Assistant Professor
Computer Science and Artificial Intelligence
SRM University-AP
4 Years
VLSI Design
VLSI Design, Neuromorphic Computing, AI and ML, Hybrid Circuit Design Using Memristors
Ph.D in Electronics and Communication Engineering from SRM University-AP, India
M.tech in Nimra College of Engineering and Technology, Vijayawada, JNTUK.
B.tech in Nimra College of Engineering and Technology, Vijayawada, JNTUK.
Assistant Professor at Nimra College of Science and Technology, from 2016-08-21 to 2020-12-20.
PG
UG
P N S B S V Prasad V, Syed Ali Hussain, Pranab Mandal, Biswabandhu Jana, NagaMalleswari Katra- gadda, Ch. Lakshmi Rajyam, and Pradyut Sanki. ”Non-Invasive In-Vivo Detection of Random Blood Glu- cose using Photoacoustic Spectroscopy” 46th Interna- tional Conference on Engineering in Medicine and Bi- ology Conference (EMBC-2025) Accepted
Syed, A. hussain, bevara, vasudeva, & Sanki, P. K. (2021). Performance Analysis of an Efficient Compara- tor Using Memristor-CNTFETs. SPAST Abstracts,
Turja Bhattacharjee, Hussain, Syed Ali, Pradyut Ku- mar Sanki, and Pranab Mandol. Medical Image Clas- sification of Brain Tumour: A Multi-Model Approach With Explainable Models,” 2024 IEEE 16th Interna- tional Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2024. [DOI: 10.1109/CICN63059.2024.10847436]
Billakurthi Sai Sanjana, Bandi Raja Babu, Hussain, Syed Ali, and Pradyut Kumar Sanki. ”ASIC Imple- mentation of Pre-Trained CNN for Image Classification Using GPDK90nm Technology,” 2024 IEEE 16th In- ternational Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2024. [DOI: 10.1109/CICN63059.2024.10847565]
Bandi Raja Babu, Billakurthi Sai Sanjana, Hussain, Syed Ali, and Pradyut Kumar Sanki. ”ASIC Imple- mentation of Pre-Trained CNN for Handwritten Digit Detection Using GPDK90nm Technology,” 2024 IEEE 16th International Conference on Computational Intel- ligence and Communication Networks (CICN). IEEE, 2024. [DOI: 10.1109/CICN63059.2024.10847480]
Hussain, Syed Ali, and Pradyut K. Sanki. ”Design & Implementation of a Hybrid Multiplexer Leverag- ing Memristor and Cntfets.” 36th IEEE International Conference on Microelectronics (ICM), pp. 1-6. IEEE, 2024. [DOI: 10.1109/ICM63406.2024.10815743]
Hussain, Syed Ali, Vasudeva Bevara, and Pradyut K. Sanki. ”A High-speed Low-power CMOS-Memristor Based Hybrid Comparator Using m GDI Technique for IoT Applications.” 2022 IEEE International Sympo- sium on Smart Electronic Systems (iSES). IEEE, 2022. [DOI: 10.1109/iSES54909.2022.00139]
Kamala Kumari Durua, Praneash Venkatachalamb, Hus- sain, Syed Ali, Asha Anish Madhavand, Sangaraju Sambasivame, Sujith Kalluri ”Optimal Charging of Lithium- Ion Batteries: An Electro-Thermal Model Approach Using Maximum Possible Optimization.” Advanced The- ory and Simulations (2025): 2500320. [DOI: 10.1002/adts.202500320] [SCI-Q1]
Yamini, Vanama, Syed Ali Hussain, G. Chandra Sekhar, P. Avinash Kumar, P. Lehitha, B. Sree Venkata Teja, Swagata Samanta, and Pradyut Kumar Sanki. ”An SoC System for Real-Time Edge Detection.” Journal of Electronic Materials (2024): 1-8. [DOI: 10.1007/s11664-024-11255-x] [SCI-Q2]
Bevara Vasudeva, Syed Alihussain, P. N. S. B. S. V. Prasad, and Pradyut K. Sanki. ”Design of an efficient QCA-based median filter with energy dissipation anal- ysis.” The Journal of Supercomputing 79, no. 3 (2023): 2984-3004. [DOI: 10.1007/s11227-022-04780-1] [SCI-Q2]
Prasad, P.N.S.B.S.V., Hussain, Syed Ali., Thotakura, P. et al. Design and Development of an IoT-Based Embedded System for Continuous Monitoring of Vital Signs. J. Electron. Mater. (2024). DOI: 10.1007/s11664-024-11368-3 [SCI-Q2]
