The faculty members of ISE are actively involved in several multi-faceted research and consulting activities with high relevance to industry and society. The Department has been at the forefront in areas such as Cloud Computing, Internet of Things, Cloud Security, Artificial Intelligence and Machine Learning, Data Mining, Image Processing, Natural Language Processing and, Grid Computing.
Cloud computing implementation is being done in our DBIT-Data Centre. The primary benefit of moving to Clouds is application scalability. With the rapid advance of cloud computing, the data centre plays a key role. Cloud Computing Research areas are Green Cloud Computing, Edge Computing, Cloud Cryptography, Load Balancing, Cloud Analytics, Cloud Scalability, Mobile Cloud Computing.Several projects which can be deployed on the cloud are being developed by our students, faculty members, and research scholars.
Internet of Things (IoT)
Internet of Things, popularly recognized as IoT, is an emerging technology. IoT is dominating the Information Technology field because of “Smart Objects” which can freely “talk” to each other and generate an enormous volume of data, spread across different communication networks. Interconnectivity, related to what sensors can now capture, plays a very important role in the IT field. Every field of human requirement including Health care, Retail, Disaster Management, Traffic Management, Secured and Smart Homes, Smart Cities, Smart Agriculture are depending on the Internet of Things. We are developing innovative applications on the IoT domain, which support societal needs.
With the rapid development of computer technology, cloud-based services have become an emerging topic. Cloud-based services not only provide users with convenience but also bring many security issues. Therefore, the study of access control schemes to protect user privacy in a cloud environment is of great significance. We are exploring the various mechanisms to achieve security measures in cloud computing which provide a major research field.
Artificial Intelligence and Machine Learning (AI&ML)
Machine Learning is a recently developed field belonging to Artificial Intelligence. It tries to mimic the human brain, which is capable of processing complex input data, learning different knowledge intellectually and fast, and solving different kinds of complicated tasks well. Switching these features of the human brain to a learning model, the model can be dealt with the high-dimensional data, support a fast and intellectual learning algorithm and perform well in the complicated AI tasks like computer vision or speech recognition. Deep architecture is believed to be such kind of model, with good learning algorithms for deep learning and excellent performance in solving AI tasks.
Data mining is an extensively used technique for extracting frequent patterns in large databases. By extracting unique patterns, data mining provides information to numerous problems. Mining algorithms are applied in various domains, it is mainly used to predict trends and forecast business activities by extrapolation in business and economics, in the medical field to predict the onset of seasonal diseases, to identify new and antibiotic-resistant diseases, and in almost all fields of science and technology. Though data mining can bring huge benefits, it also raises some privacy concerns, e.g. when a medical database is shared, preserving the privacy of the data is also important to avoid violation of individual patient’s highly personal information.
Image processing is a method to perform some operations on an image, to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Some open research areas in image processing are Automatic Detection, Classification, Identification of Single and Multiple objects, Automatic Image, Enhancement, Image Segmentation, Image Classification, Image Compression Image Inpainting, Image Restoration.
Natural Language Processing
Natural Language Processing (NLP) is the application of Linguistics, Computer Science, Information Engineering, and Artificial Intelligence in the interactions between computers and human (natural) languages. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a valuable manner. Computers are programmed to process and analyze large amounts of natural language data. Some of the tasks associated with NLP include Grammar Induction, Lemmatization, Morphological Segmentation, Part-of-Speech Tagging, Treebank Generation, Parsing, Stemming, Automatic Summarization, Co-reference Resolution, Discourse Analysis, Speech Recognition, Speech Segmentation and Text-To-Speech Synthesis (TTS).
Grid computing is the use of widely distributed computer resources which enables grids composed of many networked loosely coupled computers acting together to perform large tasks. It enables scheduling of jobs, balancing the load, migrating the jobs, partitioning the tasks into manageable units for parallel and distributed processing, and tolerance to the failures and faults. It enables the high-level availability from the pool of resources for the applications throughout the world.