ASHISH SURESH AWATE

@svkm-iot.ac.in

ASSISTANT PROFESSOR, COMPUTER ENGINEERING
SHRI VILE PARLE KELAVANI MANDAL'S INSTITUTE OF TECHNOLOGY DHULE

ASHISH SURESH AWATE


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https://researchid.co/ashish.awate

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Science
13

Scopus Publications

69

Scholar Citations

4

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Vividh-Vaani: Video Translation and Synchronization using Machine Learning
    Kavita Tukaram Patil, Nita Jayesh Mahale, Mayuri Diwakar Kulkarni, Makarand Shahade, Ashish Awate, Bhushan Nandwalkar
    Cluster Computing, 2026
  • A comprehensive approach to brain tumor detection and classification
    Bhushan Nandwalkara, Ashish Awate, Mohit Desal, Ayush Kakaria, Nishita Shah, Pooja Mali
    Next Generation Technologies for Sustainable Development, 2026
  • Artificial intelligence and machine learning for colorimetric detections: Techniques, applications, and future prospects
    Arpita Parakh, Ashish Awate, Sampa Manoranjan Barman, Rakesh K. Kadu, Dhiraj P. Tulaskar, Madhusudan B. Kulkarni, Manish Bhaiyya
    Trends in Environmental Analytical Chemistry, 2025
    Rapid, low-cost detection of contaminants and quality markers is critical across healthcare, food safety, environmental monitoring, and industrial applications. While traditional laboratory methods remain accurate, they are often slow, expensive, and unsuitable for point-of-care or field use. Colorimetric biosensing offers a simple, affordable, and visually intuitive alternative; however, its dependence on subjective human interpretation introduces bias and limits reproducibility, particularly when subtle color variations arise under different lighting conditions or device types. Recent advances in artificial intelligence (AI), machine learning (ML), and especially deep learning (DL) have transformed these limitations into opportunities by enabling automated, robust, and highly precise analysis. Models such as convolutional neural networks (CNNs) and specialized architectures like ColorNet can directly interpret raw images, extract complex features, and adapt across varied environments, thereby enhancing accuracy and scalability. Through smartphone integration, edge computing, and explainable AI, these systems are now being deployed in diverse real-world scenarios, including biomedical diagnostics, wound and tissue health monitoring, food spoilage and adulteration detection, environmental pollutant sensing, and smart packaging. This review critically examines AI/ML/DL-assisted colorimetric systems, highlights domain-specific applications, and addresses challenges such as dataset generalizability, model interpretability, and regulatory validation, offering practical solutions and future directions for smarter, portable, and accessible biosensing platforms.
  • ExamGuard: Smart contracts for secure online test
    Mayuri Diwakar Kulkarni, Ashish Awate, Makarand Shahade, Bhushan Nandwalkar
    Information Systems, 2025
  • IntelliMeet: AI-Powered Meeting Summarization with FLAN-T5 and Cosine Clustering
    Bhushan Nandwalkar, Ashish Awate, Mayur Jain, Soham Chaudhari, Vaishnavi Pardeshi, Pranali Magar
    Iet Conference Proceedings, 2025
    In response to increased use of virtual and hybrid meetings, IntelliMeet offers an AI-based solution for real-time transcription and summarization. We use Google’s Speech-to-Text API for high-quality transcription, abstractive summarization using fine-tuned FLAN-T5, and cosine clustering for information organization based on topics. With hybrid strategy using extractive and abstractive techniques, IntelliMeet provides readable and coherent meeting minutes. Experimental evaluations using SAMSum datasets prove better ROUGE-1 and ROUGE-2 ratings, displaying potential for large-scale use in corporate and academic environments.
  • AlgoDecrypt: A Cryptographic Algorithm Identification System
