Bansilal Ramnath Agarwal Charitable Trust's

Vishwakarma Institute of Technology,Pune

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Home | PROF. DR. SATPALSING DEVISING RAJPUT

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PROF. DR. SATPALSING DEVISING RAJPUT

Designation:

Assistant Professor

Department:

Computer Engineering

Email :

satpalsing.rajput@vit.edu

Phone :

7588100300

 



Personal

Educational Qualification :

University Degree Year
Sri Satya Sai University of Technology and Medical Sciences Phd 2021
North Maharashtra University ME 2013
North Maharashtra University BE 2008


Date of Joining : 29/02/2024


Total Experience : 16 year:2 month

Experience :

Sr. No Organisation Designation From Date To Date Years of Experience
1 Softcore Solutions Thane Jr Programmer 18-Sep-2008 28-Nov-2009 1
2 SSBT's College of Engineering Technology Bambhori Jalgaon Lecturer 01-Jan-2010 31-May-2010 0
3 SSBT's COllege of Engineering Technology Bambhori Jalgaon Lecturer 05-Jul-2010 15-Jun-2011 0
4 SSBT's College of Engineering Technology Bambhori Jalgaon Assistant Professor 01-Jul-2011 05-Feb-2022 10
5 Pimpri Chinchwad College of Engineering Nigdi Pune Assistant Professor 08-Feb-2022 29-Feb-2024 2
6 Vishwakarma institute of Technology Pune Assistant Professor 01-Mar-2024 - 1

Invited Talks :

Sr. No Name Description Type Role From Date To Date
1 Generative Artificial Intelligence and Machine Learning Generative AI and Machine Learning (ML) are closely related fields within artificial intelligence. Generative AI refers to a subset of artificial intelligence techniques focused on creating new content, such as images, text, music, or even entire virtual worlds. It utilizes models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) to generate data that mimics the properties of real-world data.Machine Learning, on the other hand, is a broader field that involves teaching computers to learn from data and improve their performance over time without being explicitly programmed. ML algorithms identify patterns in data and make predictions or decisions based on that data. Supervised learning, unsupervised learning, and reinforcement learning are key approaches within ML, each serving different purposes and applications.Together, Generative AI and ML are revolutionizing various industries by enabling more sophisticated data analysis, creative content generation, and enhanced decision-making capabilities. STTP Participated 21-May-2024 25-May-2024
2 Confluence of Deep Learning, Generative AI and Data Science The confluence of deep learning, generative AI, and data science represents a powerful synergy in the field of artificial intelligence. Deep learning, a subset of machine learning, utilizes neural networks with many layers to model complex patterns in large datasets. Generative AI leverages these deep learning techniques to create new, synthetic data that resembles real-world data, enabling advancements in areas such as natural language processing, image synthesis, and automated content creation. Data science, which focuses on extracting insights and knowledge from data, benefits significantly from deep learning models' ability to handle and interpret vast amounts of complex data. Together, these technologies drive innovation, offering robust solutions across various domains, from healthcare to finance, by enhancing predictive analytics, automating tasks, and generating novel data-driven insights. FDP Participated 06-May-2024 10-May-2024
3 Recent Trends in Multidisciplinary Research Recent trends in multidisciplinary research emphasize the integration of diverse fields to address complex global challenges. Key trends include:Health and Technology Convergence: Integrating AI, big data, and biomedical research to advance precision medicine and public health.Sustainability and Environmental Sciences: Collaborative efforts between environmental science, engineering, and policy-making to combat climate change and promote sustainable development.Digital Humanities: Combining computational tools with humanities research to analyze cultural and historical data on a large scale.Smart Cities and Urban Planning: Using IoT, data analytics, and social sciences to design sustainable, efficient, and livable urban spaces.Neuroscience and Cognitive Computing: Merging neuroscience with AI to understand brain functions and develop advanced computational models. FDP Participated 29-Apr-2024 03-May-2024
4 Cognitive Computing for Smart Applications Cognitive computing for smart applications refers to the utilization of advanced technologies and algorithms that mimic human cognitive functions to enable intelligent behavior in various applications and systems. These applications leverage cognitive computing to process vast amounts of data, understand natural language, learn from interactions, and make informed decisions autonomously. FDP Participated 18-Mar-2024 22-Mar-2024
5 Advancements in Artificial Intelligence Artificial Intelligence (AI) has witnessed significant advancements in recent years, transforming various sectors and revolutionizing how we interact with technology. These advancements have been driven by breakthroughs in machine learning, deep learning, natural language processing, robotics, and other related fields. FDP Participated 04-Mar-2024 08-Mar-2024
6 NEP 2020 Orientation The National Education Policy (NEP) 2020 is a comprehensive framework that aims to transform the education system in India. Orientation and sensitization sessions are essential to familiarize stakeholders with the key provisions and objectives of the NEP 2020 and to foster understanding and ownership among them FDP Participated 01-Feb-2024 14-Feb-2024
7 Recent Trends in Computing 3.0 , Quantum Computing, FDP Participated 09-Oct-2023 13-Oct-2023
8 Data Science for Buisness Data Science for Business" is a field that involves applying data science techniques and methodologies to solve business problems and drive decision-making processes. FDP Participated 04-Sep-2023 08-Sep-2023
9 One Week National level FDP on Cloud Infrastructure A one-week national level Faculty Development Program (FDP) on Cloud Infrastructure can cover a broad range of topics related to cloud computing, focusing on both theoretical concepts and hands-on practical sessions. FDP Participated 21-Aug-2023 25-Aug-2023
10 Advanced Excel for Data Analytics- Hands on PivotTables,Advanced Functions,Chart and Graphs, Conditional Formatting FDP Participated 07-Aug-2023 12-Aug-2023
11 30 days Masterclass on Internet of Things At its core, IoT is about connecting the physical world with the digital world, creating a seamless network where information can flow freely between devices and systems. This connectivity enables a wide range of applications and services across various industries and sectors, including smart homes, healthcare, transportation, agriculture, manufacturing Industry Training Participated 12-Jul-2023 12-Aug-2023

