Degree Programs

CSA offers two research programs, Ph.D. and MTech (Research), and two course-based MTech programs.

Note: The M.Sc. (Engg.) and M.E programs have been renamed M.Tech (Research) and M.Tech respectively effective academic year 2016-17.

Our degree programs provide a solid foundation in core and emerging areas of computer science and trains students to become independent researchers. A comprehensive description of the degree requirements is available in our information brochure (pdf format).

For the more information on guidelines one can refer to Institute Student Information Handbook 2019-20 available in the section “Current Students” here.

 

The duration of the Ph.D. program is usually 4-5 years. The students are expected to be self-motivated and should be able to work well in teams as well as individually.

First term

1. Getting acquainted with the people, facilities in CSA specifically and IISc in general.
2. Selection of courses: The courses you select depend on your intended area of research. It is compulsory that you should select at least one mathematics or mathematically-oriented course. A Direct Ph.D. student after finishing their B.E./B.Tech. should gain at least 24 credits (which may mean usually 6-8 courses) to complete their Research Training Programme (RTP) whereas a Ph.D. student who already has a Masters degree needs to gain only 12 credits (i.e. 3-4 courses). Students are usually advised to take a maximum of 4 courses in the first semester.
3. Selection of research area and guide: Take help from Departmental Curriculum Committee (DCC), faculty and senior research students in the department in this regard. A special DCC meeting will be arranged for this purpose shortly after the semester starts.
4. Work hard to complete your RTP with good grades.

Second Term

1. Take any advanced course useful for your research if required or suggested by your advisor.
2. Select the research problem(s) and start working on the same.
3. Start doing a literature survey in your area of research.

Third term

1. Deliver a ‘Perspective Seminar’, a comprehensive survey of your area of work from the standpoint of the specific problem under investigation.
2. Start concrete work on solving your research problem.
3. A Ph.D. student has to pass the comprehensive examination. You may appear for the comprehensive examination either in the third semester or in the fourth semester (before the end of two years), depending on the progress in your research work and in consultation with your advisor. In the comprehensive examination, the candidate is first expected to give a brief presentation of his/her research work. This is followed by questions on the syllabus for the RTP undergone by the student.
4. Writing of research paper/technical reports, etc.

Fourth Term

1. Complete the comprehensive examination if you haven’t already completed it.
2. Continue with your research work.
3. Write more research papers.

Fifth term onwards

1. Complete the remaining work to conclude your research.
2. Once you have enough results, start writing your thesis. (You may want to consult your advisor regarding when to start writing your thesis.)
3. Colloquium, Thesis defense, etc.

Math Requirement Courses

Direct PhD students may credit any one of the following courses to satisfy the Math course requirement:
1. Courses in Pool A for the M. Tech. 2019-2021 batch
2. E0 226 : Linear Algebra and Probability
3. E0 299 : Computational Linear Algebra
4. E1 222 : Stochastic Models and Applications
5. E2 202 : Random Processes
5. MA 219 : Linear Algebra
6. MA 221 : Analysis I
7. MA 261 : Probability Models
8. Any other course with the approval of DCC, CSA

Faculty Advisor

While we are sure that all of you have the inherent motivation and abilities to get through the Programme with flying colours, we believe a little extra guidance from us will go a long way in smoothing out your adjustment to a new academic environment and in enhancing your academic performance. Your primary source of academic guidance and counseling is the faculty advisor assigned to you. You should make it a point to get to know your advisor well, and meet your advisor frequently in the early part of your stay here, and especially whenever you face any problems. The distinction between students and faculty is more blurred: you will find faculty willing to deal with you on a more equal level, to listen to and value ideas from you that might be contradictory to their current knowledge and viewpoints, etc.

Another person who can help you will be the TA (Teaching Assistant) for each course. The TA is likely to be a student just one year senior to you; occasionally, the TA can be someone from your batch who has done the course a semester before you! This is because graduate studies are also meant to teach you things such as honest and critical evaluation of work done by peers.

Student Advisor

There will also be a student advisor assigned to each student. He/She is someone with whom you can interact closely in a friendly and informal way to help yourself acclimatize to the environment here. Apart from the Faculty Advisor, the Student Advisor is another avenue for helping you in adjusting with the environment in the CSA department and the IISc campus in general.