    Makarand Shahade, Ashish Awate, Anish Nale, Pavan Patil, Prerna Khairnar, Siddheshwar Nerkar
    2025 International Conference on Engineering Innovations and Technologies Icoeit 2025, 2025
    Identifying cryptographic algorithms is a critical process in cybersecurity, providing insights into encryption methods used to protect information. Traditional identification methods involve manual examination, which is time-consuming, inefficient, and prone to errors. With the evolution of encryption algorithms, an efficient and automated solution is essential. This paper presents an AI/ML-based system employing a Convolutional Neural Network (CNN) with 10 layers integrated with Bi-Directional Long Short-Term Memory (LSTM) networks to categorize cryptographic algorithms based on ciphertext characteristics. 13 different models were developed, each trained to identify specific algorithms. The system extracts features such as entropy, block size, and character distribution for accurate classification. A React frontend allows users to input ciphertext for analysis, while a Flask backend processes the data and applies the trained models. Results are stored in a MongoDB database for further analysis and future research. Using deep learning tools like TensorFlow and PyTorch, the system achieves superior accuracy and efficiency compared to traditional methods. This research demonstrates how AI can significantly enhance cryptographic analysis, offering a scalable, reliable, and rapid solution for cybersecurity professionals.
  • Mathematical Modelling and Deep Learning: Innovations in E-Commerce Sentiment Analysis
    Et al. Ashish Suresh Awate
    Advances in Nonlinear Variational Inequalities, 2024
    This research explores e-commerce dynamics, focusing on the challenge of predicting customer churn using deep learning [65]. It integrates and analyses both textual and transactional data, including social media posts and customer feedback [59]. The approach uses an advanced deep learning model, involving data collection, pre-processing, and feature extraction [40]. Novel methods fuse data to create a detailed customer profile combining sentiment analysis with behavioural insights derived from transaction data [25]. The deep learning architecture is designed to analyse and predict customer sentiments and purchasing behaviours, informed by the latest research [65]. This study is significant as it provides an innovative solution for predicting customer churn in e-commerce, aiding sustainability [45]. It also enables targeted retention strategies and personalized customer engagement [59]. Additionally, it contributes insights to big data analytics and customer relationship management in e-commerce, showcasing deep learning's potential in transforming business practices and enhancing customer experience [40].
  • Unmasking attacker identity behind the VPN
    A.S. Awate, B.N. Nandwalkar, M.R. Shahade, D.B. Mali, H.V. Patil, H.R. Waghare, H.R. Patil
    Advances in AI for Biomedical Instrumentation Electronics and Computing Proceedings of the 5th International Conference on Advances in AI for Biomedical Instrumentation Electronics and Computing Icabec 2023, 2024
    In the dynamic landscape of cybersecurity, this paper addresses a critical challenge: the ability of attackers to conceal their identities behind VPNs and proxy servers. Our dual objectives are to develop advanced techniques for pinpointing these elusive actors and to empower the cybersecurity community with actionable insights. Leveraging the MERN stack, cloud services, open-source tools and specialized libraries, we unveil attackers’ identities. In a digital era, valuing privacy and security, this paper lays the foundation for an in-depth exploration, offering solutions to enhance online safety. Through strategic use of technology and insights, we contribute to a more secure online environment.
  • e-Nidan: Autism spectrum disorder detection using machine learning
