Enabling growth that’s joyous,
unlimited and self-motivated

1. Semiconductor based Photocatalysis:

   Water pollution, caused by the thoughtless disposal of chemicals, dyes, wastes, plastics and other organic pollutants, has severely affected the natural water resources, causing a significant threat to the availability of clean drinking water. Advanced Oxidation Process (AOP) uses highly reactive species to destroy pollutants by creating hydroxyl radicals in the water. As a result, most organic compounds are oxidized to less harmful chemicals. Frequently used AOPs are photolysis, photo-Fenton, and photocatalysis, which create radicals using semiconductors and light energy.

1. Digital Signal Processing

   Advancements in digital signal processing technology are enabling its use for increasingly widespread applications. Developers are challenged to use this processing power to its utmost, while creating new applications and improving existing ones. An ever-increasing range of integrated circuits, specifically custom-made to perform common DSP functions, is available to the design engineer as system building blocks or parts-in-trade. DSP methodologies have been applied to consumer electronics, communications, automotive electronics, instrumentation, medical electronics, tomography and acoustic imaging, cartography, seismology, speech recognition, robotics etc. Digital signal processing is used everywhere, primarily in areas of audio signal processing, speech processing, RADAR, seismology, audio, SONAR, voice recognition and some financial signals.

2. Communication Systems

   The recent advances in the area of communication research focus mainly on 5G and 6G Mobile networks, Wireless networks, Quantum Communication, MIMO Technology, Satellite communication. Higher Bandwidth, together with fast data-speeds, can change communication drastically, resulting in increased number of connected devices. AI, along with mobile network security, enables the development of innovative algorithms, architecture that is reliable and user friendly.

1. Crystal Growth (Nonlinear Optics Materials) :

   Crystal growth for nonlinear optical materials in photonic applications is a multidisciplinary field that involves materials science, crystallography, and optics. Advances in this area contribute significantly to the development of more efficient and versatile photonic devices. Exploring new materials with enhanced nonlinear properties and incorporating nanostructures for tailored optical responses. It supports the application of frequency conversion, Phase matching and optical parametric oscillation. This is particularly important for photonic applications where the control of light is essential.

2. LASER Analytical techniques Designing:

   LASER (Light Amplification by Stimulated Emission of Radiation) analytical techniques utilize laser technology for various analytical applications. Designing a LASER analytical technique involves considering the specific requirements of the analysis, the type of sample being studied, and the desired level of sensitivity and precision. The research is designing the analytical technique for solid sample.

1. Computer Networks

   A computer network is a network of diverse computing hardware linked through different communication technologies to share various resources. The communication links of the network can be either wired (cables) or wireless (radio waves / IR signals). The areas of research in Wireless Sensor Networks include the following:

   1. Evaluate and implement energy efficient protocol for data aggregation in wireless sensor networks

   2. Node Localization Approach in underwater acoustic network using bio-inspired method

   3. Evaluate and implement sink hole attack isolation method in wireless sensor networks

   4. The three-level hierarchical routing protocol for data aggregation in wireless sensor networks

   5. Design and implement black hole attack isolation method in wireless sensor networks

   The areas of research in Vehicular ad hoc Networks include the following:

   1. Implement and evaluate Sybil attack isolation scheme for vehicular ad hoc networks

   2. Propose novel scheme for the detection of DDOS attack in vehicular ad hoc networks

   3. Zonal based routing scheme for path establishment in vehicular ad hoc networks

   4. Secure and efficient message authentication scheme for vehicular ad hoc networks

   Other areas in Wireless ad hoc Network are:

   1. Propose hybrid routing protocol based on the bio-inspired methods in mobile ad hoc network

   2. Threshold-based mechanism for the isolation of worm hole attack in mobile ad hoc networks

   3. Evaluate and implement clustering-based method for the isolation of black hole attack in mobile ad hoc network

   4. Novel method for congestion avoidance in mobile ad hoc network, to maintain quality of service in the network

2. Embedded Systems

   Embedded systems play a critical role in the design and implementation of practical real-world robotics and intelligent applications. The field of embedded systems focuses on how to develop fast, efficient, small, secure, reliable, and self-adaptive computing systems, covering both the hardware as well as the software aspects of the systems.

