Indian Institute of Technology Bombay

Ph.D. Admissions

  • Introduction

    The CSE department invites applications from students with a "research" bent of mind, to apply for admission to the Ph.D. programme. Applicants must have a creative drive, the willingness to work on challenging technical problems for a sustained duration, and the academic preparation in basic subjects of computer science and engineering. Admission to the Ph.D. programme can be gained in various categories (Full-Time, Part-Time, etc.). Please familiarize yourself with the categories and the admission requirements for each category by reading the official Ph.D. Information Brochure here.
    International Ph.D Students can view scholarship opportunities here.

  • Process for Ph.D. admissions
    Step Date
    Availability of online application form March 24, 2021
    Last date for submission of completed application form April 12, 2021
    Publication of shortlisted candidates for Written Test and/or Interview April 23, 2021
    Date of Written Test(for all categories) May 02, 2021
    Dates of Interviews(for all categories) May 13 to 25, 2021
  • CSE Departmental Admissions Procedure
    1. The CSE department's recommendation will be based on the performance of the candidate in the following:
      • Written test.
      • For candidates shortlisted from written test:
        • Verbal Interview.

    2. The syllabus for the written test is as follows:
      • Mathematical Aptitude: Discrete structures (sets, graphs, elementary counting and probability), elementary calculus, linear algebra, geometry.
      • Programming Aptitude: Ability to write programs in C/C++ to solve simple problems. Use of elementary data structures such as arrays, lists, stacks, queues, trees. Familiarity with recursion. Ability to reason about programs, e.g., writing loop invariants and assertions.
      • Computer Science and Engineering: Questions from the following 9 areas of the undergraduate computer science and engineering curriculum:
        • Algorithm Design and Analysis.
        • Artificial Intelligence.
        • Compiler Construction.
        • Computer Graphics and Image Processing.
        • Computer Networks.
        • Database Management Systems.
        • Operating Systems.
        • Theory of Computation.
        • Computer Architecture

    3. The written test will consist of simple fill-in-the-blank type questions. The test will have around 40 blanks to be answered in 3 hours. All questions are compulsory. All candidates, except those granted waiver, have to appear for the written test. The eligibility conditions for waiver from the written test can be found in the Ph.D. Information brochure. Click here for the May 2016 Question Paper.

    4. The Students who have been shortlisted from the written exam will be interviewed by the panel of their area. The respective panels will get in touch with their candidates closer to the interview date.

    5. In the verbal interview, a panel of faculty members will assess the candidates on their academic background and research potential. Candidates will be given an option to appear before at most 2 interview panels based on their choice of area.
      The dates of the written tests and interview are final and cannot be changed under any circumstance.

    6. The list of research areas for interviews are as follows.
      1. Theoretical Computer Science: Algorithms, Combinatorial Optimization, Combinatorics, Complexity Theory, Cryptography and Graph Theory.
      2. Speech and Natural Language Processing: Natural language understanding, Machine translation, Semantics Extraction, Document understanding, Cross lingual information Retrieval, Intelligent interfaces.
      3. Visual Computing: Computer graphics, Geometry processing, Image and signal processing, Computer vision and medical image computingRendering (photorealistic, non-photorealistic, real-time, immersive), animation (character, physics-based), sketch-based systems, augmented and virtual reality, camera and imaging systems. Image and geometry reconstruction, restoration, compressed sensing, compression, pattern recognition, localization, segmentation, tracking, registration, quantization, shape analysis, group analysis, retrieval, affective computing. Machine learning methods, deep learning, matrix analysis, statistical methods.
      4. Computer Security and Applied Cryptography: Information flow-based security modeling, language and OS security, web and browser security, security analytics, secure multi-party communication, verification of cryptographic protocols, side channel attacks and hardware security, computation on encrypted data.
      5. Computer Networks: Performance modeling, analysis and design of wired and wireless networks, Implementation and verification of network security protocols. Deployment, data management, communication and energy-efficiency issues in Sensor Networks, Design of content distribution networks for data dissemination, Architectures and protocols for metro optical networks, Network algorithms, Utility and Pricing models, Quality of service protocols, Mobile Computing, Voice Routing, Voice over IP, RFID networks, Enterprise networks, Access and Broadband networks.
      6. Database and Information Systems: Query Optimization, with a focus on parallel and distributed databases (aka Big Data systems), Holistic optimization of database applications, data generation for testing and grading SQL queries, Real time databases, Database support for Embedded and IoT systems, Spatial databases.
      7. Machine Learning and Information Retrieval: Data integration models and algorithms, Graphical models, Information extraction and retrieval, Forecasting and smart e-business, Text and Web data mining. Integrated mining with relational DBMS, Temporal mining, Integrating mining with OLAP
      8. Distributed Systems: Performance Evaluation, fault tolerance and scalability issues in distributed systems, Distributed object-based systems, Programming models and runtimes for generic agents, Parallel Computing, High performance cluster computing, Distributed operating systems, Self-configuration using abstract performance and capacity models of distributed component based applications, Topology based problem detection and root cause isolation in enterprise environments.
      9. Formal Methods: Formal specification, design and verification of hardware and software systems including distributed systems, Logic, automata theory and their applications in reasoning about systems, Automated theorem proving, Model checking, Reachability analysis of large and infinite state spaces: exact and approximate techniques.
      10. Programming languages and Compilers: Theory of code optimization, Optimizing and parallelizing compilers, Analysis and implementation of functional and logic programming languages, Theory of programming languages.
      11. Real-Time, Embedded, Cyber Physical Systems: Functional Programming Applications, Reconfigurable computing, Automobile Telematics, Embedded control units, Design and development of robots and sensor platforms, temporal constraints, time critical applications
      12. Software Engineering and Paradigms: Software Architecture, Program Synthesis and Analysis, Design, Evolution and Re-engineering of Programs, Conceptual Models of Programs, Abstractions and Paradigms, Design Quality of Program Structure.
      13. Computer Architecture: Data and instruction cache optimizations for emerging (server, desktop, mobile, domain-specific) workloads, microarchitecture optimizations for address translation in virtualized environments, memory hierarchy for persistent memory systems,
        Energy efficient memory hierarchy for mobiles and servers, transient execution and timing attacks, secure processor and memory hierarchy, trusted execution environments like Intel SGX and ARM TrustZone, attack detectors, security-performance tradeoffs.

    7. We also have project openings for Ph.D.

      Click here for the complete list of project openings for the year 2021.

  • Ph.D. Qualifier Model

    The PhD qualifier in our department is considered completed when a PhD student meets all of the following criteria:

    • Obtaining a minimum CPI of 7.5 over the specified number of courses, completed within the stipulated time. The course requirements of PhD students for the qualifier depend on the prior education background of the student. Students who already have a post graduate degree in CSE are required to complete 4 PG-level courses in 2 semesters. Students with only an undergraduate CSE degree will need to complete 5 PG courses in 2 semesters. Students who do not have an undergraduate CSE degree will need to complete 6 UG courses and 5 PG courses in 4 semesters.
    • Clearing the PhD seminar course with a grade of BB or higher (you will have two attempts to clear the seminar)
    • Obtaining a pass grade in the communication skills course
    • Finding a CSE faculty member willing to guide you, and a coherent research proposal that is mutually agreed upon by the student and the faculty member.

    Once the student meets the above requirements, he/she may submit a PhD confirmation form to the PhD faculty advisor for approval, which completes the PhD qualifier.
    More info