Dr. Vinayak Dagadu Shinde

@slrtce.in

Associate Professor, Department of Computer Engineering
Shree L. R. Tiwari College of Engineering

Dr. Vinayak Dagadu Shinde


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https://researchid.co/vdshinde

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Hardware and Architecture, Software, Computer Networks and Communications
11

Scopus Publications

81

Scholar Citations

4

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • Human Capital Meets Artificial Intelligence: Integrating AI/ML-Powered Digital Payment Solutions into HR Ecosystems
    Veena K P, C. Mahadeva Murthy, Pratibha Gupta, Aditi Dadhich, Vinayak Dagadu Shinde, Praveen Kumar Mannepalli
    2026 International Conference on Emerging Smart Computing and Informatics Esci 2026, 2026
  • Deep Unrolled Optimization Networks for Solving High-Dimensional Inverse Problems in Risk-Sensitive Portfolio Engineering
    Yogesh Kumar Jain, Rajashri Chaudhari, Anshu Kumar Tripathi, Prachi Beriwala, Vinayak Dagadu Shinde, Sheetal Dayanand Shirke
    2025 International Conference on Artificial Intelligence and Quantum Computation Based Sensor Application Icaiqsa 2025 Proceedings, 2025
    The authors proposed a new framework using Deep Unrolled Optimization Networks to solve high-dimensional inverse problems for Risk Sensitive Portfolio Engineering. Classical optimization methods and most Deep Learning Methods are limited as they either lack scalability or interpretability. The proposed framework unrolls an iterative solver into a trainable network thereby providing faster convergence rates, better risk-return trade-offs, and greater robustness with respect to noisy covariance estimates than traditional methods. Simulations were used to demonstrate superior performance of the proposed framework relative to well-established benchmarks (Markowitz, Black-Litterman) in terms of cumulative wealth growth, Sharpe Ratio, Value-at-Risk and drawdown reductions. The simulations suggest that Deep Unrolled Optimization has potential as a means to provide interpretable and computationally efficient tools for practical portfolio management in dynamic and uncertain financial markets.
  • Analyzing the Effects of K-Means and Random Forest Algorithms on Resume Classification through Manipulation of Cluster Sizes and Datasets
    Sweety Mahesh Patil, Vinayak D. Shinde
    Proceedings of the 18th Indiacom 2024 11th International Conference on Computing for Sustainable Global Development Indiacom 2024, 2024
    In online job recruitment, precise job classifications are crucial for both job seekers and recruiters. Categorizing resumes is a crucial stage in the multi-step recruitment process. The success of an organization heavily relies on the personality of its candidates. This system is based on two modules. Questionnaires in the MCQ format are used in Module 1 to collect input from user. Module 1 includes pre-processing using min-max scaling, enrichment using cluster optimization technique, pattern recognition using k-means clustering algorithm, and by changing the cluster’s size, personality traits can be identified and personality traits predicted. The output of Module 1 is detecting appropriate personality based on categories are Extroversion, Neuroticism, Agreeableness, Conscientiousness and Openness. When appropriate category of personality is detected in Module 1, which will be helpful in further analysis of job, resume will be passed to the system as input in PDF format to Module 2. Module 2 is based on two stages. Data collection, text vectorization on training datasets, and job title encoding are all included in stage one. Stage 2 involves input resumes in PDF format using the PyPDF2 library. The NLTK library and regular expression are used to pre-process resumes, followed by TF-IDF vectorization and Random Forest Algorithm to classify them based on similarity to job title. Accurate resume classification can be achieved by optimizing K-Means and Random Forest Algorithms, yielding a 70% accuracy rate. Ensemble learning techniques or Linear Support Vector Classifier (SVC) can potentially enhance accuracy.
  • Enhancing Breast Cancer Detection: A Machine Learning Approach for Early Diagnosis and Classification
    Aditi Sawant, Divya Patil, Dimple Khuman, Yogesh Pingle, Vinayak Shinde
    Proceedings of the 18th Indiacom 2024 11th International Conference on Computing for Sustainable Global Development Indiacom 2024, 2024