   An embedded system is an application-specific computing system found inside products such as home appliances, mobile handheld personal systems, instrumentation, automobiles, aircraft, missiles, satellites, and nuclear power plants. Embedded systems are distinguished from general-purpose computing systems by their well-defined functionalities and stringent design constraints. Embedded systems encompass all the four fundamental operational capabilities required to interface with the world at large - sensing, computing, control, and communication - which can now be integrated with single-chip multiprocessors. The ability to combine operational capabilities in this way has opened new possibilities for application-specific computing.

1. Future directions
   Machine learning and Deep learning

   In recent years, the integration of machine learning (ML) and deep learning (DL) technologies into healthcare has shown remarkable promise in transforming the landscape of medical diagnosis, treatment, and patient care. Machine learning and deep learning, subsets of artificial intelligence, have emerged as powerful tools in processing vast amounts of healthcare data. From medical imaging to predictive analytics, these technologies are revolutionizing how healthcare professionals approach diagnosis and treatment.

2. Applications in Medical Imaging

   One of the notable contributions of ML and DL in healthcare is in medical imaging interpretation. Deep learning algorithms excel in tasks such as image recognition and segmentation, aiding in the early detection of diseases. Examples include the use of convolutional neural networks (CNNs) for identifying anomalies in radiological images, improving the accuracy and efficiency of diagnostics.

3. Predictive Analytics for Disease Prevention

   ML models are increasingly being employed to analyze patient data, predict disease risk, and recommend preventive measures. By processing electronic health records, genetic information, and lifestyle data, predictive models can identify patterns and provide personalized health recommendations. This proactive approach holds the potential to significantly reduce the burden of chronic diseases.

4. Drug discovery and Development

   In pharmaceutical research, ML and DL contribute to the acceleration of drug discovery processes. Predictive modeling aids in identifying potential drug candidates, optimizing clinical trial designs, and predicting patient responses to specific treatments. These advancements streamline the drug development pipeline, leading to faster and more cost-effective solutions.

Google Scholar: https://scholar.google.co.in/citations?user=jk9_oa8AAAAJ&hl=en

1. Signal Processing

   Signal Processing is the technique in which real-world analog signals are interpreted, using digital software and algorithms. The research area of Communications and Signal Processing is dedicated to addressing the challenges associated with the efficient processing and transmission of data. This research encompasses various sources of data, such as sound, images and sensor output signals.

   Objectives of Signal Processing Applications:

   1. Taking decisions in voice interpretation (identification of the portion with high energy, in a speech)

   2. Identifying phonetics (using spectrograms for identifying phonetics)

   3. Identifying gender (LPC or linear predictive coding estimate for gender identification)

   4. Identifying control words (audio tape system controlled by voice)

   5. Analysing formants (using spectrograms and fast Fourier transform)

   6. Identifying formants (using discrete cosine transform or DCT)

   The key research domains, with some examples:

   1. Modelling of Digital Hearing Assistance

   2. EEG based Multiple Epileptic Seizure Detection

   3. Multimodal Speech Recognition and Processing

   4. Real-time Brain Activity Prediction and Analysis

   5. ML approaches for Bio-signals Analysis

2. Image Processing, AI and ML

   In today’s world, it is difficult for humans to handle enormous data and interpret them to take complex decisions. Artificial Intelligence (AI) is the basis for mimicking human intelligence processes, through the creation and application of algorithms built into a dynamic computing environment. Machine Learning (ML) has become one of most widely used AI techniques for several companies, institutions and individuals who are in the business of automation. This is because of considerable improvements in the access to data and increase in computational power, which allow practitioners to achieve meaningful results across several areas.

   Image processing is the process of converting an image to a digital format, and then performing various operations on it to gather useful information. In recent years, Artificial Intelligence (AI) and Machine Learning (ML) have had a huge influence on various fields of technology. Computer vision, the ability of computers to understand images and videos on their own, is one of the top trends in this industry. The popularity of computer vision is growing, and its application is spanning across industries like automobiles, consumer electronics, retail, manufacturing and many more. Some of the familiar use cases that leverage ML image processing techniques are Medical Imaging / Visualization, Law Enforcement & Security, Self-Driving Technology, Gaming, Image Restoration & Sharpening, Pattern Recognition, Image Retrieval etc.

1. Thin film photovoltaics and Photoelectrochemical cells

   Thin films play a vital role in materials science because it has various applications in solar power harvesting, photoelectrochemical cells, sensors (IR, Bio and optical, etc). Advances in this area contribute significantly to the development of more efficient and versatile solar cells devices. Exploring new materials with enhanced photovoltaic properties and incorporating nanostructures for various sensor responses.