The M.Tech. (Research) research program is a 1 to 2.5 year program. The students are expected to be self-motivated and should be able to work well in teams as well as individually. It is to be noted that, as in case of M. Tech. program, you can also convert to Ph.D. programme during the course of M.Tech. (Research). However, you can also change over to Ph.D. programme at the time of submitting your M.Tech. (Research) thesis.

First Term

1. Getting acquainted with the people, facilities in CSA specifically and IISc in general.
2. Selection of courses (depending on your intended area of research): The selection includes at least one mathematics or mathematically-oriented course. Most students take 4 courses to complete the Research Training Programme (minimum required is at least 12 credits) in the first semester. However, you can choose to take less based on the availability of required courses.
3. Selection of Research area and guide: Take help from Departmental Curriculum Committee (DCC), faculty and senior Research students in the department in this regard. There will also be a DCC meeting shortly after joining.

Second Term

1. Take any advanced course useful for your research if required or suggested by your advisor.
2. Select the research problem(s) and start working on the same.
3. Do a literature survey in your area of research.

Third Term

1. Deliver a ‘Perspective Seminar’, a comprehensive survey of your area of work from the standpoint of the specific problem under investigation.
2. Start experimentation and collection of results
3. Writing of research papers, technical reports, etc.
4. You may continue on to the PhD program immediately after submitting your dissertation. (Alternatively, you may apply for a PhD later and appear in a research interview after graduating and leaving IISc.)

Fourth Term

1. Complete the remaining work to conclude your research.
2. Start writing your thesis.
3. Colloquium and thesis defense.
4. Prepare for your future endeavors.

Math Requirement Courses

MTech (Research) students may credit any one of the following courses to satisfy the Math course requirement:
1. Courses in Pool A for the M. Tech. 2019-2021 batch
2. E0 226 : Linear Algebra and Probability
3. E0 299 : Computational Linear Algebra
4. E1 222 : Stochastic Models and Applications
5. E2 202 : Random Processes
5. MA 219 : Linear Algebra
6. MA 221 : Analysis I
7. MA 261 : Probability Models
8. Any other course with the approval of DCC, CSA

Faculty Advisor

While we are sure that all of you have the inherent motivation and abilities to get through the Programme with flying colours, we believe a little extra guidance from us will go a long way in smoothing out your adjustment to a new academic environment and in enhancing your academic performance. Your primary source of academic guidance and counseling is the faculty advisor assigned to you. You should make it a point to get to know your advisor well, and meet your advisor frequently in the early part of your stay here, and especially whenever you face any problems. The distinction between students and faculty is more blurred: you will find faculty willing to deal with you on a more equal level, to listen to and value ideas from you that might be contradictory to their current knowledge and viewpoints, etc.

Another person who can help you will be the TA (Teaching Assistant) for each course. The TA is likely to be a student just one year senior to you. Occasionally, the TA can be someone from your batch who has done the course a semester before you! This is because graduate studies are also meant to teach you things such as honest and critical evaluation of work done by peers.

Student Advisor

There will also be a student advisor assigned to each student. He/She is someone with whom you can interact closely in a friendly and informal way to help yourself acclimatize to the environment here. Apart from the Faculty Advisor, the Student Advisor is another avenue for helping you in adjusting with the environment in the CSA department and the IISc campus in general.

The MTech programme in Computer Science and Engineering (CSE) is a challenging one with courses that have high standards, interesting and stimulating content.

First Term

1. Selection of courses: Meet with your faculty advisor and select exactly four courses, ensuring that one course is taken from each of Pools A, B and C.
2. Work hard to complete your courses with good grades. Note that if your CGPA is high, you can take an additional course in the next semester.

Second Term

1. Selection of courses: Meet with your faculty advisor and select up to four courses (you may take an additional course if you secure the required CGPA). You must have taken two courses each from Pools A, B and C at this point.
2. Selection of Research project and guide: Take help from Departmental Curriculum Committee (DCC), faculty and senior Research students in the department in this regard. By the end of the second term, you will have to select your project and guide in consultation with the DCC.

Third Term

1. Selection of courses: Meet with your faculty advisor and select the remaining courses, ensuring that you finish both your course and pool requirements (you may take an additional course if you secure the required CGPA).
2. Placements are usually held during this term.
3. Start working on your research project.

