An authoritative technical companion and scholarly archival mirror designed to synchronize functional implementations with research artifacts shared on the ResearchGate platform.
Source Code · Technical Specification · ResearchGate Profile
Research Lab · Overview · Pathways · Structure · Project Catalog · Usage Guidelines · License · About · Acknowledgments
Focusing on Artificial Intelligence, Web Engineering, and Computational Design.
Research Contributors
| Contributor | Role | Profile & ORCID |
|---|---|---|
| Amey Thakur | Principal Investigator | Profile ·  |
| Mega Satish | Principal Researcher | Profile ·  |
| Karan Dhiman | Collaborator | Profile |
| Hasan Rizvi | Collaborator | Profile |
| Mayuresh Phansikar | Collaborator | Profile |
| Archit Konde | Collaborator | Profile |
| Saakshi Deokar | Collaborator | Profile |
Note
This repository functions as a deterministic technical archival mirror for scholarly implementations. It synchronizes functional research outputs with the academic artifacts shared across the global ResearchGate network.
ResearchGate (Technical Archival) is a specialized scholarly companion architecture engineered to preserve, showcase, and mirror a diverse range of technical research projects linked to the ResearchGate network. By bridging the gap between theoretical system design and high-fidelity archival, this repository provides a foundational study into Machine Learning, Computational Intelligence, and Applied Software Engineering.
The repository functions as a deterministic technical corridor for complex algorithms and modern development frameworks, enabling high-performance research synchronization directly within a version-controlled environment.
The archival model is governed by strict computational design patterns ensuring fidelity and clarity:
- Archival Integrity: Systematic documentation of technical reports, preprints, and peer-reviewed articles.
- Multi-Domain Synthesis: Integration of varied research fields including Neural Networks, NLP, and Financial Optimization.
- Verification Standards: Every project goal is coupled with functional code, demos, and scholarly artifacts for zero-latency proof.
Tip
Scholarly Precision Integration
To maximize academic value, the repository employs a Formal Archival Strategy. Each project contains its own Technical Reports and Demos, strictly coupling implementation results with peer-reviewed validation. This ensures that the research remains accessible and provides a high-fidelity reference for the engineering community.
Note
Curriculum Roadmap: This repository is structured as a progressive computational curriculum. Follow these verified pathways to master specific domains, moving from Theoretical Foundations to Production-Grade Implementation.
From Neural Foundations to Generative Deep Learning.
graph LR
A[Neural Networks] -->|Theory| B[Bangalore Housing]
B -->|Regression| C[Neuro-Fuzzy]
C -->|Hybrid Systems| D[GANs]
D -->|Generative| E[White-Box Cartoonization]
E -->|Vision| F[Stock Trading RL]
style A fill:#e1f5fe,stroke:#01579b,stroke-width:2px
style F fill:#dbf5ee,stroke:#004d40,stroke-width:2px,stroke-dasharray: 5 5
From Database Schemas to Cloud-Integrated Web Architecture.
graph LR
A[Car Rental DB] -->|SQL| B[Digital Bookstore]
B -->|E-Commerce| C[Chat Room]
C -->|Async| D[Text Summarizer]
D -->|NLP| E[Pizza Chatbot AWS]
style A fill:#f3e5f5,stroke:#4a148c,stroke-width:2px
style E fill:#dbf5ee,stroke:#004d40,stroke-width:2px,stroke-dasharray: 5 5
Mastering Data Structures and Interactive Reasoning.
graph LR
A[Hangman Game] -->|Java Applets| B[QuadTree Visualizer]
B -->|Spatial Data| C[Computational Logic]
style A fill:#fff3e0,stroke:#e65100,stroke-width:2px
style C fill:#fff8e1,stroke:#fbc02d,stroke-width:2px,stroke-dasharray: 5 5
RESEARCHGATE/
│
├── docs/ # Project Documentation
│ └── SPECIFICATION.md # Technical Architecture
│
├── ResearchGate/ # Primary Engineering Layer
│ ├── Bangalore House Price Prediction/ # ML: Price Forecasting
│ ├── CHAT ROOM USING HTML.../ # Web: Chat Engineering
│ ├── Car Rental Database System/ # Data: Schema Design
│ ├── Digital Bookstore/ # Web: Bookstore Architecture
│ ├── Fundamentals of Neural Networks/ # AI: Core Theory & Implementation
│ ├── Generative Adversarial Networks/ # AI: GAN Research
│ ├── Hangman Word Game/ # Logic: Applet Deduction
│ ├── Neuro-Fuzzy - Artificial.../ # AI: Hybrid Systems
│ ├── Pizza Ordering Chatbot.../ # AI: AWS Lex Interaction
│ ├── Text Summarizer Using Julia/ # NLP: High-Performance Summarization
│ ├── White-Box Cartoonization.../ # AI: Extended GAN Framework
│ └── ResearchGate.png # Branding Asset
│
├── CITATION.cff # Project Citation Manifest
├── codemeta.json # Metadata Standard
├── LICENSE # CC BY 4.0 License
├── SECURITY.md # Security Protocols
└── README.md # Project EntranceNote
Click on each section below to expand and view the curated research projects with direct access to technical documentation and scholarly articles.
Hangman Word Game
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Project Goal: Hangman Word Game using Applet in Java.
