ADMISSIONS 2018

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Academics

This M. Tech. programme aims at preparing the students to take up application, research and development activities in core and some emerging areas in Computer Science, with focus on AI and AI related applications in a distributed computing environment. The programme includes advanced level courses in Computer Architecture, Networking, Algorithms, Data Bases, Distributed Computing and Computational Intelligence. This programme will provide a strong basis in Computer Science for those who opt for a serious career in industry.

The purpose of the programme is to generate human resources capable of supporting R & D activities in critical areas like automated, secured, monitoring and surveillance systems, medical diagnostics, intelligent monitoring systems etc. The diversity of platforms available for implementation and the huge volume of data available for analysis, knowledge mining activities associated with biological systems, medical field, data related to climate changes etc. attract employment opportunities.


Program Highlights

  • Placement and internships in core companies like Cisco, IBM, Cerner, L & T Technology, Inside View, ThermoFisher Scientific, Bosch ,KPIT Technologies, 1000Looks.com, TCS-TRDDC, Lucid Imaging, Samsung, Tata Consultancy Services, Kodak ,Canon and organizations like ISRO, NPOL, Oracle, Zoho Corpoation etc
  • Opportunities for student exchange in premiere universities like KTH Sweden, Politecnico Di Milano– Italy, University of New Mexico-USA, RWTH – Aachen University Germany, University of York, University of Turku-Finland, Vrije University ,and other universities USA and Europe etc for a semester or a year.
  • Fully equipped computer laboratory exclusively for PG students.
  • Amrita Multi Dimensional Data Analytics Laboratory to support projects in Pervasive computing, Big Data Analytics, Web Science etc
  • Cognizant Innovation lab focusing on Robotics, Artificial Intelligence and Security, Image Analysis, Video processing and computer vision.
  • Wireless Sensor Networks Lab involved in developing solutions using IoT, smart meters for societal applications
  • Mobile Application Development Lab actively works in developing applications using signal processing for mobiles.
  • Opportunities to work on live projects for Government of India and Industry, Research as a part of the curriculum resulting in scholarly publications and collaborative projects with Amrita Institute of Medical Sciences (Multi Specialty Hospital), Kochi
  • Innovative course structure enabling specialization in Big Data and Computational Intelligence, Networking, and High Performance Computing with specialized Mathematics Courses
  • Advanced courses in recent thrust areas like Enterprise Architecture, Parallel and Distributed Computing, Foundations of Data Science, Machine Learning for Big Data
  • Research as part of curriculum resulting in scholarly publications
  • Courses with focus on lab components providing expertise in technologies like Hadoop, R Programming, Data Analytics Tools
  • Regular workshops conducted by industry and academia: Workshop by TCS on Hadoop and Mapreduce, NS2 Workshop with sessions from experts from academia

Thrust Areas in Research

Biometrics

Computer Vision

Signal Processing

Human Computer Interaction

Multidimensional Data Analytics

Data Analytics
 

Evolutionary Computing

Next Gen Computing

Predictive Analytics and IoT

Security

 

Image Analysis and Pattern Recognition


Best Student Projects

Company: Robert Bosch Engineering and Business Solutions Private Limited, Coimbatore

Abstract
Air conditioning systems in large scale buildings contribute a major portion of the energy requirements. A centralized temperature monitoring system would result in the enhancement of air conditioning services in large scale buildings. Here we develop a centralized temperature monitoring scheme suitable for office environments. Wireless sensors are placed inside a compartmentalized office area, which collects the surrounding temperature data and sends it to the cloud. The application in the cloud will receive this data, store the data and present this data graphically to the end user. In order to reduce the redundant data as well as for making the sensor network energy efficient, we carry out a data analytics algorithm to identify the redundant sensors in the network based on data correlation.

Abstract
Main focus of this research work is to design an efficient and scalable RFID based hybrid indoor localization algorithm that operates over long-range RFID readers. The major objectives of this work are to design an approach that is extensible to large environments with minimal calibration and to provide high accuracy. Asset tracking is important for resource utilization and recovery. It is a service that helps locate objects instantly by providing easy access of item locations without much manual effort. We design a hybrid localization algorithm to accurately estimate the position of an object within a finite indoor space. Our approach uses power level and signal strength parameters which are readily available without the requirement of additional hardware. Furthermore, our algorithm applies intelligent region elimination techniques, thereby avoiding the use of heavy calibration and computationally complex algorithms.

Abstract
The most unbeatable technology, Internet brings to people for communication is social networks. With the exponential growth of users in internet, there is an equivalent growth among internet users to regularly visit social websites for linking with their friends, sharing thoughts, photos, videos and even discuss about their day today activities. The fact these social networks are available to all the users for free, leads to various types of security issues. Image security has been a topic of research over decades. Enhancements to individual techniques and combinations proposed till date have offered different levels of security assurances. This work aim to present a technique for secure sharing of image posts in social network. The significant feature of the scheme lies in the selection of security technique based on image content, evaluation of peers with whom the image can be shared based on text classification, transliteration and tone analysis. The proposed scheme a cost effective solution as it does not require any additional hardware. The utility of the model is demonstrated by mapping the scheme with Facebook and analyzing its performance through simulation.


Placements


Curriculum

FIRST SEMESTER SECOND SEMESTER THIRD SEMESTER FOURTH SEMESTER
Modern Computer Architecture Parallel and Distributed Systems Elective –IV Dissertation
Advanced Algorithms and Analysis Machine Learning Elective –V  
Systems Security Enterprise Architecture Dissertation  
Mathematical Foundations of Computer Science Elective–II    
Elective-I Elective–III    
Cultural Education Negotiated Studies    
  Technical Writing    
Elective-I (General Electives) (Mathematical Foundations) Elective-II
Computational Intelligence Advanced Linear Algebra
Topics in Databases Randomized Algorithms
Object Oriented Design Computational Optimization
Computational Statistics Random Process and Optimization theory
Advanced Computer Networks Networks and Spectral Graph Theory
Compiler Design  
Wireless Networks  
Foundations for Signal and Image Processing  
Stream-I Machine Learning and Data Science Stream –II   Architecture and  Systems Stream –III Networks and Intelligent Systems Stream –IV  Computer Vision
Machine Learning for Big Data Hardware Software Co-Design Mobile Networks Digital Image Processing
Foundations of Data Science Parallel Computer Architecture Principles of  Software Designed Networks Video Analytics
Applications of Machine Learning Reconfigurable Computing Wireless Sensor Networks Medical Image Analysis
Statistical Learning Theory Advanced Operating Systems Network Security Content Based Image and Video Retrieval
Natural Language Processing Critical Systems and Verification Pervasive Computing Pattern Recognition
Information Retrieval Compiler Optimization Techniques and Design Agent Based Intelligent Systems Data Compression
Data Mining and Business Intelligence Computer Systems’ Performance Analysis Scripting Languages  
Semantic Web Parallel Programming Computer Crimes, Security and Cyber Laws  
  High Performance Computing Debugging Tools  
    Open Course  
You can join this program at
Degree: 
Postgraduate (PG)
School: 
School of Engineering
Campuses: 
Bengaluru
Coimbatore
207
PROGRAMS
OFFERED
6
AMRITA
CAMPUSES
15
CONSTITUENT
SCHOOLS
A
GRADE BY
NAAC, MHRD
8th
RANK(INDIA):
NIRF 2018
150+
INTERNATIONAL
PARTNERS