    Millions of new cases of breast cancer are discovered worldwide each year, which is a serious health risk. For treatment options to be directed and patient outcomes to be improved, a timely and correct diagnosis is essential. Medical diagnostics has shown machine learning, and more specifically logistic regression, to be a useful tool. This work uses a logistic regression model to show how machine learning may be used practically to categorize breast cancer cases. The main goal is to develop a model that can reliably classify breast tissue as benign, malignant, or normal based on medical photos in order to aid in the early diagnosis of cancer. By reducing reliance on arbitrary human judgements, this method aims to improve the consistency and effectiveness of the diagnostic procedure.
  • Improved Crop Yields and Resource Efficiency in IoT-based Agriculture with Machine Learning
    Santosh Kumar, Vinayak Dagadu Shinde, Uma Bhavin Goradiya, Aabha Amey Patil, Sonu Prasad Verman, Vilas Kisanrao Tembhurne
    2024 International Conference on Automation and Computation Autocom 2024, 2024
    Despite popular belief, agricultural research today is more based on hard evidence; exact; precise, and rigorous than ever before. Almost every industry has been disrupted by the spread of IoT-based technologies, including urban planning, healthcare, the electricity grid, the home, and agriculture, frequently referred to as “smart agriculture”. Machine learning (ML) and IoT data analytics in agriculture can boost crop yields to meet rising food demand. These revolutionary developments are upending standard agricultural practices and giving rise to new and finest opportunities, but with some drawbacks. Optimal agriculture output requires this research seeks to develop an effective and precise system that uses Crop selection choices made using algorithms that utilize Internet of Things (IoT) sensors and ML Therefore, this paper, proposed an ensemble model using machine learning for crop prediction based on IoT data which is collected from the IoT sensors using the PLX-DAQ tool. There are several suggested machines learning models, including “Naive Bayes, Decision Tree, Random Forest Support Vector Machine, and K-Nearest Neighbour,”. According to the experimental findings, ensemble learning had the greatest accuracy of 97.45% for predicting early crop yields. The results of this research will significantly increase the dependence on data for choices relating to climate change and agricultural practices.
  • American Sign Language Recognition using Video Vision Transformers
    Nishant Singh, Vinayak Shinde, Pratik Kanani
    Proceedings of 3rd International Conference on Advanced Computing Technologies and Applications Icacta 2023, 2023
    Sign language is the most natural and effective way for communication amongst the hearing/vocally challenged and the hearing abled. To bridge the social gap, this paper proposes a system that aids in translating from a video feed of American Sign Language signers to a known set of common English words. Current solutions for vision based sign language to English translation is limited to a very small set of target classes and old modeling techniques that do not take into consideration the temporal factor that caters to the sequential nature of signing. We use the WLASL dataset, which is a largescale dataset for Word-Level American Sign Language and it comprises of 2000 words from over 100 signers and develop models on WLASL100 and WLASL300 each representing the top 100 and 300 most commonly appearing glossaries respectively. For modelling, we make use of video vision transformers (ViViT) to leverage the power of multi head attention in a temporal and spatial setting and experiment with two feature extraction models like Truncated Resnet50 and MoveNet-thunder which act as a precursor to the ViViT. The final model does better than state of the art models like Pose-GRU, Pose-TGCN and VGG-GRU, which were also trained on the WLASL dataset with a top-1 accuracy of 59.44% on the WLASL100 subset and a top-1 accuracy of 48.38% on the WLASL300 subset.
  • IoT-based Air Pollution Monitoring System to Measure Air Quality on Cloud Storage
    Vilas Kisanrao Tembhurne, Vinayak Dagadu Shinde, Santosh Kumar, Manish Shrimali, Gunjan Chhabra, M N Quadri, Vikram Rajpoot