2. Nanomaterials for energy storage and photocatalytic applications

   Nanomaterials, with their unique properties at the nanoscale, hold significant promise for developing efficient and sustainable solutions in these areas. This section of the research profile delves into the exciting world of nanomaterials and their applications in both energy storage and photocatalysis.

1. VLSI Design

   Research in this domain focuses on the development of processors for applications that require very high processing speed as well as their implementation onto VLSI. Design methodologies are developed that include novel number systems and allow the parallel processing of signals at the word level and the digit level. Research is conducted in VLSI circuits and computer-aided design, building blocks for new circuit technology, integrated circuit testing and fault diagnosis, digital signal processing, computer-aided synthesis, field programmable gate arrays (FPGAs), and design of low-power circuits.

1. Internet of Things

   ‘Connecting the Unconnected’ through the world of Internet being the main goal of IOT, it has made a huge impact in today’s world. Anytime, Anywhere, Anything – IoT has captured every aspect of human life with vast scope for research as well as challenges, in the near future. As it is connected to the human environment, the major research areas can be in every field such as smart city, smart agriculture, medical field, healthcare, home automation and Industry 4.0.

2. Computer Networks

   A computer network is a network of diverse computing hardware linked through different communication technologies to share various resources. The communication links of the network can be either wired (cables) or wireless (radio waves / IR signals). The areas of research in Wireless Sensor Networks include the following:

   1. Evaluate and implement energy efficient protocol for data aggregation in wireless sensor networks

   2. Node Localization Approach in underwater acoustic network using bio-inspired method

   3. Evaluate and implement sink hole attack isolation method in wireless sensor networks

   4. The three-level hierarchical routing protocol for data aggregation in wireless sensor networks

   5. Design and implement black hole attack isolation method in wireless sensor networks

   The areas of research in Vehicular ad hoc Networks include the following:

   1. Implement and evaluate Sybil attack isolation scheme for vehicular ad hoc networks

   2. Propose novel scheme for the detection of DDOS attack in vehicular ad hoc networks

   3. Zonal based routing scheme for path establishment in vehicular ad hoc networks

   4. Secure and efficient message authentication scheme for vehicular ad hoc networks

   Other areas in Wireless ad hoc Network are:

   1. Propose hybrid routing protocol based on the bio-inspired methods in mobile ad hoc network

   2. Threshold-based mechanism for the isolation of worm hole attack in mobile ad hoc networks

   3. Evaluate and implement clustering-based method for the isolation of black hole attack in mobile ad hoc network

   4. Novel method for congestion avoidance in mobile ad hoc network, to maintain quality of service in the network

3. Signal Processing

   Signal Processing is the technique in which real-world analog signals are interpreted, using digital software and algorithms. The research area of Communications and Signal Processing is dedicated to addressing the challenges associated with the efficient processing and transmission of data. This research encompasses various sources of data, such as sound, images and sensor output signals.

   Objectives of Signal Processing Applications:

   1. Taking decisions in voice interpretation (identification of the portion with high energy, in a speech)

   2. Identifying phonetics (using spectrograms for identifying phonetics)

   3. Identifying gender (LPC or linear predictive coding estimate for gender identification)

   4. Identifying control words (audio tape system controlled by voice)

   5. Analysing formants (using spectrograms and fast Fourier transform)

   6. Identifying formants (using discrete cosine transform or DCT)

   The key research domains, with some examples:

   1. Modelling of Digital Hearing Assistance

   2. EEG based Multiple Epileptic Seizure Detection

   3. Multimodal Speech Recognition and Processing

   4. Real-time Brain Activity Prediction and Analysis

   5. ML approaches for Bio-signals Analysis

4. Entropy

   Entropy is a scientific concept as well as a measurable physical property that is most associated with a state of disorder, randomness or uncertainty. It measures the degree of disorder and uncertainty in the system.

   By using the Tsalis Entropy, we can study and assess the recommended EEG abnormalities through a detection approach using diverse cases, and study the classification of different EEG features and abstraction methodologies. From the features extracted with the different classifiers available, the signal can be classified by different methodologies. The various entropies available for extraction of features are Shannon entropy and Tsalis Entropy. The measure of the uncertainty of occurrence of certain EEG signals, with partial information about the system, can be analysed by using the different entropies.

