562 332 : 570   Robotics     560 562  

Robotics Learning Concentration Details SubjectMathematical FoundationAlgorithmic FoundationTools/Syst for Massive DataKnowledge DiscoveryVisualization Required Courses: 6 Total: 501*(FoMath), 560(CpRob)A,B 512/513A    520(AI,530)B 534(Vision)B  Elective Courses:  Robot Learning* (wip), 521(LP)/529(CpGeom), 522(CombOpt) 510(Num), 514(LP) 527(539 DB), 543(MDS) 535(Pattern)/536(ML), 533(NLP)/525(BrainCp) 523(Graphics), 526(DIVA) Elective Courses:   515  550(MDM), 672(Smart Cities) 672(Advanced AI)   Independent Studies: Up to three credits of Independent Studies (604, 605, 606). Course Table     UGrad Basic Core Advanced Non CS & Seminars M.S. Category A Algorithm   334 / 512 501 513 521 529 596 514 522 711 : 558 Complexity   452 / 508 509  538 540   Numerical 324 510       Statistics   954 : 581     960 : 563 960 : 565 960 : 588 M.S. Category B Arch     505 507   OS/DS   518  519 545   Networking     552 553 67x : Cloud Computing Cm/PL 415   515 516 67x  Parallel Prog Security   544   546 547 67x : Cryptography DB 336 527   539   541   AI   520 530 532 533 598   ML     535   543   550 536     Graphics 428   523   67x : Game Science Vision\InfoVis     534   526 580 332 : 561 332 : 562 332 : 570   Robotics     560 562  

AI/Machine Learning Concentration Details SubjectMathematical FoundationAlgorithmic FoundationTools/Syst for Massive DataKnowledge DiscoveryVisualization Required Courses: 6 Total: Stat581/501*(FoMath)A 512/513A  543(MDS)/550 A/(A,B) 520/530(AI), 535(Pattern), 536(ML)B   Elective Courses:   510(Num), 521(LP) 527/539(DB)   523(Graphics), 525(BrainCp), 526(DIVA) Elective Courses:   525(Comb. Opt)  67x(Smart Cities) 553(NLP), 67x(Advances in AI) 534(Vision), 560(CpRob) Independent Studies: Up to three credits of Independent Studies (604, 605, 606). Course Table     UGrad Basic Core Advanced Non CS & Seminars M.S. Category A Algorithm   334 / 512 501 513 521 529 596 514 522 711 : 558 Complexity   452 / 508 509  538 540   Numerical 324 510       Statistics   954 : 581     960 : 563 960 : 565 960 : 588 M.S. Category B Arch     505 507   OS/DS   518  519 545   Networking     552 553 67x : Cloud Computing Cm/PL 415   515 516 67x  Parallel Prog Security   544   546 547 67x : Cryptography DB 336 527   539   541   AI   520 530 532 533 598   ML     535   543   550 536     Graphics 428   523   67x : Game Science Vision\InfoVis     534   526 580 332 : 561 332 : 562 332 : 570   Robotics     560 562  

Massive Data Analytics Concentration Details SubjectMathematical FoundationAlgorithmic FoundationTools/Syst for Massive DataKnowledge DiscoveryVisualization Required Courses: 6 Total: 501*(FoMath), 512/513(Alg)A 512(Basic Alg) A 527/539(DB), 543(MDS) (Alg)B 550(MDM)B  526(DIVA)A Elective Courses: Stat697: Data Wrangling 521(LP/OPT)  539(DB) 520/530(AI) 523(Graphics) Elective Courses: Stat596: Regression Time Series 513/514(Adv.Alg)  546/547/544(Sec) 535/536(ML) 534(Vision) Independent Studies: Up to three credits of Independent Studies (604, 605, 606). Course Table     UGrad Basic Core Advanced Non CS & Seminars M.S. Category A Algorithm   334 / 512 501 513 521 529 596 514 522 711 : 558 Complexity   452 / 508 509 538 540   Numerical 324 510        Statistics   954 : 581     960 : 563 960 : 565 960 : 588 M.S. Category B Arch     505 507   OS/DS   518  519 545   Networking     552 553 67x : Cloud Computing Cm/PL 415   515 516 67x  Parallel Prog Security   544   546 547 67x : Cryptography DB 336 527   539   541   AI   520 330 532 533 598   ML     535   543   550 536     Graphics 428   523   67x : Game Science Vision\InfoVis     534   526 580 332 : 561 332 : 562 332 : 570   Robotics     560 562  