    2023 2nd International Conference on Paradigm Shifts in Communications Embedded Systems Machine Learning and Signal Processing Pcems 2023, 2023
    Air pollution (AP) is today’s most pressing issue. Particularly concerning are the potential adverse effects that an excessive amount of certain hazardous gases, such as CO, SO2, particulate matter, and several others, may have on human health. Other environmental gases are affected by temperature, humidity, etc., wind speed, and their causes and impacts. These weather factors include temperature, humidity, as well as wind speed.For this project, a centralized cloud-based system using sensors that monitor and analyze AP will be developed. The information gathered by each sensor node is uploaded to a cloud server, where it is stored and can be viewed through a web browser at any time and from any location. Because the environment is being monitored in real-time, prompt action may be performed in response to discovering a contaminant in the ecosystem. This project aims to monitor the AP of the surrounding area and ensure that data are kept up to date on the internet. Readings are conducted continuously throughout the day and in real-time. Many air pollutants like SO2, CO, PM10, humidity, and temperature are considered to measure air quality by IoT-based air pollution monitoring systems (APMS). We created graphics that simplify analyzing the proportion of pollutants in a certain location. The LCD can show the gas sensor’s real-time data constantly.
  • Alphanumeric database security through digital watermarking
    Akshata A. Churi, Vinayak D. Shinde
    2020 International Conference on Convergence to Digital World Quo Vadis Iccdw 2020, 2020
    As the demand of online data availability increases for sharing data, business analytics, security of available data becomes important issue, data needs to be protected from unauthorized access as well as it needs to provide authority that the data is received from a trusted owner. To provide owners identity digital watermarking technique is used since long time for multimedia data. This paper proposed a technique which supports watermarking on database as most of the data available today is in database format. The characters to be entered as watermark are converted into binary values; these binary values are hidden in the database using space character. Each bit is hidden in each tuple randomly. Ant colony optimization algorithm is proposed to select tuples where watermark bits are inserted. The proposed system is enhanced in terms of security due to use of ant colony optimization and resilient because even if some bits are modified the hidden text remains almost same.
  • Recommendation system using content filtering: A case study for college campus placement
    Nishigandha Karbhari, Asmita Deshmukh, Vinayak D. Shinde
    2017 International Conference on Energy Communication Data Analytics and Soft Computing Icecds 2017, 2018
    Recommender system known as information gathering system aims at creating an algorithm which, keeps in consideration the diverse needs and varying level of competence. It offers better opportunities in project development cycle under requirement phase and design phase. Social media and Ecommerce market has tapped in the recommender system to boost its growth by providing with precise results. It provides with either service or product recommendation using the information gathered in the software engineering process. It is broadly divided in three categories which are Collaborative, Content-based and Hybrid recommendation approach. This paper presents a model to generate recommendations based on marks of student. It discovers best solutions which would have otherwise remained hidden. The case study performed on the recommender system implementation in college campus will result a recommendation in placement of students (employee) to companies (employer) as per their requirements in shortest possible time. It can be expected as a situation where we have tried to achieve the results while keeping in mind the requirements of employer and employee.
  • Smart Locker Management System Using IoT
    12th Indiacom 5th International Conference on Computing for Sustainable Global Development Indiacom 2018, 2018
  • Detection of Intruder using Honeywords and IP Blocking
    11th Indiacom 4th International Conference on Computing for Sustainable Global Development Indiacom 2017, 2017