1. Waste Management

   It is the process or actions required to manage different types of waste (liquid or solid), from source of generation to ultimate disposal or reuse. Liquid waste is an important category of Waste Management because, if it is not properly treated, it leads to environmental pollution. Unlike solid wastes, liquid wastes cannot be easily picked up and removed from an environment. Liquid wastes spread out, and easily pollute other sources of liquid, if come into contact. This type of waste also leads to soil and groundwater pollution.

1. Image processing

   Image Processing (IP) is a computer technology applied to images that helps us process, analyze and extract useful information from them. Advancements in image processing technology are enabling its use for increasingly widespread applications. In medical imaging, there is an increased usage of digital devices in healthcare services for the last few decades because of the advancements made in the medical field. The most appropriate method that is used for the enhancement of security and authentication of medical data is medical image watermarking, which is crucial and used for further diagnosis and reference. Medical image watermarking techniques for the protection and authentication of medical data using hybrid transforms. To develops innovative algorithms in the field of medical imageing using wavelets that is reliable and user friendly.

2. Machine Learning and Deep Learning image processing techniques can become more powerful.

   Deep learning is a subset of machine learning that uses artificial neural networks to learn from data. The process involves feeding a large dataset of images into the network and training it to recognize specific features. Applications of deep learning image processing include image recognition, object detection, image segmentation, and image restoration. To explore deep learning image processing and its potential to revolutionize the future of visual intelligence.

3. Numerical Analysis

   Fluid (Heat and Mass transfer) problems are of critical importance in almost all areas of engineering and technology, especially in mechanical engineering. Over several decades, engineers and scientists have been working on solving these problems by designing and optimizing components and systems needed to transfer, handle, and store thermal energy. Heat transfer problems occur in the form of highly nonlinear differential equations. Moreover, this study says that the wavelet theory will act as a tool to study fluid problems. Also, this method can apply to higher-order equations with slight modifications. This method can be treated as a domain method.

Google Scholar: https://scholar.google.com/citations?user=hj-6hSAAAAAJ&hl=en

ORCID: https://orcid.org/0000-0002-9359-8683

1. Organic Solar Cells

   Organic solar cells, a type of third-generation solar cell, utilize organic materials as light-absorbing materials. These cells have garnered significant attention due to the abundance and tunability of materials, as well as their compatibility with flexible substrates. Efficiencies of up to 17% have been achieved through improvements in device architecture, materials engineering, and solvent techniques. However, enhancing environmental stability alongside power conversion efficiency remains a key challenge. Dr. Reshmi's research focuses on understanding the device physics to uncover efficiency-limiting factors and optimizing interfacial layers to control recombination mechanisms.

2. Perovskite Solar Cells

   Hybrid organic-inorganic perovskite solar cells are attracting considerable interest due to their excellent photovoltaic properties. Perovskite materials exhibit high absorption coefficients, mobility, and diffusion lengths, making them promising candidates for solar cell applications. The efficiency of Perovskite solar cells has increased from 3% to 25%, but stability remains a critical issue for industrialization. Dr. Reshmi's work aims to develop non-toxic, sustainable solar cells with high efficiency and stability. Also, Plasmonic materials will be used to enhance absorption and improve the electrical properties of perovskite solar cells.

1. Wireless Communication for Signal Processing

   Adaptive filters play a very significant role in most of today’s signal processing, communication, and control applications. Their ability to process data under conditions not predictable a priori make them very useful in a diverse array of applications like radar, sonar, wireless communications, speech and audio processing, instrumentation, exploration geophysics etc. Adaptive signal processing for wireless communication which includes blind synchronization and parameter estimation, modulation classification, cooperative communications, physical layer security, cognitive radio, OFDM, SC-FDMA, MIMO, MIMO-OFDM NOMA, mm WAVE, IRS, and sequence design.

1. Internet of Things

   ‘Connecting the Unconnected’ through the world of Internet being the main goal of IOT, it has made a huge impact in today’s world. Anytime, Anywhere, Anything – IoT has captured every aspect of human life with vast scope for research as well as challenges, in the near future. As it is connected to the human environment, the major research areas can be in every field such as smart city, smart agriculture, medical field, healthcare, home automation and Industry 4.0.

