Dr. Mohammed Ali Shaik
Associate Professor
School of Computer Science & Artificial Intelligence
Dr. APJ. Abdul Kalam University
17 Years
Programming
Deep Learning, Data Mining, Cloud Computing
Mail: ali@sru.edu.in
Associate Professor
School of Computer Science & Artificial Intelligence
Dr. APJ. Abdul Kalam University
17 Years
Programming
Deep Learning, Data Mining, Cloud Computing
Mail: ali@sru.edu.in
Ph.D from Dr. APJ. Abdul Kalam University, Indore (M.P.)
M.Tech from Aurora's Research & Technological Institute, Warangal and MCA from University PG College, Hanamkonda
BCA from Masterji Degree & PG College, Hanamkonda
Assistant Professor at SR University, Warangal, from 2018-06-04 to .
Assistant Professor at Aurora's Research & Technological Institute, from 2007-11-05 to 2018-06-02.
Jr. Testing Engineer at Lending Space Pvt. Ltd., from 2006-06-01 to 2007-10-05.
Ph.D
PG
UG
D. Ramakrishna and M. Ali Shaik, "A Comprehensive Analysis of Cryptographic Algorithms: Evaluating Security, Efficiency, and Future Challenges," in IEEE Access, vol. 13, pp. 11576-11593, 2025, doi: 10.1109/ACCESS.2024.3518533
M. A. Shaik, G. Rakshitha, K. Saipriya, T. Thrisha, M. Varshini and J. G. Sai, "Machine Learning for Detecting the Phishing Threats," 2025 6th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI), Goathgaun, Nepal, 2025, pp. 1221-1226, doi: 10.1109/ICMCSI64620.2025.10883227.
M. A. Shaik, A. Fatima, M. Parveen, A. Soumya Rani, A. Mohammad and A. Rahim, "Dual-Model Approach for Lung Disease Classification Using Convolutional Neural Networks and Support Vector Machines," 2024 International Conference on Integrated Intelligence and Communication Systems (ICIICS), Kalaburagi, India, 2024, pp. 1-6, doi: 10.1109/ICIICS63763.2024.10860090.
M. Ali Shaik, P. Sairam, P. Rahul, T. Sadhvik and P. Nithin, "Titanic Survival Predictor Using Machine Learning Algorithms," 2024 4th Asian Conference on Innovation in Technology (ASIANCON), Pimari Chinchwad, India, 2024, pp. 1-6, doi: 10.1109/ASIANCON62057.2024.10837935.
M. A. Shaik and E. Ravithreyini, "Enhanced BreastNet Architecture and Comparison with State-of-the-Art Models," 2024 5th International Conference on Data Intelligence and Cognitive Informatics (ICDICI), Tirunelveli, India, 2024, pp. 604-608, doi: 10.1109/ICDICI62993.2024.10810949.
M. A. Shaik, A. Kethireddy, S. Nerella, S. Pinninti, V. Kathare and P. Pitta, “Sound Wave Scribe: Bridging Spoken Language and Written Text”, 2024 First International Conference on Pioneering Developments in Computer Science & Digital Technologies (IC2SDT), Delhi, India, 2024, pp. 413-417, doi: 10.1109/IC2SDT62152.2024.10696694.
M. A. Shaik and N. L. Sri, “A Comparison of Stock Price Prediction Using Machine Learning Techniques”, 2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC), Coimbatore, India, 2024, pp. 1-5, doi: 10.1109/ICESC60852.2024.10689767.
M. A. Shaik, M. Parveen and I. Qureshi, “Leveraging Machine Learning and Drone Technology for Effective Insect Pest Management in Agriculture”, 2024 Asia Pacific Conference on Innovation in Technology (APCIT), MYSORE, India, 2024, pp. 1-8, doi: 10.1109/APCIT62007.2024.10673597.
M. A. Shaik, Y. Sahithi, M. Nishitha, R. Reethika, K. S. Teja and C. P. Reddy, “Realtime Emotion Recognition from Images to Understand Facial Expressions”, 2024 Asia Pacific Conference on Innovation in Technology (APCIT), MYSORE, India, 2024, pp. 1-5, doi: 10.1109/APCIT62007.2024.10673486.