RECENT SCHOLAR PUBLICATIONS

  • Measurement of Human Attention levels using Artificial Intelligence Pattern Simulation
    K Pimparkhede, VD Shinde
    Solid State Technology 64 (2), 7352-7355 , 2021
    2021
  • Service Discovery Mechanism Using Dynamic Analysis
    K Pimparkhede, VD Shinde
    Solid State Technology 64 (2), 6557-6564 , 2021
    2021
  • PERFORMANCE ANALYSIS SYSTEM USING WEB BASED SOLUTION FOR MCQ TYPE ONLINE EXAMINATION
    J Navik, A Sawant, S Saini, VD Shinde
    Open Access International Journal of Science Engineering (OAIJSC-2021) , 2021
    2021
    Citations: 1
  • client side and Server Side Load balancing
    K Pimparkhede
    International Journal for Research in Ap-plied Science and Engineering … , 2021
    2021
    Citations: 4
  • Measurement of Human Attention levels using Artificial Intelligence Pattern Simulation
    VDS Kunal Pimparkhede
    Solid State Technology 64 (2), 3461-3465 , 2021
    2021
  • alphanumeric database security through digital watermarking
    AA Churi, VD Shinde
    2020 International Conference on Convergence to Digital World - Quo Vadis … , 2020
    2020
    Citations: 1
  • Performance evaluation of various supervised machine learning algorithms for diabetes prediction
    JR Raut, Y Sharma, VD Shinde
    European Journal of Molecular & Clinical Medicine 7 (8), 2020 , 2020
    2020
    Citations: 6
  • Human Identification Using Motion Vector Analysis
    C D'Souza, S Gaikwad, V Shinde
    International Journal in IT & Engineering 7 (5), 1-7 , 2019
    2019
  • Traffic rules violation system using NFC card
    R Yadav, A Korgaonkar, S Yadav, P Yadav, VD Shinde, S Sal
    International Research Journal of Engineering and Technology (IRJET) , 2018
    2018
    Citations: 1
  • Smart Locker Management System Using IoT
    P Parab, M Kulkarni, V Shinde
    system 8 (10) , 2018
    2018
    Citations: 4
  • Recommendation system using content filtering: A case study for college campus placement
    N Karbhari, A Deshmukh, VD Shinde
    2017 International conference on energy, communication, data analytics and … , 2017
    2017
    Citations: 36
  • A Study on Gait Analysis for Human Identification
    C D’Souza, S Gaikwad, V Shinde
    International Conference On Emanations in Modern Technology and Engineering … , 2017
    2017
    Citations: 1
  • A survey on: Sound source separation methods
    MR Pimpale, S Therese, V Shinde
    International Journal 3 (11), 580-584 , 2016
    2016
    Citations: 12
  • The adoption of cloud computing technologyin engineering Colleges in mumbai concern resistances and challenges
    V Shinde
    Jhunjhunu , 2016
    2016
  • Generating Honeywords From Real Passwords With Decoy Mechanism
    MK Naik, V Bhosale, VD Shinde
    International Journal for Research in Engineering Application & Management 2 … , 2016
    2016
    Citations: 2
  • Design and Implementation of Embedded Web Server and DACS with ARM9 using Linux
    N Priyanka, VD Shinde
    International Journal of Scientific and Research Publications, 603 , 2015
    2015
    Citations: 1
  • Survey on Distributed Incomplete Pattern Matching
    MJS Pande, JW Bakal, MV Shinde
    International Journal of Global Technology Initiatives 4 (1), C11-C17 , 2015
    2015
  • Design and development of ARM9 based embedded web server
    N Priyanka, VD Shinde
    Int. Journal of Engineering Research and Applications 5 (8), 50-53 , 2015
    2015
    Citations: 4
  • Study of cluster, grid and cloud computing
    V Shinde, A Shaikh, CD Souza
    International Journal of Advanced Research in Computer and Communication … , 2015
    2015
    Citations: 1
  • Survey on malware detection techniques
    P Gaikwad, D Motwani, V Shinde
    International Journal of Modern Trends in Engineering and Research 21 (7), 1-25 , 2015
    2015
    Citations: 5