2. GPS/INS Integrated System

   All through history, the science of navigation and exploration have played a significant role in the life of mankind. Beginning with seamanship and its unimaginable extension of vast applications such as geomatics, aviation, unmanned vehicles, robotic control and even the medical field, the last few decades have seen a tremendous technology development in the field of GPS and INS. Computation technology and the state of the sensor enhances the applications for both military as well as civilian applications, which include synchronized prototype for marine navigation, hardware guide for dementia patients and visually challenged, besides an algorithm for estimating the spread of the recent Covid19 across the country.

3. Communication Systems

   The recent advances in the area of communication research focus mainly on 5G and 6G Mobile networks, Wireless networks, Quantum Communication, MIMO Technology, Satellite communication. Higher Bandwidth, together with fast data-speeds, can change communication drastically, resulting in increased number of connected devices. AI, along with mobile network security, enables the development of innovative algorithms, architecture that is reliable and user friendly.

1. Electronic and Opto-Electronic Devices

   Finding a new material and tuning its properties are the fascinating research in materials science and nanotechnology. Many materials are commercially introduced for the electronic and opto-electronic device fabrications for day-to-day life applications but still it demands the suitable materials with better performance for the remarkable future devices. Advanced research development is needed for the tuneable material properties via green, chemical and physical methods in order to replace the existing materials for the futuristic transparent electronic and opto-electronic devices.

2. Flexible Gas Sensor and Plasmonic-Nanobiosensor Devices

   The revolution in sensor research activities in instrumentation demands the advancement in the new materials and its properties in order to safeguard from toxic gas exposure to human, environment and avoid the explosion and/or other dangerous accidents. But the demand is for the suitable material for the environmental control and safety purpose in sensors devices for human health concerns. A feasible developments through flexible thin film sensor device is anticipated for the multi target detections against toxic and non-toxic gases at low level concentrations. Further, research extension to be focused onto the fabrication of plasmonic nanobiosensors and smart sensors for the early stage cancer and virus biomarker detection and remote health monitoring for medical applications.

3. Plasmonic Photocatalysis Applications

   A recent prominent research aspects to find a suitable material to preserve the human health and environment. A major concern by the researchers for the remedy for air pollution and water pollution due to its adverse effects to environment and human health. Photocatalytic technology has shown a great potential to convert the harmful organic/inorganic/gases into harmless substances through degradation and detection of dyes/heavy metal in water and gaseous pollutants in air. The percent technology demands the suitable material with remarkable properties from the plasmonic assisted photocatalytic materials to achieve the better performance than existing materials for air pollution and water pollution control systems. Further, research extension to be focussed on to plasmonic photocatalysis for the hydrogen generation.

1. Pattern Recognition

   Pattern recognition is an essential part of Artificial Intelligence. It is the process of classifying data based on predefined patterns or features. It involves the use of algorithms and models to identify unique patterns in data, and then use those patterns to make predictions for new data. One of the most common applications of pattern recognition is in image recognition. Pattern recognition algorithms can be used to recognize objects in images. For example, a facial recognition system can be used to identify people in photographs or videos. Other applications include speech recognition, handwriting recognition and natural language processing.

   Pattern recognition can be supervised or unsupervised. In supervised learning, the algorithm is trained on labelled data, which means that the desired output is provided for each input. In unsupervised learning, however, the algorithm must identify patterns on its own, with no prior knowledge of the desired output. There are several methods used in pattern recognition, including decision trees, neural networks, support vector machines and k-nearest neighbour. Each method has its strengths and weaknesses, and the choice of a particular method depends on the nature of the data and the application.

2. Information Security

   Networking is the backbone of the interconnected world, and cybersecurity is its guardian. Advances in biotechnology have made DNA manipulation and information processing ubiquitous. It is now an essential tool in many fields, including medicine, genomics, forensics and bioengineering. DNA technology increasingly resembles information technology: DNA, like any form of information, can be read (sequenced), written (synthesized), analysed (with bioinformatics utilities), and stored (in genetic databases). However, the increasing computerization of DNA technology, and biotechnology more generally, raises new bio-cyber security concerns. Vulnerabilities that are typically associated with traditional computer systems - like the processing of untrusted input, side-channel leaks, poor authentication, falsified data, and vulnerabilities in cyber-physical systems, now exist in biotechnology.