Mohammed Ali Shaik, Praveen Pappula, T. Sampath Kumar, Battu Chiranjeevi, “Ensemble model based prediction of hypothyroid disease using through ML approaches”, International Conference on Research in Sciences, Engineering, and Technology, AIP Conf. Proc., 2971, 020038 (2024), https://doi.org/10.1063/5.0196055
Mohammed Ali, P. Praveen, Sampath Kumar, Sallauddin Mohmmad, M. Sruthi, “A survey report on cloud based cryptography and steganography procedures”, International Conference on Research in Sciences, Engineering, and Technology, AIP Conf. Proc. 2971, 020040-1–020040-8; https://doi.org/10.1063/5.0196050
Mohammed Ali Shaik, P. Praveen, T. Sampath Kumar, Masrath Parveen, Swetha Mucha, "Machine learning based approach for predicting house price in real estate", International Conference on Research in Sciences, Engineering, and Technology, AIP Conf. Proc. 2971, 020041-1–020041-5; https://doi.org/10.1063/5.0196051
M. A. Shaik, Y. Sahithi, M. Nishitha, R. Reethika, K. Sumanth Teja and P. Reddy, "Comparative Analysis of Emotion Classification using TF-IDF Vector," 2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS), Erode, India, 2023, pp. 442-447, doi: 10.1109/ICSSAS57918.2023.10331897.
M. A. Shaik, M. Azam, T. Sindhu, K. Abhilash, A. Mallala and A. Ganesh, "Hand Gesture Based Food Ordering System," 2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS), Erode, India, 2023, pp. 867-872, doi: 10.1109/ICSSAS57918.2023.10331637.
M. Parveen and M. A. Shaik, "Review on Penetration Testing Techniques in Cyber security," 2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), Trichy, India, 2023, pp. 1265-1270, doi: 10.1109/ICAISS58487.2023.10250659.
M. A. Shaik, R. Sreeja, S. Zainab, P. S. Sowmya, T. Akshay and S. Sindhu, “Improving Accuracy of Heart Disease Prediction through Machine Learning Algorithms”, 2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA), Uttarakhand, India, 2023, pp. 41-46, doi: 10.1109/ICIDCA56705.2023.10100244.
M. A. Shaik, M. Y. Sree, S. S. Vyshnavi, T. Ganesh, D. Sushmitha and N. Shreya, “Fake News Detection using NLP”, 2023 International Conference on Inovative Data Communication Technologies and Application (ICIDCA), Uttarakhand, India, 2023, pp. 399-405, doi: 10.1109/ICIDCA56705.2023.10100305.
Mohammed Ali Shaik, M. Varshith, S. SriVyshnavi, N. Sanjana and R. Sujith, “Laptop Price Prediction using Machine Learning Algorithms”, 2022 International Conference on Emerging Trends in Engineering and Medical Sciences (ICETEMS), Nagpur, India, 2022, pp. 226-231, doi: 10.1109/ICETEMS56252.2022.10093357.
Mohammed Ali Shaik, Praveen Pappula, T Sampath Kumar, "Predicting Hypothyroid Disease using Ensemble Models through Machine Learning Approach", European Journal of Molecular & Clinical Medicine, 2022, Volume 9, Issue 7, Pages 6738-6745. https://ejmcm.com/article_21010.html
Mohammed Ali Shaik, T. Sampath Kumar, P. Praveen, R. Vijayaprakash, “Research on Multi-Agent Experiment in Clustering”, International Journal of Recent Technology and Engineering (IJRTE), ISSN:2277-3878,Volume-8,Issue-1S4, June2019. Pp. 1126-1129.
Mohammed Ali Shaik, “A Survey of Multi-Agent Management Systems for Time Series Data Prediction”, International Journal of Grid and Distributed Computing (IJGDC), ISSN:2005-4262,Volume-12,Issue-3 (2019), Pp.166-171.
Mohammed Ali Shaik, V. Sudharani, “Forth Factor Authentication: Who Am I”, International Journal of Scientific & Engineering Research, Vol.7, Issue8, August-2016, ISSN 2229-5518, pp. 1025-1029.
Mohammed Ali Shaik, P. Praveen, R. Vijaya Prakash, “Novel Classification Scheme for Multi Agents”, Asian Journal of Computer Science and Technology, ISSN: 2249-0701Vol.8 No.S3, 2019, pp.54-58.
V. Sudha Rani, Mohammed Ali. Shaik, “IMPLEMENTATION OF USER FRIENDLY TEXT MESSAGING”, International Journal of Emerging Trends and Technology in Computer Science (IJETTCS), Volume 2, Issue 4, July–August 2013, ISSN:2278-6856, pp.085-092.
Imran Qureshi, Mohammed Ali Shaik, Kanchi Suresh, G.RamaMurthy, “A Data Mining Approach for Unification of Association Rules in Distribute and Parallel Databases”, International Journal of Emerging Trends and Technology in Computer Science (IJETTCS), Volume3, Issue 3, May–June2014, ISSN: 2278-6856, pp.184-188.