    Ashish Awate, Krutika Yeola, Makarand Shahade, Vaishnavee Patil, Mayuri Vispute, Hemshri Amrutkar, Bhushan Nandwalkar
    Advances in AI for Biomedical Instrumentation Electronics and Computing Proceedings of the 5th International Conference on Advances in AI for Biomedical Instrumentation Electronics and Computing Icabec 2023, 2024
    Autism Spectrum Disorder (ASD) is a developmental disorder characterized by social, communication, and behavioral challenges. People with ASD may struggle with interaction, exhibit repetitive behaviors, and have specific interests. Early diagnosis is crucial, typically occurring in early childhood through a comprehensive evaluation of a child's development, history, and behavior. While there is no cure for ASD, various treatments, such as Applied Behavior Analysis and therapy, can enhance social, communication, and behavioral skills. ASD's symptoms vary among individuals and may include sensory processing difficulties, resistance to change, and a typical eating or sleeping habits. The average age of diagnosis is around 0 - 6 years, but some individuals may be diagnosed later due to less obvious symptoms in younger children. ASD, or Autism Spectrum Disorder, is a developmental condition associated with significant social, communication, and behavioral challenges. To solve this problem, this paper proposes an ML-powered system called eNidan to detect early symptoms of Autism Spectrum Disorder (ASD). Three algorithms are evaluated: KNN, Decision Tree, and Logistic Regression. Accuracy of decision tree algorithm is 64 percent, Accuracy of SVM algorithm is 58 percent, Accuracy of logistic regression algorithm is 67 percent. Logistic Regression is the best algorithm, with an accuracy of 67 percent. All three algorithms are appended to the model, and the accuracy of each algorithm is compared. Logistic Regression is found to be the best algorithm, and all results are fetch to the final algorithm. The paper focuses on historical data that is available and suitable for training data. This algorithm is downloaded onto the ML algorithm and trained on historical data collected from Kaggle. The parameters in the dataset are roll number, student age, speech delay, learning disorder, sex, family ASD, and ASD train. So final result is logistic regression is best algorithm for this e-Nidan System.
  • TrustCaller- Voice-based Fraud Prevention System
    Rushikesh Sonwane, Mansi Patil, Purva Chauhan, Anushka Jain, Bhushan Nandwalkar, Ashish Awate, Makarand Shahade
    2024 4th International Conference on Intelligent Technologies Conit 2024, 2024
    An innovative project called “TrustCaller” aims to improve call security. With the goal of establishing caller verification and building trust in incoming calls, the project makes use of state-of-the-art technologies for voice feature extraction, processing, and pattern matching. Utilizing React Native only for the Android application, “TrustCaller” assumes a key function in boosting the security of phone communications when combined with Machine Learning (ML) and Speech Synthesis. This program is a vital step in protecting people from possible dangers and promoting safer phone communication. Moreover, it provides scalable security settings to guarantee users’ privacy and control over communication.
  • Understanding Customer Behaviour: A Comprehensive Survey of Segmentation and Classification Techniques in the Age of Big Data
    International Journal of Intelligent Systems and Applications in Engineering, 2023
  • Descriptive Handwritten Paper Grading System using NLP and Fuzzy Logic
    Nandwalkar Bhushan, Pardeshi Sukruta, Shahade Makarand, Awate Ashish
    International Journal of Performability Engineering, 2023
  • Survey of algorithms for assigning advertisement to search keywords
    Ashish S. Awate, Sameer S. Prabhune
    Proceedings of the 2014 Conference on IT in Business Industry and Government an International Conference by Csi on Big Data Csibig 2014, 2014