Fourth Term

1. Complete the remaining work to conclude your research.
2. Start writing your M.Tech. project report.
3. Writing of research papers, technical reports, etc.
4. Prepare for your future endeavors.

Doing Research as a Part of Dissertation Work

The next important issue is the idea of pursuing research. As a part of M.Tech. programme, you are required to write a dissertation. Over the years, the nature of this dissertation work has become more research-oriented, and you are expected to publish papers in international conferences and journals from your dissertation work. Gradually, facilities have been enhanced to do this kind of dissertation work. In the good old days, papers need to be photocopied and read, but now everything is available at your fingertips on the internet (you still need to read them). At the same time, terabytes of storage space is also available. The only additional input you require from your end is your determination to carry out an excellent dissertation work.

Further opportunities for research at IISc

You can convert from M. Tech. to the Ph.D. program at the end of first, second or third term. The requirement is a high CGPA.

Course Requirements:
Department Core: A minimum of 24 credits comprising at least 8 credits each from Pool A, Pool B and Pool C. Pools course for 2019-2021, 2018-2020 and 2017-2019 batches are shown in the following tables.


POOL COURSES FOR 2019-2021 BATCH


POOL A

Course NoCreditsCourse Title
E0 2033:1Spectral Algorithms
E0 2203:1Graph Theory
E0 2223:1Automata Theory and Computability
E0 2243:1Computational Complexity Theory
E0 2253:1Design and Analysis of Algorithms
E0 2283:1Combinatorics
E0 2293:1Foundations of Data Science
E0 2343:1Introduction to Randomized Algorithms
E0 2353:1Cryptography
E0 2443:1Computational Geometry and Topology
E0 2483:1Theoretical Foundations of Cryptography
E0 2493:1Approximation Algorithms

POOL B

Course NoCreditsCourse Title
E0 2023:1Automated Software Engineering with Machine Learning
E0 2103:1Dynamic Program Analysis: Algorithms and Tools
E0 2273:1Program Analysis and Verification
E0 2393:1Software Reliability Techniques
E0 2433:1Computer Architecture
E0 2523:1Programming Languages: Design and Implementation
E0 2533:1Operating Systems
E0 2543:1Network and Distributed Systems Security
E0 2553:1Compiler Design
E0 2563:1Theory and Practice of Computer Systems Security
E0 2613:1Database Management Systems
E0 2643:1Distributed Computing Systems
E0 2713:1Graphics and Visualization
E0 2723:1Formal Methods in Software Engineering

POOL C

Course NoCreditsCourse Title
E0 2263:1Linear Algebra and Probability
E0 2303:1Computational Methods of Optimization
E0 2363:1Information Retrieval
E0 2383:1Intelligent Agents
E0 2683:1Practical Data Science
E0 2673:1Soft Computing
E0 2703:1Machine Learning
E1 2463:1Natural Language Understanding
E1 2543:1Game Theory
E1 2773:1Reinforcement Learning

Project: 21 Credits

EP 299 0:21 Dissertation Project (To be completed during the second year of study.)


POOL COURSES FOR 2018-2020 BATCH


POOL A

Course NoCreditsCourse Title
E0 2033:1Spectral Algorithms
E0 2203:1Graph Theory
E0 2213:1Discrete Structures
E0 2223:1Automata Theory and Computability
E0 2243:1Computational Complexity Theory
E0 2253:1Design and Analysis of Algorithms
E0 2283:1Combinatorics
E0 2293:1Foundations of Data Science
E0 2343:1Introduction to Randomized Algorithms
E0 2353:1Cryptography
E0 2443:1Computational Geometry and Topology
E0 2483:1Theoretical Foundations of Cryptography
E0 2493:1Approximation Algorithms

POOL B

Course NoCreditsCourse Title
E0 2023:1Automated Software Engineering with Machine Learning
E0 2103:1Dynamic Program Analysis: Algorithms and Tools
E0 2273:1Program Analysis and Verification
E0 2393:1Software Reliability Techniques
E0 2433:1Computer Architecture
E0 2523:1Programming Languages: Design and Implementation
E0 2533:1Operating Systems
E0 2543:1Network and Distributed Systems Security
E0 2553:1Compiler Design
E0 2563:1Theory and Practice of Computer Systems Security
E0 2613:1Database Management Systems
E0 2643:1Distributed Computing Systems
E0 2713:1Graphics and Visualization
E0 2723:1Formal Methods in Software Engineering