Mohammed Ali Shaik, S. k. Koppula, M. Rafiuddin and B. S. Preethi, "COVID-19 Detector Using Deep Learning," 2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 2022, pp. 443-449, doi: 10.1109/ICAAIC53929.2022.9792694.
P Praveen, M Ranjith Kumar, Mohammed Ali Shaik, R Ravi kumar and R Kiran, (2020), The comparative study on agglomerative hierarchical clustering using numerical data, 2020 IOP Conf. Ser.: Mater. Sci. Eng. 981 022071, doi.org/10.1088/1757-899X/981/2/022071
Mohammed Ali Shaik, P. Praveen, “A Survey on Various Clustering Algorithms Using Nature Inspired Algorithms”, Journal of Mechanics Of Continua And Mathematical Sciences, Vol.-15, No.-7, July (2020) pp. 282-293 ISSN (Print) 0973-8975, DOI NO: doi.org/10.26782/jmcms.2020.07.00023
Mohammed Ali Shaik, “Time Series Forecasting using Vector quantization”, International Journal of Advanced Science and Technology (IJAST), ISSN:2005-4238,Volume-29,Issue-4 (2020), Pp.169-175.
Mohammed Ali Shaik, “Time Series Forecasting using Vector quantization”, International Journal of Advanced Science and Technology (IJAST), ISSN:2005-4238,Volume-29,Issue-4 (2020), Pp.169-175.
T. Sampath Kumar, B. Manjula, Mohammed Ali Shaik, Dr. P. Praveen, “A Comprehensive Study on Single Signon Technique”, International Journal of Advanced Science and Technology (IJAST), ISSN: 2005-4238, E-ISSN:2207-6360, Vol-127June-2019, pp. 435-441.
Imran Qureshi, Mohammed Ali Shaik, Kanchi Suresh, G.RamaMurthy, “Designing Parallel and Distributed Algorithms for Data Mining and Unification of Association Rule”, International Journal of Advances in Engineering Science and Technology (IJAEST),Volume3, Issue3, 2014, ISSN: 2319-1120, pp.157-163.
Mohammed Ali. Shaik, S.Narasimha Rao, Abdul Rahim, “A SURVEY OF TIME SERIES DATA PREDICTION ON SHOPPING MALL”, Indian Journal of Computer Science and Engineering (IJCSE), Volume 4 No.2 Apr-May 2013, ISSN:0976-5166, pp.174-184.
Shabana, Sallauddin Mohmmad, Mohammed Ali Shaik, K Mahender, Ranganath Kanakam and Bonthala Prabhanjan Yadav, (2020), Average Response Time (ART):Real-Time Traffic Management in VFC Enabled Smart Cities, 2020 IOP Conf. Ser.: Mater.Sci.Eng.981 022054, doi.org/10.1088/1757-899X/981/2/022054
Sallauddin Mohmmad, Mohammed Ali Shaik, Ramesh Dadi, Syed Nawaz Pasha, Shabana and BonthalaPrabhanjan Yadav, (2020), Time for relative velocity optimal time approach in internet of vehicle communication, 2020 IOP Conf. Ser.: Mater. Sci. Eng. 981 022053, doi.org/10.1088/1757-899X/981/2/022053
Imran Qureshi, Burhanuddin Mohammad, Mohammed Abdul Habeeb and Mohammed Ali Shaik, (2020), Mathematical model for implementing Non Linear Time Series Forecasting using Deep Learning, 2020 IOP Conf. Ser.: Mater. Sci. Eng. 981 022021, doi.org/10.1088/1757-899X/981/2/022021
Mohammed Ali Shaik and Dhanraj Verma, (2020), Deep learning time series to forecast COVID-19 active cases in INDIA: A comparative study, 2020 IOP Conf. Ser.:Mater.Sci.Eng. 981 022041, doi.org/10.1088/1757-899X/981/2/022041
Mohammed Ali Shaik, Dhanraj Verma, P Praveen, K Ranganath and Bonthala Prabhanjan Yadav, (2020), RNN based prediction of spatiotemporal data mining, 2020 IOP Conf. Ser.: Mater. Sci. Eng. 981 022027, doi.org/10.1088/1757-899X/981/2/022027
Mohammed Ali Shaik and Dhanraj Verma, (2020), Enhanced ANN training model to smooth and time series forecast, 2020 IOP Conf. Ser.: Mater. Sci. Eng. 981 022038, doi.org/10.1088/1757-899X/981/2/022038
Mohammed Ali Shaik, Dhanraj Verma, (2021), Agent-MB-DivClues: Multi Agent Mean based Divisive Clustering, Ilkogretim Online - Elementary Education, Vol 20(5), pp. 5597-5603, doi:10.17051/ilkonline.2021.05.629
G. Ranadheer Reddy, V.Pranathi, Mohammed Ali Shaik, T Chandra Prakash and V.Renuka, "An medical image analysis by deep learning", Iternational Conference on Research in Sciences, Engineering & Technology, AIP Conf. Proc. 2418, 020033-1–020033-6; https://doi.org/10.1063/5.0083703, Published by AIP Publishing. 978-0-7354-4368-6, pp. 020033-1 to 020033-5
Sallauddin Mohmmad, Ramesh Dadi, Kothandaraman D 1, E. Sudarshan, Syed Nawaz Pasha and Mohammed Ali Shaik, "A survey machine learning based object detections in an image", International Conference on Research in Sciences, Engineering & Technology, AIP Conf. Proc. 2418, 020024-1–020024-9; https://doi.org/10.1063/5.0081892, Published by AIP Publishing. 978-0-7354-4368-6, Pp: 020024-1 to 020024-9
Mohammed Ali Shaik, Geetha Manoharan, B Prashanth, NuneAkhil, Anumandla Akash and Thudi Raja Shekhar Reddy,"Prediction of Crop Yield using Machine Learning", International Conference on Research in Sciences, Engineering & Technology, AIP Conf. Proc. 2418, 020072-1–020072-8; https://doi.org/10.1063/5.0081726, Published by AIP Publishing. 978-0-7354-4368-6, pp. 020072-1 to 020072-8