General CS Concentration Details SubjectMathematical FoundationAlgorithmic FoundationTools/Syst for Massive DataKnowledge DiscoveryVisualization Required Courses: 6 Total: 501*(FoMath), 512/513(Alg)A   507(CA), 518/519(OS), 515(Comp I)B 520/530(AI), 527/539(DB)B   Elective Courses: 509(FoCS), 510(Num), 514(Adv. Alg), 521(LP), 529(CpGeo)   516(Comp II), 552(Networks), 543(MDS) 533(NLP), 535/536(ML), 525(BrainCp) 523(Graphics), 526(DIVA) Elective Courses: 540(Complexity)   553(IntServ), 544(Sec) 550(MDM), 67x(Smart Cities), 67x(Advances in AI) 534(Vision), 560(CpRob) Independent Studies: Up to three credits of Independent Studies (604, 605, 606). Course Table     UGrad Basic Core Advanced Non CS & Seminars M.S. Category A Algorithm   334 / 512 501 513 512 529 596 514 522 711 : 558 Complexity   452 / 508 509 538 540   Numerical 324 510       Statistics   954 : 581     960 : 563 960 : 565 960 : 588 M.S. Category B Arch     505 507   OS/DS   518 519 545   Networking     552 553 67x : Cloud Computing Cm/PL 415   515 516 67x  Parallel Prog Security   514   546 547 67x : Cryptography DB 336 527 539 541   AI   520 530 532 533 598   ML     535 543 550 536   Graphics 428   523   67x : Game Science Vision\InfoVis     534 526 580 332 : 561 332 : 562 332 : 570   Robotics     560 562  

  M.S. Category A M.S Category B Approved M.S. Classes from Other Departments Algorithms & Complexity: *501, 508, 509, 510, 512, 513, 514, 521, 522, 529, 538, 540, 550 CS Foundational Topics: 596   Computer Architecture: 505, 507 Programming Languages: 515, 516 Systems/Networks: 518, 519, 545, 544, 546, 547, 552, 553 Data Storage and Retrieval: 527, 539, 541, 543, 550 AI/Machine Learning: 520, 525, 535, 536, 530, 532, 533, 598 Robotics: 560, *562 Visualization: 523, 526, 534, 580 CS Software Topics: 583 954 Statistics-Data Science: 581 (REQUIRED), 553, 554, 555, 563, 565, 576, 580, 582, 583, 586, 587, 588, 590, 591, 592, 593, 595, 596, 652, 653, 654, 681, 682, 690, 697, 668 642 Applied Mathematics: 516, 527, 528, 550, 551, 575, 577, 578, 581, 582, 583, 587, 588, 589, 591, 592, 611 125 Biomedical Engineering: 520, 526, 610, 620 185 Cognitive Sciences: 500 Electrical and Computer Engineering: 505, 506, 526 527, 529, 539, 542, 543, 544, 553, 560, 561, 562, 563, 564, 565, 566, 568, 570, 571, 574, 575, 576, 578, 579, 588 540 Industrial and Systems Engineering: 515, 525, 540, 575, 585, 685 625 Linguistics: 510, 511, 514, 520, 521, 524, 530, 531, 534 640 Mathematics: 551, 561, 566, 567, 569 711 Operations Research (RU Newark): 513, 553, 556, 558 730 Philosophy: 513, 550, 570, 575, 650, 670, 675, 676, 678, 679 830 Psychology: 514, 515, 535, 540, 546, 547, 550, 602, 611, 635, 637, 641 960 Statistics: 553, 554, 555, 563, 565, 576, 580, 581, 582, 583, 586, 587, 588, 590, 591, 592, 593, 595, 596, 652, 653, 654, 681, 682, 690, 697, 668 960 Statistics (MBA): 641

Two courses (6 credits) of M.S. Category A Two courses (6 credits) of M.S. Category B Two courses (6 credits) from either category A or category B Four courses (12 credits) from the list of courses acceptable for CS graduate credit, including courses from M.S. Categories A and B, acceptable undergrad courses, approved courses in other departments, CS seminars, and independent study. However, at most one of the four courses may be an independent study. A culminating sequence (6 credits) consisting of: Two additional courses from the union of M.S. Categories A and B, plus an M.S. essay approved according to the requirements of the School of Graduate Studies. 6 credits of M.S. Thesis research 704, 705, 706 plus an M.S. thesis defended successfully according to the requirements of the School of Graduate Studies. 6 credits of 601, 602 and successful completion of the Ph.D qualifying exam in Computer Science. (In this case, the Ph.D. qualifying paper will satisfy the writing requirement of the School of Graduate Studies).