MOST CITED SCHOLAR PUBLICATIONS

  • Recommendation system using content filtering: A case study for college campus placement
    N Karbhari, A Deshmukh, VD Shinde
    2017 International conference on energy, communication, data analytics and … , 2017
    2017.0
    Citations: 36
  • A survey on: Sound source separation methods
    MR Pimpale, S Therese, V Shinde
    International Journal 3 (11), 580-584 , 2016
    2016.0
    Citations: 12
  • Performance evaluation of various supervised machine learning algorithms for diabetes prediction
    JR Raut, Y Sharma, VD Shinde
    European Journal of Molecular & Clinical Medicine 7 (8), 2020 , 2020
    2020.0
    Citations: 6
  • Survey on malware detection techniques
    P Gaikwad, D Motwani, V Shinde
    International Journal of Modern Trends in Engineering and Research 21 (7), 1-25 , 2015
    2015.0
    Citations: 5
  • client side and Server Side Load balancing
    K Pimparkhede
    International Journal for Research in Ap-plied Science and Engineering … , 2021
    2021.0
    Citations: 4
  • Smart Locker Management System Using IoT
    P Parab, M Kulkarni, V Shinde
    system 8 (10) , 2018
    2018.0
    Citations: 4
  • Design and development of ARM9 based embedded web server
    N Priyanka, VD Shinde
    Int. Journal of Engineering Research and Applications 5 (8), 50-53 , 2015
    2015.0
    Citations: 4
  • Generating Honeywords From Real Passwords With Decoy Mechanism
    MK Naik, V Bhosale, VD Shinde
    International Journal for Research in Engineering Application & Management 2 … , 2016
    2016.0
    Citations: 2
  • PERFORMANCE ANALYSIS SYSTEM USING WEB BASED SOLUTION FOR MCQ TYPE ONLINE EXAMINATION
    J Navik, A Sawant, S Saini, VD Shinde
    Open Access International Journal of Science Engineering (OAIJSC-2021) , 2021
    2021.0
    Citations: 1
  • alphanumeric database security through digital watermarking
    AA Churi, VD Shinde
    2020 International Conference on Convergence to Digital World - Quo Vadis … , 2020
    2020.0
    Citations: 1
  • Traffic rules violation system using NFC card
    R Yadav, A Korgaonkar, S Yadav, P Yadav, VD Shinde, S Sal
    International Research Journal of Engineering and Technology (IRJET) , 2018
    2018.0
    Citations: 1
  • A Study on Gait Analysis for Human Identification
    C D’Souza, S Gaikwad, V Shinde
    International Conference On Emanations in Modern Technology and Engineering … , 2017
    2017.0
    Citations: 1
  • Design and Implementation of Embedded Web Server and DACS with ARM9 using Linux
    N Priyanka, VD Shinde
    International Journal of Scientific and Research Publications, 603 , 2015
    2015.0
    Citations: 1
  • Study of cluster, grid and cloud computing
    V Shinde, A Shaikh, CD Souza
    International Journal of Advanced Research in Computer and Communication … , 2015
    2015.0
    Citations: 1
  • Malicious user detection using honeyword and IP tracking
    MK Naik, V Bhosale, VD Shinde
    International Conference On Emanations in Modern Technology and Engineering … , 0
    Citations: 1
  • Government policies search using marathi speech recognition system-based on mfcc with gamma-tone filter
    M Parande, S Therese, V Shinde
    Citations: 1
  • Measurement of Human Attention levels using Artificial Intelligence Pattern Simulation
    K Pimparkhede, VD Shinde
    Solid State Technology 64 (2), 7352-7355 , 2021
    2021.0
  • Service Discovery Mechanism Using Dynamic Analysis
    K Pimparkhede, VD Shinde
    Solid State Technology 64 (2), 6557-6564 , 2021
    2021.0
  • Measurement of Human Attention levels using Artificial Intelligence Pattern Simulation
    VDS Kunal Pimparkhede
    Solid State Technology 64 (2), 3461-3465 , 2021
    2021.0
  • Human Identification Using Motion Vector Analysis
    C D'Souza, S Gaikwad, V Shinde
    International Journal in IT & Engineering 7 (5), 1-7 , 2019
    2019.0