1. Electric Vehicles

   The research prospects of Electric Vehicles (EVs) hold immense potential for shaping the future of transportation and sustainable energy systems. Advancements in EV technology continue to focus on areas such as battery technology, charging infrastructure, power electronics, energy management systems and grid integration. Research on battery technology aims to enhance energy density, charging speed and lifespan, while research on charging infrastructure focuses on developing efficient and widespread charging networks. Advancements in Power Electronics seek to optimize energy conversion and integration with renewable sources. Energy management systems aim to maximize efficiency and optimize power allocation. Research in Grid integration explores the impact of EVs on the electrical grid, and strategies for stable integration. Overall, ongoing research prospects in EVs are geared towards improving performance, range, convenience and environmental impact, promoting and facilitating the transition to a cleaner and more sustainable future for transportation.

2. Applied Math for Power System and Energy

   The research prospects of Applied Mathematics in power systems and energy, are extensive, and crucial for the efficient operation and optimization of these complex systems. Applied Mathematics provides valuable tools and techniques for modelling, analysing and solving various challenges in the domains of power systems and energy. Research in this field focuses on areas such as optimal power flow, energy scheduling and management, demand- response, grid stability and resilience, renewable energy integration and smart grid technologies. Applied Mathematics enables the development of mathematical models, algorithms and optimization techniques, to address these challenges and improve system performance, reliability and sustainability. By leveraging mathematical principles and computational methods, researchers can take informed decisions, optimize resource allocation, minimize energy losses, and enhance the overall efficiency and resilience of power systems and energy networks. The ongoing research in Applied Mathematics holds the potential to revolutionize the way we generate, distribute and consume energy, paving the way for a more sustainable and resilient energy future.

3. Smart Grid and Micro Grid

   The research prospects of Smart Grids and Microgrids are highly promising in revolutionizing the future of energy systems. Smart Grids refer to modern electricity networks that utilize advanced communication, control and automation technologies, to enable efficient and reliable power delivery. Research in Smart Grids focuses on developing intelligent grid architectures, integrating renewable energy sources, optimizing energy management and storage, implementing demand-response strategies, and enhancing grid resilience and cybersecurity. Microgrids, on the other hand, are localized power systems that can operate independently, or in conjunction with the main grid. Research in Microgrids explores topics such as optimal system design, control strategies, energy sharing and trading, and islanding capabilities. These research areas aim to maximize renewable energy utilization, improve grid reliability, increase energy efficiency, and enable decentralized energy generation and consumption. By furthering Smart Grid and Microgrid technologies, researchers strive to create more sustainable, flexible and resilient energy systems that can adapt to the changing energy demands, reduce greenhouse gas emissions, and promote a landscape of decentralized and democratized energy.

1. RF & Microwave Communications, Antenna Design

   Antenna Design and its analysis, thereafter, is a fundamental part of any Wireless Communication system. In the era of modern Wireless Communication systems. The need of high performance, compact antennas are in the boom, to facilitate multi – level system integration. Planar monopole antennas cater to that requirement. Fractal antennas are particularly intriguing in this aspect. Dielectric Resonators are indispensable in reducing the ohmic losses in the radiators, making them the obvious choice where high gain antennas are necessary, as in Satellite Communication applications. Metamaterial based antennas offer radiation metrics that are unable to attain using conventional structures. This opens an entire avenue for Antenna design flexibility. Perhaps the most recent members of the Metamaterial family are Antennas based on Frequency Selective Surfaces, which act as spatial filters, thereby reinforcing certain frequencies, while blocking some others, in a specific frequency band. Finally, the entire aspect of Antenna Design and Simulation is based upon in depth mathematical modelling, and numerical curve fitting, which are taken care by the domain of Computational Electromagnetics.

1. Computer Networks

   Computer networking refers to interconnected computing devices that can exchange data and share resources with one another. These networked devices use a system of rules called communications protocols, to transmit information over physical or wireless technologies. Intrusion Detection System is one of the research areas in Computer Networks. Some of the most recent areas for computer networks are MANET, Wireless Sensor Networks and Delay Tolerant Networks. Computer networks are used in scientific research, to facilitate collaboration among researchers to share data and information.

2. Cyber Security and Block Chain

   Cybersecurity is the practice of protecting systems and networks from digital attacks which aim to access, change or destroy digital information, to extort either money or sensitive data. With increasing reliance on technology and data, it becomes absolutely necessary to reinforce security measures in order to protect digital data and transactions. Block chain is a shared, decentralized, and digital ledger that records transactions in the form of blocks. This ledger helps to store information transparently, due to its property of immutability and access to allowed members only. This approach reduces vulnerabilities, provides strong encryption, and verifies data ownership and integrity, more effectively. Hence, researchers and practitioners are mindful about the multiple applications of block chain, around areas like human resource, marketing, finance, supply chain etc.