Program Course Requirements: MSCS Students require 36 credits (12 courses) in total, and they must meet the following requirements: - Two from Category A - Two from Category B - Four additional courses from Category A OR Category B (M.S. Category A, and M.S. Category B). Note: Two of these additional courses must be from Category A OR Category B; the other two additional courses may be used for Essay Option (Category A or Category B) OR Thesis Option (704, 705, 706; 601, 602) - Four from the list of courses acceptable for MSCS credit: approved courses from other departments, additional Category A or B courses, CS Seminars, acceptable undergraduate courses, OR independent study. Note: at most two of the four courses may be independent study. Note: refer to the SGS and Global Policies below for online courses - Essay Option (A report from project-based MSCS courses or work approved as an essay) OR Thesis Option [equivalent to 2 courses (6 credits)]. Note: courses supporting the Essay or Thesis Options may also satisfy above requirements/conditions under "Four additional courses" Graduation Requirements: Students need to maintain a minimum of 3 GPA.. Student need to have no more than 2 Cs or lower. School of Graduate Studies Policies Rutgers Global Policies Essay/Thesis Requirements: In addition to the coursework requirements for the M.S. degree that are established by the School of Graduate Studies, the student must choose either the Essay Option or Thesis Option as described below. The essay or thesis must be written in English (except that some portion may require a computer language, with English documentation), it must be the student's own work, and it must demonstrate the student's facility for expository writing. Essay Option: The student must write and submit an expository paper in a field of computer science that was covered in the student's course work. It may be a paper written as part of a course in computer science, or it may be based on such a course. The essay "must" be appropriately formatted and contain: Title, Author(s), Abstract, and References. A paper that has previously been submitted for a course must have received a grade of B or higher. If the essay you're planning on submitting is a group assignment, you'll need to provide cover page(s) detailing your contributions to the project along with the rest of the project report. Corresponding presentation slides are required with all essay submissions. When relevant, a video and documentation or user's manual are recommended but not required. No extra credit is given for the preparation of the essay. The essay must be approved by a member of the Graduate Faculty of the Department of Computer Science followed by the M.S. Director. Thesis Option: The student must write a Master's Thesis and must register for exactly six credits of 198:704-706. Upon initial registration, the student is required to provide the MS Director with written confirmation from the faculty member agreeing to supervise their thesis. The Master's Thesis must be a written account of a critical and scholarly investigation in an area of computer science. It may represent: (a) a piece of independent research (extensions and improvements of work in a given part of the field are acceptable at a level of novelty which is less than that required for a doctoral thesis); (b) a work of synthesis that gives new significance and insight to previously-known results; or (c) an important constructive contribution to the development of a computer application. The thesis may not be a digest of known results from the literature, a summary of a published report, company classified or government classified material, or dependent for its background on other non-available reports. The thesis topic should be chosen by mutual agreement between the student and their faculty supervisor. The thesis must be approved by the student's thesis committee. The committee consists of the thesis supervisor and two other faculty members who are determined in consultation with the thesis supervisor. The advisor and members of the thesis committee must be members of the Graduate Faculty in Computer Science. In addition to submitting a copy of the completed Master's Thesis to the MS Director, the student is required to follow all thesis formatting, content, and submission guidelines from the School of Graduate Studies. Degree Completion Processing: [IMPORTANT: ALL INFORMATION AND INSTRUCTIONS FOR GRADUATION FORMS/MATERIALS ARE PROVIDED IN THE APPROPRIATE CANVAS MODULES FOR MSCS] There are several forms that must be filled out and submitted by the appropriate deadlines in order for the student who has fulfilled the above requirements to receive a Master's Degree. It is the student's responsibility that all necessary paperwork be completed on time. Information and forms can be obtained from the M.S. Administrative Assistant   Choose your own study plan >>>>