P. N. S. B. S. V. Prasad V, Hussain, Syed Ali, Amrit Kumar Singha, Biswabandhu Jana, Pranab Mandal, and Pradyut Sanki. ”An advanced IoT-based non- invasive in vivo blood glucose estimation exploiting photoacoustic spectroscopy with SDNN architecture.” Sensors and Actuators A: Physical (2025): 116391. DOI: 10.1016/j.sna.2025.116391 [SCI-Q1]
Hussain, Syed Ali, P. N. S. B. S. V. Prasad V, Rohith Kodali, Lokesh Rapaka, and Pradyut Kumar Sanki. ”Predicting and Categorizing Air Pressure System Fail- ures in Scania Trucks using Machine Learning.” Jour- nal of Electronic Materials (2024): 1-11. [DOI: 10.1007/s11664-024-11115-8] [SCI-Q2]
Hussain, Syed Ali, P. N. S. B. S. V. Prasad V, Swikriti Khadke, Pragya Gupta, and Pradyut Kumar Sanki. ”Innovative Web Application Revolutionizing Disease Detection, Empowering Users and Ensuring Accurate Diagnosis.” Journal of Electronic Materials (2024):1-9. [DOI: 10.1007/s11664-024-11092-y] [SCI-Q2]
Hussain, Syed Ali, Nandini Chalicham, Likhita Garine, Shushma Chunduru, V. N. V. S. L. Nikitha, P. N. S. B. S. V. Prasad V, and Pradyut Kumar Sanki. ”Low- Light Image Restoration Using a Convolutional Neural Network.” Journal of Electronic Materials (2024):1-12. [DOI: 10.1007/s11664-024-11079-9] [SCI-Q2]
Hussain, Syed Ali, Karnatapu Sri Sai Dhanush, Kothuri Abhinav Eswar, Chundru Vaishnavi, Kaveti Sujith Surya, P. N. S. B. S. V. Prasad V, Swagata Samanta, and Pradyut Kumar Sanki. ”Leaky Integrate-and-Fire Neu- ron Model-Based SNN Latency Estimation Using FNS.” Journal of Electronic Materials (2024): 1-9. [DOI: 10.1007/s11664-024-11078-w] [SCI-Q2]
Hussain, Syed Ali, P. N. S. B. S. V. Prasad V, and Pradyut Kumar Sanki. ”Synergistic m GDI-based ALU Design Using CMOS and VTEAM Memristor Model for Low-Power High-Speed Applications.” Journal of Electronic Materials 53, no. 7 (2024): 3626-3641. [DOI:10.1007/s11664-024-11125-6] [SCI-Q2]
Hussain, Syed Ali, Prasad V, P. N. S. B. S. V., and Pradyut Kumar Sanki. ”Efficient in situ learning of hybrid LIF neurons using WTA mechanism for high- speed low-power neuromorphic systems.” Physica Scripta 99, no. 10 (2024): 106010. [DOI: 10.1088/1402-4896/ad79c5] [SCI-Q2]
Prasad V, P. N. S. B. S. V., Ali Hussain Syed, Mudigonda Himansh, Biswabandhu Jana, Pranab Mandal, and Pradyut Kumar Sanki. ”Augmenting authenticity for non-invasive in vivo detection of random blood glucose with pho- toacoustic spectroscopy using Kernel-based ridge re- gression.” Nature Scientific Reports 14, no. 1 (2024): 8352. [DOI: 10.1038/s41598-024-53691-z] [SCI-Q1]
The innovation is an enhancement of the hybridization procedure that employs memristors and CNTFETs in binary representation. Previously, CNTFETs were used to implement tri-state logic in hybrid notation. However, there is no such binary logic implementation using CNTFETs along with memristors in hybrid mode. The Hybridisation framework gives enough comparability to gain the benefits of more than one technology. Because CMOS circuits are compatible with memristors, CNTFETs are likewise compatible with memristors as described
An object of the present disclosure is to provide a system for the non-invasive measurement of glucose concentration in a human body. Another object of the present disclosure is to provide a system to measure glucose concentration in the human body. Still another object of the present disclosure is to provide a system to determine the concentration of a particular component in a biological sample in Vivo. It provide a system to utilize photoacoustic spectroscopy to enable the measurement of the concentration of analytics.
The present disclosure further relates to a piezoelectric sensor and a process for its preparation. The piezoelectric sensor of the present disclosure is lead-free, has higher piezoelectric coefficients due to BZT-BCT material, tunable piezoelectric and ferroelectric properties, and is capable of working at a broad range of sintering temperatures.