RECENT SCHOLAR PUBLICATIONS

  • Vividh-Vaani : Video Translation and Synchronization using Machine Learning
    KT Patil, NJ Mahale, MD Kulkarni, M Shahade, A Awate, B Nandwalkar
    Cluster Computing 29 (3), 137 , 2026
    2026
  • Threatshield: Toxic Comments on Social Media
    A Awate, M Shahade, K Badgujar, P Badgujar, R Patil, B Patiil
    2026 International Conference on Multidisciplinary Innovations For Smart … , 2026
    2026
  • Artificial intelligence and machine learning for colorimetric detections: Techniques, applications, and future prospects
    A Parakh, A Awate, SM Barman, RK Kadu, DP Tulaskar, MB Kulkarni, ...
    Trends in Environmental Analytical Chemistry, e00280 , 2025
    2025
    Citations: 29
  • AlgoDecrypt: A Cryptographic Algorithm Identification System
    M Shahade, A Awate, A Nale, P Patil, P Khairnar, S Nerkar
    2025 International Conference on Engineering Innovations and Technologies … , 2025
    2025
  • IntelliMeet: AI-powered meeting summarization with FLAN-T5 and cosine clustering
    B Nandwalkar, A Awate, M Jain, S Chaudhari, V Pardeshi, P Magar
    Parul University International Conference on Engineering and Technology 2025 … , 2025
    2025
  • ExamGuard: Smart contracts for secure online test
    MD Kulkarni, A Awate, M Shahade, B Nandwalkar
    Information Systems 128, 102485 , 2025
    2025
    Citations: 4
  • Deep Learning-Driven Dynamic Segmentation and Sentiment Prediction to Enhance Customer Retention in Online Platforms
    SKS Ashish Suresh Awate
    Journal of Information Systems Engineering and Management 10 (2), 624-639 , 2024
    2024
    Citations: 2
  • TrustCaller-Voice-based Fraud Prevention System
    R Sonwane, M Patil, P Chauhan, A Jain, B Nandwalkar, A Awate, ...
    2024 4th International Conference on Intelligent Technologies (CONIT), 1-6 , 2024
    2024
    Citations: 2
  • Unmasking attacker identity behind the VPN
    AS Awate, BN Nandwalkar, MR Shahade, DB Mali, HV Patil, HR Waghare, ...
    Advances in AI for Biomedical Instrumentation, Electronics and Computing … , 2024
    2024
    Citations: 1
  • e-Nidan: Autism spectrum disorder detection using machine learning
    A Awate, K Yeola, M Shahade, V Patil, M Vispute, H Amrutkar, ...
    Advances in AI for Biomedical Instrumentation, Electronics and Computing … , 2024
    2024
    Citations: 1
  • Mathematical modelling and deep learning: Innovations in e-commerce sentiment analysis
    AS Awate, SK Sharma
    Advances in Nonlinear Variational Inequalities 27 (1), 52-81 , 2024
    2024
    Citations: 6
  • Understanding Customer Behaviour: A Comprehensive Survey of Segmentation and Classification Techniques in the Age of Big Data
    SKS Ashish Suresh Awate
    International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING … , 2023
    2023
    Citations: 7
  • Deep care: Smart depression counselling system through emotion recognition and opinion mining using deep learning
    A Awate, H Sharma, R Hatkar, M Shahade, B Nandwalkar, Y Jadhav, ...
    2023
    Citations: 1
  • Descriptive Handwritten Paper Grading System using NLP and Fuzzy Logic.
    B Nandwalkar, S Pardeshi, M Shahade, A Awate
    International Journal of Performability Engineering 19 (4), 273-282 , 2023
    2023
    Citations: 10
  • REAL TIME SURVEILLANCE SYSTEM USING ARTIFICIAL INTELLIGENCE TO GET PRECISE INSIGHTS AND RESULTS FOR SECURITY AND SURVEILLANCE PURPOSE
    MAAMJCDMSMMKMBNMTCMRGMA Patil
    IN Patent App. 202221075165 A , 2023
    2023
  • Diabetes Disease Prediction Using KNN
    M Shahade, A Awate, B Nandwalkar, M Kulkarni
    International Conference on Innovations in Data Analytics, 293-306 , 2022
    2022
    Citations: 1
  • M-health: a revolution due to technology in healthcare sector
    MD Kulkarni, AS Awate, JM Chatterje
    2022
  • Determining Soil Fertility with the Help of Capacitive Touch Sensor
    PC Meghal Jambhale , Janvi Rajput, Amruta Patil , Ashish Awate
    Compliance Engineering Journal (CEJ) 13 (Issue 3,2022), 1-7 , 2022
    2022
  • Convergence Of Machine Learning And Blockchain For Securing Future Of Internet Of Things
    D Borse, N Hire, D Gavale, A Awate
    e-Conference on Data Science and Intelligent Computing, 83 , 2020
    2020
  • Review On: Applications Of Augmented Reality
    M Gindodiya, T Bhavsar, U Shaikh, A Awate
    e-Conference on Data Science and Intelligent Computing, 93 , 2020
    2020

