IIIT Sri City PhD Admission 2025 Monsoon

Indian Institute of Information Technology (IIIT) Sri City Chittoor invites applications for PhD admission for Monsoon session 2025.

Available Research Areas

Computer Science and Engineering (CSE)

Agent based modeling & simulations, Algorithms, Authentication and Access Control, Cognitive modeling – relational patterns, Computational Geometry, Computer Architecture, Computer networks, Cryptography and Network Security, Cloud/SDN Security, Cybersecurity, Cyber Physical Systems, Data Analytics, Design Automation of Electronic Systems, Distributed Algorithms, EEG Data Analysis, Embedded Systems, System architecture, Healthcare informatics, High performance computing, Human Computer Interaction, Image Processing and Computer Vision, Intelligent Control, Machine/Deep Learning, , Multi-objective optimization, Natural Language Processing, Security and Blockchain, Self Organizing and Self-Assembly Systems, Soft Computing, Spatial/Spatio Temporal/Multivariate Statistical modeling, Statistical and machine learning models for Environmental Applications, Text Data Mining / Information Retrieval, VR/AR, Wireless Sensor Systems, Human Robot Interaction, Unmanned Aerial Vehicles, Advanced Cryptography, AI driven intrusion Detection System, Bioinformatics and Computational Biology with Deep Learning, Bio-Medical Image/Data Analysis using Artificial Intelligence, Industrial Internet of Things, Edge Computing, Quantum Computing, Federated Learning, Document image and Video analysis, and OCR, AI and ML / DL for Data Science.

Electronics and Communication Engineering (ECE)

Adaptive Driver Assistance System, Applications of Pattern Recognition, Biomedical Signal Processing, Cyber Physical Systems, Deep learning, Electromagnetic scattering, Energy harvesting, MEMS and VLSI Technology, Microfabrication, Microfluidics and micropumps, Passive components, Propagation modeling, Protocols for IoT, Sensor Technology, Speaker recognition, Speech/voice activity detection, Statistical Signal Processing, Vehicular Communication, Wireless Networks, Quadrotor Control, Renewable Energy, Performance analysis of nano scale molecular communication system with different channel conditions, Interfacing of Terahertz communication with in body communications for health care applications, 5G-OFDM Communication Systems, MIMO Communication system.

Mathematics and Data Science

Theoretical and Applied Statistics, Remote Sensing, Geostatistics, Spatial and Spatio-temporal Statistics, Environmental Statistics, Non-stationarity and Non-Gaussianity Problems, Machine Learning, Neural Networks, Applied Mathematics, Numerical Solution of Partial Differential Equations – Neural Network Finite Difference/Element/Volume Methods, Computational Fluid Dynamics, Asymptotic Preserving IMEX-DG Schemes on Adaptive Grids for Multiscale Compressible Flows.

Eligibility Criteria

For PhD in CSE

• Any branch (in BTech) with relevant MS/MTech degree; with Master’s degree (M.E. /M.Tech) or MS by Research in CSE or related specializations and Bachelor’s degree (B.E./B.Tech) or MCA, MSc in CS, Maths, statistics, or equivalent with a minimum of 60% (or above) aggregate marks (CGPA ≥ 6.5/10) in UG and PG for admission under GEN/GEN-EWS/OBC-NCL category and 55% (or above) aggregate marks (CGPA of ≥ 6.0/10) for SC/ST/PwD candidates.
• Direct PhD admission: Good Candidates having B.E / B.Tech in CSE or equivalent disciplines from CFTIs or Institute of National Importance or Top 200 NIRF ranking institutions with CGPA of 8.0 and above with demonstrated research potential by means of research papers, IPs and similar research outcomes may also be considered

For PhD in ECE

• Master’s degree (M.E. /M.Tech) or MS by Research in Electronics, ECE, Instrumentation, EEE or related specializations and Bachelor’s degree (B.E./B.Tech)/MSc Physics, Electronics or equivalent with a minimum of 60% (or above) aggregate marks (CGPA ≥ 6.5/10) in UG and PG for admission under GEN/GEN-EWS/OBC-NCL category and 55% (or above) aggregate marks (CGPA of ≥ 6.0/10) for SC/ST/PwD candidates.
• Direct PhD admission: Good Candidates having B.E / B.Tech in ECE or equivalent disciplines from CFTIs or Institute of National Importance or Top 200 NIRF ranking institutions with CGPA of 8.0 and above with demonstrated research potential by means of research papers, IPs and similar research outcomes may also be considered.

For PhD in Mathematics and Data Science

• Bachelor’s and Master’s degree in Mathematics/Statistics or equivalent discipline with a minimum of 60% (or above) aggregate marks (CGPA ≥ 6.5/10) in UG and PG for admission under GEN/GEN-EWS/OBC-NCL category and 55% (or above) aggregate marks (CGPA of ≥ 6.0/10) for SC/ST/PwD candidates with a valid score in GATE or CSIR/ UGC NET(JRF)/NBHM/ INSPIRE.
• As of date, students selected under Mathematics and Data Science would work and get a degree under the CSE group.

Application Process

Candidates may submit the detailed application using the Google Form available on website.

