Machine LearningMachine Learning is a vast area which includes supervised learning, unsupervised learning, and reinforcement learning. Lots of works recently focused on reinforcement learning to make computer learn by designing reward functions and policy gradients, you have probably heard of AlphaGo from Google DeepMind, Dota2 Player from OpenAI and so forth.
There are a lot of research papers published regarding the reinforcement learning in ICML, NeurIPS, and ICLR. There are interesting as well as fascinating to read. The other works are on supervised learning and it has a vast literature now its upto you what kind of work interests you. For instance,
Machine Learning is one of the most actively researched areas of Computer Science and Engineering in Saveetha School of Engineering by which we are trying to bridge the gap between transferring learning to active learning domains. |
Dr. S P. CHOKKALINGAM
PROGRAM DIRECTOR |
Dr. SRIRAMALU MAGESH
PROFESSOR & ASSOCIATE DEAN OF FACULTY AFFAIRS |
Cloud ComputingCloud Computing, a technology that has proliferated into an all pervasive aspect of computing domain contains many unexplored research opportunities. These opportunities can be broadly categorized under the sub aspects of resource sharing, load balancing, cloud security, cloud app development, data management within the cloud, privacy preservation of communication, governance, risk and compliance aspects etc.
The technology of cloud must be tightly coupled with various other technologies like, embedded systems, communication systems, wireless sensor networks, to tap the unexplored potential in those applications. Cloud computing when combined with data science with improved security can definitely prove to be a game changer in the decades to come. |
Dr. RAMA PARVATHY
PROFESSOR |
Data Science and AnalyticsData science is a concept used to handle big data, which includes data cleansing, preparation, and analysis. A data scientist collects data from multiple sources and applies machine learning techniques, predictive analytics, and sentiment analysis to extract critical information from the collected data sets. A data analyst is generally the person who can do basic descriptive statistics, visualize data, and communicate data points for conclusions. Statistics understanding, familiarity of Databases, the ability to create new views and the perception to visualize the data are some of the skills required to become Data analyst.
Skill set required to become a Data Scientist/Analyst
|
Dr. R.SABITHA
PROFESSOR |
Edge computingEdge computing is transforming the way data is being handled, processed, and delivered from millions of devices around the world. The explosive growth of internet-connected devices – the IOT – along with new applications that require real-time computing power, continues to drive edge-computing systems.
Faster networking technologies, such as 5G wireless, are allowing for edge computing systems to accelerate the creation or support of real-time applications, such as video processing and analytics, self-driving cars, artificial intelligence and robotics, to name a few. While early goals of edge computing were to address the cost of bandwidth for data travelling long distances because of the growth of IoT-generated data, the rise of real-time applications that need processing at the edge will drive the technology ahead. Edge computing is “a part of a distributed computing topology in which information processing is located close to the edge – where things and people produce or consume that information”. At its basic level, edge computing brings computation and data storage closer to the devices where it’s being gathered, rather than relying on a central location that can be thousands of miles away. This is done so that data, especially real-time data, does not suffer latency issues that can affect an application’s performance. In addition, companies can save money by having the processing done locally, reducing the amount of data that needs to be processed in a centralized or cloud-based location. Edge computing was developed due to the exponential growth of IoT devices, which connect to the internet for either receiving information from the cloud or delivering data back to the cloud. And many IoT devices generate enormous amounts of data during the course of their operations. |
Dr. SARAVANAN. M.S
PROFESSOR |
Data Science and Computational IntelligenceData Science focus on core competencies in machine learning, data mining, data visualization, and cloud computing, If you select the Data Science domain based study at Saveetha School of Engineering then your courses and projects will focus on:
|
Augmented Reality based GamificationVirtual reality have long been the fancy application for gaming industry since the early 1990s, however, its potential was limited to its hardware performance, which in turn depended on the GPU (Graphical Processing Unit). Once the Cloud technology become a reality in the recent days, accessing GPU remotely has led to a promising world of Augmented Reality mixed Virtual Reality applications.
Another important area which is trending around the world is Gamification, which is nothing but the application of game elements in non-gaming situations, often to motivate or influence behavior. The rewards or the spirit of competition can spur students' concentration and interest and lead to more effective learning. The research focus at Saveetha School of Engineering ventures into this high-tech education system where students can benefit using AR based Gamification application. Our primary focus is to develop mobile based AR applications using UNITY 3D and provide it as a cloud-based service. The data collection from Students can be done using Edge devices and performance related training can be captured through edge analytics. The applications of this research can certainly enable our institute enrich our young generation for a better future through advancement of technology. |
Dr. UDHAYA KUMAR
PROFESSOR |
Cyber SecurityCyber security is the practice of defending computers, servers, mobile devices, electronic systems, networks, and data from malicious attacks. It's also known as information technology security or electronic information security. The term applies in a variety of contexts, from business to mobile computing, and can be divided into a few common categories.
End-user Data protection End-user protection or endpoint security is a crucial aspect of cyber security. After all, it is often an individual (the end-user) who accidentally uploads malware or another form of cyber threat to their desktop, laptop or mobile device. So, how do cyber-security measures protect end users and systems? First, cyber-security relies on cryptographic protocols to encrypt emails, files, and other critical data. This not only protects information in transit, but also guards against loss or theft. In addition, end-user security software scans computers for pieces of malicious code, quarantines this code, and then removes it from the machine. Security programs can even detect and remove malicious code hidden in Master Boot Record (MBR) and are designed to encrypt or wipe data from computer’s hard drive. Cyber Security Research is one the active research focus in the Institute of Computer Science , at Saveetha School of Engineering. |
Dr. S.SUBBIAH
PROFESSOR |