MOST CITED SCHOLAR PUBLICATIONS

  • Artificial intelligence and machine learning for colorimetric detections: Techniques, applications, and future prospects
    A Parakh, A Awate, SM Barman, RK Kadu, DP Tulaskar, MB Kulkarni, ...
    Trends in Environmental Analytical Chemistry, e00280 , 2025
    2025
    Citations: 29
  • Descriptive Handwritten Paper Grading System using NLP and Fuzzy Logic.
    B Nandwalkar, S Pardeshi, M Shahade, A Awate
    International Journal of Performability Engineering 19 (4), 273-282 , 2023
    2023
    Citations: 10
  • Understanding Customer Behaviour: A Comprehensive Survey of Segmentation and Classification Techniques in the Age of Big Data
    SKS Ashish Suresh Awate
    International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING … , 2023
    2023
    Citations: 7
  • Mathematical modelling and deep learning: Innovations in e-commerce sentiment analysis
    AS Awate, SK Sharma
    Advances in Nonlinear Variational Inequalities 27 (1), 52-81 , 2024
    2024
    Citations: 6
  • ExamGuard: Smart contracts for secure online test
    MD Kulkarni, A Awate, M Shahade, B Nandwalkar
    Information Systems 128, 102485 , 2025
    2025
    Citations: 4
  • Analysis and optimization of wire electro discharge machining parameters of TiNi shape memory alloy using Taguchi technique
    AM Takale, NK Chougule, RL Patil, AS Awate
    International Conference on Advances in Thermal Systems, Materials and … , 2017
    2017
    Citations: 3
  • Deep Learning-Driven Dynamic Segmentation and Sentiment Prediction to Enhance Customer Retention in Online Platforms
    SKS Ashish Suresh Awate
    Journal of Information Systems Engineering and Management 10 (2), 624-639 , 2024
    2024
    Citations: 2
  • TrustCaller-Voice-based Fraud Prevention System
    R Sonwane, M Patil, P Chauhan, A Jain, B Nandwalkar, A Awate, ...
    2024 4th International Conference on Intelligent Technologies (CONIT), 1-6 , 2024
    2024
    Citations: 2
  • Survey of algorithms for assigning advertisement to search keywords
    AS Awate, SS Prabhune
    2014 Conference on IT in Business, Industry and Government (CSIBIG), 1-5 , 2014
    2014
    Citations: 2
  • Unmasking attacker identity behind the VPN
    AS Awate, BN Nandwalkar, MR Shahade, DB Mali, HV Patil, HR Waghare, ...
    Advances in AI for Biomedical Instrumentation, Electronics and Computing … , 2024
    2024
    Citations: 1
  • e-Nidan: Autism spectrum disorder detection using machine learning
    A Awate, K Yeola, M Shahade, V Patil, M Vispute, H Amrutkar, ...
    Advances in AI for Biomedical Instrumentation, Electronics and Computing … , 2024
    2024
    Citations: 1
  • Deep care: Smart depression counselling system through emotion recognition and opinion mining using deep learning
    A Awate, H Sharma, R Hatkar, M Shahade, B Nandwalkar, Y Jadhav, ...
    2023
    Citations: 1
  • Diabetes Disease Prediction Using KNN
    M Shahade, A Awate, B Nandwalkar, M Kulkarni
    International Conference on Innovations in Data Analytics, 293-306 , 2022
    2022
    Citations: 1
  • Vividh-Vaani : Video Translation and Synchronization using Machine Learning
    KT Patil, NJ Mahale, MD Kulkarni, M Shahade, A Awate, B Nandwalkar
    Cluster Computing 29 (3), 137 , 2026
    2026
  • Threatshield: Toxic Comments on Social Media
    A Awate, M Shahade, K Badgujar, P Badgujar, R Patil, B Patiil
    2026 International Conference on Multidisciplinary Innovations For Smart … , 2026
    2026
  • AlgoDecrypt: A Cryptographic Algorithm Identification System
    M Shahade, A Awate, A Nale, P Patil, P Khairnar, S Nerkar
    2025 International Conference on Engineering Innovations and Technologies … , 2025
    2025
  • IntelliMeet: AI-powered meeting summarization with FLAN-T5 and cosine clustering
    B Nandwalkar, A Awate, M Jain, S Chaudhari, V Pardeshi, P Magar
    Parul University International Conference on Engineering and Technology 2025 … , 2025
    2025
  • REAL TIME SURVEILLANCE SYSTEM USING ARTIFICIAL INTELLIGENCE TO GET PRECISE INSIGHTS AND RESULTS FOR SECURITY AND SURVEILLANCE PURPOSE
    MAAMJCDMSMMKMBNMTCMRGMA Patil
    IN Patent App. 202221075165 A , 2023
    2023
  • M-health: a revolution due to technology in healthcare sector
    MD Kulkarni, AS Awate, JM Chatterje
    2022
  • Determining Soil Fertility with the Help of Capacitive Touch Sensor
    PC Meghal Jambhale , Janvi Rajput, Amruta Patil , Ashish Awate
    Compliance Engineering Journal (CEJ) 13 (Issue 3,2022), 1-7 , 2022
    2022