Mohammed Ali Shaik, MD.Riyaz Ahmed, M. Sai Ram and G. Ranadheer Reddy, "Imposing Security in the Video Surveillance", International Conference on Research in Sciences, Engineering & Technology, AIP Conf. Proc. 2418, 020012-1–020012-8; https://doi.org/10.1063/5.0081720, Published by AIP Publishing. 978-0-7354-4368-6, pp. 020012-1 to 020012-8.
Mohammed Ali Shaik and Dhanraj Verma, "Predicting Present Day Mobile Phone Sales using Time Series based Hybrid Prediction Model", International Conference on Research in Sciences, Engineering & Technology, AIP Conf. Proc. 2418, 020073-1–020073-9; https://doi.org/10.1063/5.0081722, Published by AIP Publishing. 978-0-7354-4368-6, pp. 020073-1 to 020073-9
Mohammed Ali Shaik and Dhanraj Verma, "Prediction of Heart Disease using Swarm Intelligence based Machine Learning Algorithms", International Conference on Research in Sciences, Engineering & Technology, AIP Conf. Proc. 2418, 020025-1–020025-9; https://doi.org/10.1063/5.0081719, Published by AIP Publishing. 978-0-7354-4368-6, pp. 020025-1 to 020025-9
Disclosed is a cotton-leaf disease recognition system (100) comprising, an image processing module (118) to pre -process a captured cotton-leaf image; a segmentation module (120) to segment the pre -processed image into segments by using
The covering means (100) for outdoor arenas is made of combining plurality of 2 -3 mm thickness particle foam Thermoplastic Polyurethane (TPU) mats. The Thermoplastic polyurethane is integrated with many feat ures including of rubber and p
This Invention comprises of methods to produce novel and efficient methods to implement search of data objects in various applications. It is based on the best match search to implement proximity or best match search over complex or more th
According to an aspect of the invention a Mean Base Divisive Clustering (MB-DivClues) method for categorizing unstructured data into various groups is disclosed. The constructive mean-based divisive clustering method is developed to reduce
The present invention relates to the use of Generative Adversarial Networks (GANs) for generating images and associated text. The invention includes a computer-implemented method and system for training a GAN with a generator network and a discriminator network using a dataset of images and associated captions, and generating a synthetic image and corresponding caption using the trained generator network. The invention enables the generation of realistic images and text that can be used for a wide range of applications,
A system for detection of coronavirus in users, comprising: a processor located on an application server and a storage medium is proposed which comprises of an image receiving module configured to receive a medical image; a feature extraction module is configured to extract features from the received medical image based on a training image set by using deep learning training models; a coronavirus detection module configured to detect the coronavirus in the users by correlating the extracted features of the received medical
A system for predicting hypothyroid disease using ensemble models is disclosed. The system comprises a processor situated on an application server and a storage medium housing executable programming instructions for the processor. The storage medium encompasses a data pre-processing module tasked with refining a dataset from a predefined repository, eliminating noisy and missing data, and subsequently segmenting it into training and testing subsets. Additionally, a feature
The present invention discloses a fan glider designed for efficiently cleaning a fan. The fan glider includes a user-friendly stick for comfortable grip, a dust collector located on the stick capable of radial expansion for effective dust collection, and a claw positioned at a distal end on the stick to securely receive the fan blade. The claw incorporates a cleaning pad for thorough cleaning. Additionally, the fan glider features a gripping mechanism to prevent fan rotation
A system for personalized prediction and precautionary guidance for epilepsy disease using machine learning techniques is disclosed. The system comprising: an input unit and a processing unit configured to: receive the user inputs from the input unit; extract features from the received user inputs using preprocessing techniques; apply a plurality of machine learning models based on the extracted features to predict a likelihood of epileptic seizures by each of the plurality of machine learning methods.