The invention is a design & development of a hybrid modified Gate Diffusion Input (m_GDI) basic cell consists of PMOS and Memristor together as the circuit component. Many m_GDI circuit models have been proposed using only CMOS, with no further proposals of the m_GDI technique in hybrid mode as we proposed. The paradigm in this proposal enables the benefits of both hybridization and m_GDI approach together. The hybridization framework gives enough compatibility to gain the benefits of more than one technology
The present invention proposes a synergistic methodology for generating buy and sell indicators that leverages both technical analysis and sentimental analysis. The proposed approach utilizes key technical indicators such as Volume-Weighted Average Price (VWAP), Relative Strength Index (RSI), and Ichimoku cloud to facilitate the generation of these indicators. Through the coordinated use of these indicators, the invention offers a highly integrated and sophisticated approach to trading that can assist traders.
The innovation is an enhancement to revolutionize disease detection and provide a reliable source of information for users seeking accurate diagnoses for their symptoms. Our open-source project combines user-friendly interface design with state-of-the-art machine learning models, establishing a benchmark for accuracy and enabling integration with even higher-performing models. By eliminating the risks of misinformation and misdiagnosis often encountered when searching symptoms on popular search engines.
The IOT-based water bottle for cold and hot dual water storage with temperature monitoring is a cutting-edge innovation in hydration technology. This advanced water bottle offers a range of features that ensure convenient access to both cold and hot water while keeping track of its temperature at all times. We have developed an innovative solution to address a common everyday problem using the Peltier effect as the foundation of our invention. Utilizing a Peltier device, a remarkable semiconductor with the unique capability.
This invention is a combination of both software and Hardware. Now a days we have been hearing that Vandebharat express train hits cow, causing damage to both railways and cattle owners. We need to find a solution to this problem. These issues shouldn’t be hurdle for the growth of technology for developing countries like india. The technology we are going to use is a belt is worn by a cow. When the cow tries to near railway track it receives a Non-Lethal shock, makes the cow to scare and move back.
The fast-growing logistics and e-commerce era has increased demand for delivery services that are both quick and reliable, prompting companies to find new ways to improve efficiency and customer satisfaction. However, current drone delivery systems face limitations such as unreliable battery life, complex navigation challenges, and failsafe mechanisms that can result in delays or incomplete deliveries. Our platform proposes designated rally points as staging areas for continuous and efficient delivery operations.
Rapid urbanization and increasing transportation demands have fuelled the need for efficient, fast, and reliable urban air mobility (UAM) systems. However, existing air taxi solutions face significant challenges such as limited battery life, navigation difficulties in dense urban environments, and passenger security. Our invention addresses these limitations by proposing an autonomous air taxi system with designated mid-flight charging stations (referred to as rally points) and secure OTP (One-Time Password) authentication.
In the era of e-commerce, even though the growth is substantial, Online frauds have also increased causing the companies to plunge into loss and bringing black mark on companies. This invention is bringing up two different field applications and combining them to use for the novel cause called Anti-counterfeiting. This invented product is a water-soluble sticker attached to the goods. Throughout this draft for easy understanding, we have considered the clothes as an example.
With the rapid growth of urban transportation, efficient and timely delivery solutions are seen as essential for overcoming challenges such as ground congestion and the need for faster, more effective logistics networks. Drone delivery systems are gaining prominence as a solution, but they face constraints such as limited battery life and a lack of adequate charging infrastructure in urban environments. Our invention fully focussed on a Rally Points-Based Charging System tailored to address these challenges, enabling drones.
In developing this technique, an experiment was conducted using synthetic cholesterol obtained commercially, serving as a proof of concept for the method’s effectiveness. This synthetic sample exhibited the same distinct absorption peaks, validating the approach and confirming that FTIR spectroscopy can successfully detect and analyze cholesterol's spectral features. This foundational work paves the way for creating a portable and user-friendly cholesterol detection device, with potential for widespread application in clinic
The system's foundation is built on cutting-edge deep learning models, specifically Temporal Convolutional Networks (TCN) and Bidirectional Long Short-Term Memory (BiLSTM), which have been optimized to achieve a high accuracy of 98.26% in eye blink classification. Unlike conventional EEG-based control systems, which are prone to high false activation rates and signal inconsistencies, this system incorporates a visual stimulus-based validation mechanism to ensure that only intentional blinks are detected and processed.
This invention is a dual-drone autonomous system designed specifically for disaster response operations in flooded or inaccessible terrains. It is a hybrid of hardware, software, and cloud-based coordination, where two drones work in tandem to achieve rapid search, identification, and relief delivery. The Scout Drone autonomously surveys a predefined area, detects human presence using onboard computer vision, geotags each survivor’s location in real-time, and uploads the coordinates to a cloud server.
Received Gold Medal from the SRM University on 5th Research Day-2022.
Honored as a Reviewer for the prestigious journal "Scientific Reports"