We suggest 6 study concentrations for students in the M.S. Program: General CS Massive Data Analytics AI/Machine Learning Robotics Systems/Security Vision/Visualization/Graphics     Choose your own study plan >>>>  

In addition to the general admission criteria of the Graduate School, the department requires that applicants to the M.S. program have completed an accredited undergraduate program in Computer Science, or at least taken the core prerequisite courses for the undergraduate degree as listed below: A substantial background in mathematics, especially in calculus (as in 640:151-152), linear algebra (as in 640:250), finite mathematics (as in 198:205), probability/combinatorics (as in 198:206), and numerical analysis (as in 198:323). Such background should include at least two semesters of calculus and one semester in each of the other areas. Working knowledge of high level languages (as in 198:111), data structures (as in 198:112), computer architecture and assembly language (as in 198:211), algorithm design and analysis (as in 198:344), and some elective courses in advanced undergraduate areas, such as programming languages and compilers (as in 198:314, 415), operating systems (as in 198:416), distributed systems (as in 198:417), information systems (as in 198:336), networks (as in 198:352), etc. (Short descriptions of undergraduate courses offered by the department can be found in Computer Science Undergraduate Course Synopses list.) All applicants are required to take the aptitude part of the GRE examination (verbal, analytic and mathematical reasoning sections). Criteria for admission currently include: An academic record (undergraduate and previous graduate work) that shows distinction (B+ or higher) in Computer Science, Mathematics and related fields. (The mean GPA for a recent entering class of students was 3.62; this included Master's students, with and without financial aid. ) High score on all the GRE examinations recommended, the TOEFL exam, or IELTS in the case of foreign students. (The average GRE scores for Fall 2020 incoming students were the following: Verbal 150, Quantitative 160; the mean TOEFL score was 92; the mean for IELTS was 7.0) Our MS and PhD programs require applicants to submit their GRE and TOEFL scores (or Duolingo) if these tests are available online or in person in their countries. Strong letters of recommendation (at least three). A clear statement, about one page in length, outlining the reasons why the applicant wishes to pursue graduate study in computer science. (If appropriate, please specify one or more areas of particular interest, to help us assign advisors. See section 5 for a list of areas.) The standards are higher for those awarded teaching assistantships or other forms of financial aid. More specific information for international applicants is available through the Office of Graduate and Professional Admissions. Link: Application link for M.S. Program Deferral Fees The Master of Science in Computer Science program has instituted admission confirmation deposits for incoming students starting with the Spring 2022. Our policy is based on similar deferral fees in other university departments. The rational for this decision is as follows: The number of qualified applicants the MSCS program receives each semester far exceeds the number of admits we can accommodate. Each year, a number of students tell us they will attend the program, but we find that roughly a quarter, if not more than that, do not enroll. This inflates our enrollment estimates and causes an issue when we request space for classrooms and coordinate faculty scheduling. The collection of student deposits counteracts this issue by working as a placeholder for these programs. The deposits are used as an incentive for students to actively enroll. Students are refunded by the department when they enroll, but refunds are not given if they do not. The department keeps the funds from students who do not enroll as revenue for future scholarships or the improvement of teaching aids for the MSCS program. Since the program has limited space, we are able to better track true enrollment numbers by admitting additional students when deposits are not received from those who verbally committed. To get more information on how to get a deferral please contact via the email the cs-ms-program office. The office will provide you with the fee collection details. Please note that this process does not directly affect student accounts or tuition. Students are responsible to pay tuition separate and apart from this process.

Start your application at the Graduate Admission website: Link: Application link for M.S. Program For the Spring semester: International, September 15th. MS applications only ; United States citizens as well as green card holders: October 15th. For the Fall semester: February 1st for International MS applicants; United States citizens and green card holders MS applicants: March 1st.