International Journal:

  1. CR System with Efficient Spectrum Sensing and Optimized Handoff Latency to Get Best Quality of Service ,International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING,123
  2. Enhancing Medical Image Analysis Through Deep Learning-Based Lesion Detection ,International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING,123
  3. Exercise Movement Detection Using Spearman Correlation-basedSliding WindowTechnique ,International Journal ofINTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING,123
  4. Design and Implementation of Machine Learning-Based Network Intrusion Detection ,International Journal ofINTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING,123
  5. Student Engagement Monitoring in Online Learning Environment ,International Journal ofINTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING,123
  6. Enhanced Rainfall Prediction with Weighted Linear Units usingAdvanced Recurrent Neural Network ,International Journal ofINTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING,123
  7. Weighted Fusion of Pre-processing Techniques for Neural Network-based Image Haze Removal ,INTERNATIONAL RESEARCH JOURNAL OFMULTIDISCIPLINARY TECHNOVATION,123
  8. HYPERSPECTRAL IMAGE (HSI)-ASSISTED MULTI-LEVEL CROP CLASSIFICATION WITH SPINALNET-ENABLED FRACTIONAL LIGHT SPECTRUM OPTIMIZER ,Biomedical Engineering: Applications, Basis and Communications,124
  9. An efficient method for disaster tweets classification using gradient-based optimized convolutional neural networks with BERT embeddings ,MethodsX,124
  10. Thermal analysis of fuel cells in renewable energy systems using Generative Adversarial Networks (GANs) and Reinforcement learning ,Thermal Science and Engineering Progress,124

International Conference:

  1. Blockchain-Enabled Energy Management System for Distributed Renewable Energy Microgrids: Enhancing Security and Transparency in Energy Transactions ,ICREA,124
  2. Efficient Classification of Rotten and Healthy Bell Peppers Using an Optimized DenseNet121 Model ,ICCUBEA,125
  3. Deep Learning-based Crowd Surveillance and Density Estimation ,2ND IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND QUANTUM COMPUTATION BASED SENSOR APPLICATIONS,125
  4. Spam SMS Detection Using Natural Language Processing ,ICCUBEA,124

Book:

  1. Fundamentals of Artificial Intelligence and Machine Learning ,NA,123

Book Chapter:

  1. Designing a Decentralized IoT-WSN Architecture Using Blockchain Technology ,WSN and IoT an Integrated approch for smart applications,124


  1. Best Paper Presenter

Patents :

  1. INNOVATION ZONES FOR A MOBILE APPLICATION THAT USES BLOCKCHAIN AND CYBERSECURITY TO FIND IDENTIFY MI
  2. AI Based Crop health Monitoring Device
  3. TRANSFORMING BUSINESS DYNAMICS: AI AND ADVANCED MACHINE LEARNING IN ENTERPRISE RESOURCE PLANNING OPTIMIZATION
  4. EFFICIENT CHARGING STRATEGIES: GRIDINTEGRATED PV-SOLAR EV CHARGING MODES



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