3. Big Data and Data Mining

   Big Data refers to the collection of humongous datasets, such as the datasets within excel sheets, that are too large to enable easy handling. Data Mining refers to the analysis of large data chunks, for extracting relevant and useful information. Data mining is used to explore increasingly large databases and to improve market segmentation. By analysing the relationships between parameters, it is possible to guess their behaviour in order to direct personalised loyalty campaigns. Big data comes to the rescue, when researchers need to analyze large chunks of data. These big data tools also help in the segregation of data for better analysis.

4. AI & Machine Learning, Data Science

   An intelligent computer uses AI to think like a human and perform tasks on its own. Machine Learning is how a computer system develops its intelligence. One way to train a computer to mimic human reasoning is to use a neural network, which is a series of algorithms that are modelled after the human brain. The AI is a simulation of a machine’s natural intelligence that is actually programmed for communicating and learning human actions. The AI-enabled machines can perform human-like tasks, and technologies incorporating AI are continuing to grow. Machine Learning is the part of Artificial Intelligence that allows software applications to become more accurate at predicting outcomes without the need for being explicitly programmed. The Machine Learning algorithms utilize historical data as an input for predicting recent output values. Machine Learning is crucial, as it gives the enterprise a correct view of recent trends in business operation patterns and customer behaviour, and this supports the development of a new product.

1. Polymer Matrix Composites

   Tufting of Laminated Composites is an upcoming research area with a lot of prospects in aerospace structural applications. The tufted laminated composites will enhance the structural stability of load bearing structural panels.

1. Corrosion and Dynamic Characterization of Aluminium Metal Matrix Composites

   Aluminium composites have gained significant research avenues in the marine, automotive and aerospace structures. It will fast replace monolithic metals and give better performance capabilities. This topic has potential scope for further research, especially with respect to corrosion, dynamic characterizations.

1. Contact Phenomena of Cables bent over sheaves

   Contact Mechanics and computational modeling have gained greater significance, especially to develop the new mathematic model to predict the cable failure to reduce the experimentations costs.

1. Natural fiber reinforced polymer composite materials

   These composite materials represent a burgeoning area of research and development in the field of materials science and engineering. These composites leverage the inherent strength, lightweight, and eco-friendly characteristics of natural fibers such as jute, flax, hemp, bamboo, areca and sisal, which are embedded within a polymer matrix. The integration of natural fibers enhances the mechanical properties, including tensile strength, stiffness, and impact resistance, of the resulting composite materials. Additionally, they offer advantages such as reduced production costs, lower density, and biodegradability compared to traditional synthetic fiber composites. Furthermore, natural fiber reinforced polymer composites find application across diverse sectors including automotive, construction, aerospace, and packaging industries, where their sustainable nature aligns with the growing demand for eco-friendly materials. Ongoing research in this field focuses on optimizing fiber-matrix interactions, enhancing composite performance, and exploring novel processing techniques to broaden their applicability and efficacy in various industrial applications.

1. Nano composite

   Nano composites offer unique properties that can be tailored by adjusting the composition, size, and distribution of the nanostructures within the matrix. Some potential advantages of nano composites include enhanced mechanical strength, improved electrical conductivity, increased thermal stability, and enhanced optical properties. These materials find applications in various fields including electronics, aerospace, automotive, biomedical engineering, and environmental remediation, among others. Examples of nano composites include carbon nanotube-reinforced polymers, graphene oxide-based materials, and metal nanoparticle-doped ceramics.

2. Synthesis and characterization of nano materials

   Synthesis and characterization of nanomaterials represent crucial stages in the development of advanced materials with tailored properties at the nanoscale. The synthesis process involves the creation of nanoparticles using various methods such as chemical precipitation, sol-gel synthesis, and template-assisted techniques. These methods allow for precise control over factors like particle size, shape, and composition, enabling the production of nanomaterials with specific properties suited for diverse applications. Following synthesis, rigorous characterization is essential to understand and optimize the nanomaterials' structural, chemical, and physical properties. Techniques such as transmission electron microscopy (TEM), X-ray diffraction (XRD), and spectroscopic analysis provide valuable insights into nanoparticle morphology, crystallinity, and chemical composition.