A system for identity based remote data integrity checking with data dynamics and public auditing in the cloud is disclosed. The system comprises a cloud server adapted to store files belonging to a data owner, alongside a user device enabling access to these files. Additionally, a trusted Key Generation Center (KGC) is integrated to generate a secret key, allowing the data owner secure access to the files stored in the cloud server. A third-party auditor is included to initiate audi
A system for balancing accuracy for secure cloud transactions is disclosed. The system comprising: a computing device adapted to receive a transaction request from a user device wherein the computing device is configured to: enable a user to enter login credentials using the user device authenticate the user device based on the entered credentials; receive transaction details including a data, policies, and credentials associated with the transaction request; execute a Two-Phase Validation Commit (2PVC) protocol.
A system for enhancing accessibility of visual content is disclosed. The system comprising: an input device and a processor configured to: receive the visual content from the input device extract visual features from the received visual content using a pre-trained visual geometry group (VGG) 16 model; process the extracted visual features using a long short-term memory (LSTM) network to generate a textual description of the visual content; generate the textual description based on a database of caption information associate
A decision tree machine learning framework to detect bearing faults via vibrational signals is disclosed. The framework comprising: a test bearing worn on a shaft. The shaft is connected to a motor using a coupler and the motor is adapted to rotate the shaft bearing the test bearing at a standard velocity. An accelerometer is adapted to capture vibration data in the test bearing while in rotation. A microphone is adapted to capture noise data in the test bearing while in the rotation.
A solar panel maintenance system is disclosed. The system comprises distributed sensors arranged proximate to a solar panel to monitor operational and condition parameters. A robotic cleaner navigates a solar array for performing cleaning mechanisms. The system further comprises a control unit that receives data from the distributed sensors. The system analyzes the received data to assess panel cleanliness, dynamically adjusts cleaning schedules and routes, and actuating a robotic cleaner accordingly. This system is capable
The present invention relates to handwriting generation systems, specifically to a system that mimics the handwriting of an individual using advanced machine learning techniques such as convolutional neural networks (CNN), recurrent neural networks (RNN), and generative adversarial networks (GAN). This system is designed to generate a user’s handwriting style for any provided text, offering a more personalized alternative to conventional handwriting generation tools.
This invention presents a novel hybrid encryption framework combining Advanced Encryption Standard (AES) and Elliptic Curve Cryptography (ECC) to achieve robust data security. The proposed system introduces a unique approach based on the formula E = ECC.(AES)², where AES provides high-speed symmetric encryption and ECC ensures secure key exchange through asymmetric cryptography. The framework enhances security by splitting the data into two equal parts: one encrypted using AES and the other with ECC.
REAL-TIME FACIAL EXPRESSION ANALYSIS FOR EMOTION RECOGNITION USING IMAGE PROCESSING A Real-Time Facial Expression Analysis for Emotion Recognition Using Image Processing comprises a data collection module, a data pre-processing module, a machine learning module, a CNN architecture, a SVM model, wherein the data collection module is used for gather a set of facial images of different people with different expressions. In another embodiment after gathering, the data pre-processing module characterized the data set
A system for gunshot detection and direction localization is disclosed. The system comprising: an array of hexagonal microphones to capture analogue sound waves. A conversion unit to convert the captured analogue sound waves into digital sound waves. A control unit configured to: receive the digital sound waves from the conversion unit conduct a bandpass filtering on the received digital sound waves to isolate gunshot frequencies; analyze and classify the gunshot frequencies under a subcategory of true gunshot frequencies;
The text in the image describes a dynamic double-layer cryptographic system designed to enhance data security and accelerate encryption processing. It combines symmetric and asymmetric encryption in a dynamic configuration to ensure robust protection against contemporary and future cyber threats. Key features include dynamic adaptability, optimized key management, quantum-resistant algorithms, and a parallel processing framework, making it suitable for diverse real-time applications.
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