POOL C

Course NoCreditsCourse Title
E0 2263:1Linear Algebra and Probability
E0 2303:1Computational Methods of Optimization
E0 2363:1Information Retrieval
E0 2383:1Artificial Intelligence
E0 2683:1Practical Data Science
E0 2673:1Soft Computing
E0 2703:1Machine Learning
E1 2463:1Natural Language Understanding
E1 2543:1Game Theory
E1 2773:1Reinforcement Learning

POOL COURSES FOR 2017-2019 BATCH


POOL A

Course NoCreditsCourse Title
E0 2033:1Spectral Algorithms
E0 2203:1Graph Theory
E0 2213:1Discrete Structures
E0 2223:1Automata Theory and Computability
E0 2243:1Computational Complexity Theory
E0 2253:1Design and Analysis of Algorithms
E0 2283:1Combinatorics
E0 2293:1Foundations of Data Science
E0 2343:1Introduction to Randomized Algorithms
E0 2353:1Cryptography
E0 2443:1Computational Geometry and Topology
E0 2483:1Theoretical Foundations of Cryptography
E0 2493:1Approximation Algorithms

POOL B

Course NoCreditsCourse Title
E0 2023:1Automated Software Engineering with Machine Learning
E0 2103:1Principles of Programming
E0 2273:1Program Analysis and Verification
E0 2393:1Software Reliability Techniques
E0 2433:1Computer Architecture
E0 2523:1Programming Languages: Design and Implementation
E0 2533:1Operating Systems
E0 2543:1Network and Distributed Systems Security
E0 2553:1Compiler Design
E0 2563:1Theory and Practice of Computer Systems Security
E0 2613:1Database Management Systems
E0 2643:1Distributed Computing Systems
E0 2713:1Computer Graphics
E0 2723:1Formal Methods in Software Engineering

POOL C

Course NoCreditsCourse Title
E0 2193:1Linear Algebra and Applications
E0 2303:1Computational Methods of Optimization
E0 2323:1Probability and Statistics
E0 2363:1Information Retrieval
E0 2383:1Intelligent Agents
E0 2683:1Practical Data Science
E0 2673:1Soft Computing
E0 2703:1Machine Learning
E1 2463:1Natural Language Understanding
E1 2543:1Game Theory
E1 2773:1Reinforcement Learning

Project: 24 Credits [for 2017-2019 and 2018-2020 batches]

EP 299  0:24 Dissertation Project (To be completed during the second year of study.)
               0:08 August-December Term
               0:16 January-April Term

Electives

The balance of credits to make up the minimum of 64 credits required for completing the MTech Degree Programme (all at 200 level or higher) should be covered with elective courses from within/outside the department and these courses can be taken with the approval of the DCC/Faculty advisor only.

Faculty Advisor

While we are sure that all of you have the inherent motivation and abilities to get through the programme with flying colours, we believe a little extra guidance from us will go a long way in smoothing out your adjustment to a new academic environment and in enhancing your academic performance. Your primary source of academic guidance and counseling is the faculty advisor assigned to you. You should make it a point to get to know your advisor well, and meet your advisor frequently in the early part of your stay here, and especially whenever you face any problems. The distinction between students and faculty is more blurred: you will find faculty willing to deal with you on a more equal level, to listen to and value ideas from you that might be contradictory to their current knowledge and viewpoints, etc.
Another person who can help you will be the TA (Teaching Assistant) for each course. The TA is likely to be a student just one year senior to you; occasionally, the TA can be someone from your batch who has done the course a semester before you! This is because graduate studies are also meant to teach you things such as honest and critical evaluation of work done by peers.

Student Advisor

There will also be a student advisor assigned to each student. He/She is someone with whom you can interact closely in a friendly and informal way to help yourself acclimatize to the environment here. Apart from the Faculty Advisor, the Student Advisor is another avenue for helping you in adjusting with the environment in the CSA department and the IISc campus in general.

Click here for more information.

The following individuals can register for PhD under ERP

  • Employees of scientific institutions or industries involved in R&D
  • Faculties of Colleges/Universities recognized by appropriate government agencies

The details can be found here. The degree requirements are the same as for the regular degree programs.

Faculty members from engineering colleges can register for MTech / Ph.D. under QIP. The details can be found here. The degree requirements are the same as for the regular degree programs.