(cohorts beginning prior to Fall 2020) To complete the Master of Science in Computer Science degree, students must present 30 credits satisfying the requirements listed below, yielding at least a B average and include no more than two C grades. In addition to the coursework, a student must write and submit an Essay or Thesis according to the provided guidelines. Program Course Requirements:M.S. Students must complete 30 credits (10 courses) divided as follows: Two courses (6 credits) from category A with a grade of B or better Two courses (6 credits) from category B with a grade of B or better Four courses (12 credits) from the union of categories A and B a. For the thesis option the 704/705/706 credits can count as two of these four courses Two courses (6 credits) each of at least 3 credits that can include: a. Graduate CS courses and seminars b. Undergraduate courses that are accepted for graduate credit c. Approved courses in other departments Please note that NO Independent study credits (601/602) CAN count for the course requirement for MS students. Courses that are relevant to the graduate program in Computer Science may also be taken in the following Rutgers programs: Applied Mathematics, Biomedical Engineering, Cognitive Sciences, Electrical and Computer Engineering, Industrial and Systems Engineering, Linguistics, Mathematics, Operations Research, Philosophy, Psychology, and Statistics.   A list of approved courses from these departments.   Students may also take courses of special interest to them at Princeton University (Computer Science, Electrical Engineering, Philosophy), in accordance with a cooperative arrangement between Rutgers and Princeton. Students may register for internships/CPT using the zero-credit course 16:198:844 "Research Internship". Essay/Thesis Requirements: In addition to the coursework requirements for the M.S. degree that are established by the School of Graduate Studies, the student must choose either the Essay Option or Thesis Option as described below. The essay or thesis must be written in English (except that some portion may require a computer language, with English documentation), it must be the student's own work, and it must demonstrate the student's facility for expository writing. Essay Option: The student must write and submit an expository paper in a field of computer science that was covered in the student's course work. It may be a paper written as part of a course in computer science, or it may be based on such a course. The essay "must" be appropriately formatted and contain: Title, Author(s), Abstract, and References. A paper that has previously been submitted for a course must have received a grade of B or higher. A paper with multiple authors may only be submitted by one student with written permission of the co-authors. Corresponding presentation slides are required with all essay submissions. When relevant, a video and documentation or user's manual are recommended but not required. No extra credit is given for the preparation of the essay. The essay must be approved by a member of the Graduate Faculty of the Department of Computer Science followed by the M.S. Director. Thesis Option: The student must write a Master's Thesis and must register for exactly six credits of 198:704-706. Upon initial registration, the student is required to provide the M.S. Director with written confirmation from the faculty member agreeing to supervise their thesis. The Master's Thesis must be a written account of a critical and scholarly investigation in an area of computer science. It may represent: (a) a piece of independent research (extensions and improvements of work in a given part of the field are acceptable at a level of novelty which is less than that required for a doctoral thesis); (b) a work of synthesis that gives new significance and insight to previously-known results; or (c) an important constructive contribution to the development of a computer application. The thesis may not be a digest of known results from the literature, a summary of a published report, company classified or government classified material, or dependent for its background on other non-available reports. The thesis topic should be chosen by mutual agreement between the student and their faculty supervisor. The thesis must be approved by the student's thesis committee. The committee consists of the thesis supervisor and two other faculty members who are determined in consultation with the thesis supervisor. The advisor and members of the thesis committee must be members of the Graduate Faculty in Computer Science. In addition to submitting a copy of the completed Master's Thesis to the M.S. Director, the student is required to follow all thesis formatting, content, and submission guidelines from the School of Graduate Studies. Degree Completion Processing: There are several forms that must be filled out and submitted by the appropriate deadlines in order for the student who has fulfilled the above requirements to receive a Master's Degree. It is the student's responsibility that all necessary paperwork be completed on time. Information and forms can be obtained from the M.S. Administrative Assistant

Click here to visit the M.S. Portal website.

Professor Ulrich Kremer Computer Science Department Chair Professor Richard Martin Computer Science Associate Chair Professor Jie Gao Computer Science Graduate Program Director Professor Badri Nath Computer Science MS Program Director   Andrew Chun Computer MS Senior Academic Program Coordinator Jamie Liao Shared Spaces CSGSS Computer Science Graduate Student Society We strongly encourage your active participation in CSGSS

M.S. C.S. students are advised by a committee of academic advisors who hold regular office hours. Click to Schedule an appointment with an Advisor Upon entering the M.S. program students should contact a faculty advisor whose role is: Help the student design an overall study plan that satisfies the program requirements, based on their interests Be the person the student consults before registering each semester Students may change advisors as they become more familiar with the program (in particular if the Master's thesis option/essay option is chosen.)   Please contact  for more information.