Admission Process

• Candidates recommended by the Ph.D. Admissions Committee will be called to appear for a written test.
• The candidates shortlisted based on the written test performance need to appear for a personal interview before the Ph.D. Admissions Interview panel.

Syllabus for Written Test

Computer Science and Engineering

• Discrete Mathematics: Propositional and First-order Logic. Sets, Relations, Functions, Partial Orders, and Lattices, Groups, Graphs: Connectivity, Matching, Coloring Combinatorics: Counting, Recurrence Relations, Generating Functions.
• Probability: Random Variables. Uniform, Normal, Exponential, Poisson, and Binomial Distributions. Mean, Median, Mode, and Standard Deviation. Conditional Probability and Bayes Theorem.
• Computer Programming: Programming in C, Scope of Variables, Loops, Functions, Structures, Pointers, Dynamic Memory Allocation, File Management.
• Data Structures: Stacks, Queues, Linked Lists, Trees, Binary Search Trees, Binary Heaps, Graphs.
• Algorithms: Searching, Sorting, Hashing. Asymptotic Worst-case Time and Space Complexity, Algorithm Design Techniques: Greedy, Dynamic Programming, and Divide‐and‐Conquer. Graph Search, Minimum Spanning Trees, Shortest Paths.
• Operating System: Processes, Threads, Interprocess Communication, Concurrency, and Synchronization, Deadlock, CPU Scheduling, Memory Management, and Virtual Memory, File Systems.
• Computer Networks: Concept of Layering, LAN Technologies (Ethernet), Switching, TCP/UDP and Sockets, Congestion Control, Application Layer, Network Security: Authentication, Basics of Public Key and Private Key Cryptography, Digital Signatures and Certificates

Electronics and Communication Engineering

• Basic electronics: Circuit laws, theorems (superposition, thevenin and norton, max power), passive elements, transients (RL and RC circuits) and op-amps and applications, filters active and passive). Diode characteristics, half-wave and full-wave rectifier. Transistors, and amplifiers.
• Electromagnetics: Maxwell’s equation, boundary conditions, time-varying fields, wave propagation in different media, transmission line basics, terminated transmission line and the special cases, antenna characteristics, FRIIS transmission equation and radar range equation.
• Digital logic design: Combinational logic: Logic circuits of Code Converters such as Binary to Gray Code Converter, BCD converter etc., K-maps, multiplexers, decoders, PROMs and PLAs Sequential circuits: Latches and flip-flops, counters and shift-registers Data converters: sample and hold circuits, ADCs and DACs; Memories.
• Signal Processing: Classification of signals and systems, basic deterministic signals, Linear systems and convolution, frequency domain representation of continuous and discrete signals, sampling theory, z-transform, circular convolution, discrete Fourier transform, Fast Fourier Transform, Digital filter design and implementation.
• Analog and Digital Communication: Basics of Analog and Digital modulation, Basics of Cellular, Interference, Noise, Channel, Wireless channel fading, Shannon Capacity.
• Embedded Systems: Basic Definitions, Embedded – C concepts, Python Programing, Real-Time Operating systems, microcontroller and its submodules. Additional topics: Knowledge on hardware boards like Arduino and Raspberry Pi, sensors and actuators.

Mathematics and Data Science

• Algebra: Groups, subgroups, normal subgroups, quotient groups, homomorphisms, cyclic groups, permutation groups, Cayley’s theorem, class equations, Sylow theorems. Rings, ideals, prime and maximal ideals, quotient rings, unique factorization domain, principal ideal domain, Euclidean domain. Polynomial rings and irreducibility criteria. Fields, finite fields, field extensions.
• Linear Algebra: Vector spaces, subspaces, linear dependence, basis, dimension, algebra of linear transformations. Algebra of matrices, rank and determinant of matrices, linear equations. Eigenvalues and eigenvectors, Cayley-Hamilton theorem. Matrix representation of linear transformations. Change of basis, canonical forms, diagonal forms, triangular forms, Jordan forms. Inner product spaces, orthonormal basis. Quadratic forms, reduction and classification of quadratic forms.
• Real Analysis: Elementary set theory, countable and uncountable sets, Real number system as a complete ordered field, Archimedean property, supremum, infimum. Sequences and series, convergence, limsup, liminf. Bolzano Weierstrass theorem, Heine Borel theorem. Continuity, uniform continuity, differentiability, mean value theorem. Sequences and series of functions, uniform convergence. Riemann sums and Riemann integral.
• Complex Analysis: Analytic functions, Cauchy-Riemann equations. Contour integral, Cauchy’s theorem, Cauchy’s integral formula, Liouville’s theorem, Maximum modulus principle, Schwarz lemma, Open mapping theorem. Taylor series, Laurent series, calculus of residues.
• Ordinary differential equations: Existence and uniqueness of solutions of initial value problems for first order ordinary differential equations, singular solutions of first order ODEs, system of first order ODEs. Systems of first order differential equations, equations with regular singular points, stability of linear systems.
• Probability: Random Variables. Uniform, Normal, Exponential, Poisson, and Binomial Distributions. Mean, Median, Mode, and Standard Deviation. Conditional Probability and Bayes Theorem.

Last date for submission of applications via online with relevant documents is 10th April 2025.

• Information Sheet
• Application
• IIIT Sri City Website