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Authors: Amey Thakur, Mega Satish & Saakshi Deokar
Chat Room using HTML, PHP, CSS, JS, AJAX
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Project Goal: Web-Based Chat Application using PHP, MySQL, JS, AJAX.
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Authors: Amey Thakur & Karan Dhiman
Car Rental Database System
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Project Goal: Create a simple Car Rental Database Management System.
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Author: Amey Thakur
Digital Bookstore
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Project Goal: A responsive website of Digital Bookstore that lists all of the books that are currently available in the shop, along with their descriptions. The website allows users to browse books by category or author, search for a specific book, and see the entire description page of any book. You may also sort the results based on price or discount. The user may register and login on subsequent visits, check his or her basket and purchase the books they want. In the event of a problem, the user can submit a question, which is then forwarded straight to the administrator through email.
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Authors: Amey Thakur & Mega Satish
White-Box Cartoonization Using An Extended GAN Framework
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Project Goal: An implementation of the Whitebox Cartoonization model using Tensorflow.js and HTML/CSS/Javascript/Bootstrap.
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Authors: Amey Thakur, Mega Satish & Hasan Rizvi
Bangalore House Price Prediction
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Project Goal: Machine Learning Project to Predict House Prices in Bangalore.
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Authors: Amey Thakur & Mega Satish
Fundamentals of Neural Networks
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Project Goal: Understanding the concepts of neural networks and how to put them into practice.
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Authors: Amey Thakur & Archit Konde
Generative Adversarial Networks
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Project Goal: Comprehensive study and implementation of Generative Adversarial Networks (GANs).
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Authors: Amey Thakur & Mega Satish
Neuro-Fuzzy: Artificial Neural Networks & Fuzzy Logic
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Project Goal: Understand Neuro-Fuzzy - Artificial Neural Networks & Fuzzy Logic.
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Authors: Amey Thakur, Karan Dhiman & Mayuresh Phansikar
Optimizing Stock Trading Strategy With Reinforcement Learning
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Project Goal: The main emphasis and objective of our project is to analyse given raw data and do exploratory data analysis in order to fully comprehend and identify patterns. Then, using a Neural Network approach, construct a model and train it to get the desired outcomes. Finally, it will be deployed as a web application.
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Author: Amey Thakur
Text Summarizer
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Project Goal: In this project, we propose to implement a web application that can summarize a text or a Wikipedia link. We have additionally been given an opportunity to compare different methods of summarization.
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Authors: Amey Thakur & Mega Satish
QuadTree Visualizer
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Project Goal: An application capable of presenting a view of quad tree. Design and development of quad tree view and data model.
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Authors: Amey Thakur, Mega Satish & Hasan Rizvi
Pizza Ordering Chatbot Using Amazon Lex
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Project Goal: To learn how to use Amazon Lex to build a chatbot on AWS.
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Authors: Amey Thakur & Mega Satish
Important
Scholarly Integrity & Technical Validation
All artifacts archived in this catalog are strictly synchronized with published research. For verified academic references, please consult the provided DOI (Digital Object Identifier) links or the technical preprints located within the project corridors. Execution integrity for backend modules is documented through high-fidelity synthetic logic traces and scholarly attachment logs.
This repository is shared to support scholarly exchange and research archival.
For Students
Use this project as reference material for understanding Applied Machine Learning, Database Systems, and Web Architecture. The documentation facilitate self-paced learning and exploration of academic software engineering.
For Educators
This project may serve as a practical lab example or supplementary teaching resource for AI, Web Engineering, and Data Science courses.
For Researchers
The documentation and architectural approach may provide insights into systematic project archival, DOI integration, and scholarly metadata standards.
This repository and all its creative and technical assets are made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0). See the LICENSE file for complete terms.
Note
Summary: You are free to share and adapt this content for any purpose, even commercially, as long as you provide appropriate attribution to the original authors.
Copyright © 2022 Amey Thakur & Mega Satish
Created & Maintained by: Amey Thakur
This repository serves as a deterministic technical mirror for the ResearchGate platform, designed to archive high-fidelity engineering implementations. While established as a structural initiative for Academic Engineering, this repository stands as a testament to collective intellectual contribution. The projects archived herein are the result of a rigorous collaborative synergy, where the indispensable expertise of every lab member was fundamental to the realization of these research outcomes.
Connect: GitHub · LinkedIn · ORCID
Important
Scholarly Collaboration & Institutional Gratitude
This repository is the result of a rigorous collective effort. Special recognition is extended to the following researchers for their indispensable technical and theoretical contributions:
- Mega Satish: For extensive research in Generative Adversarial Networks (GANs), NLP summarization, and core engineering contributions that bridge the gap between theory and implementation.
- Karan Dhiman: For specialized contributions to Web Engineering and hybrid Neuro-Fuzzy architectural frameworks.
- Hasan Rizvi: For critical insights into Computer Vision and high-fidelity GAN framework analysis.
- Mayuresh Phansikar: For foundational research into Artificial Neural Networks and hybrid computational intelligence.
- Archit Konde: For scholarly exposition and theoretical research into the core principles of Neural Networks.
- Saakshi Deokar: For engineering implementations in interactive logic and the development of scholarly applet demonstrations.
Heartfelt thanks also to the mentors and peers whose encouragement, rigorous discussions, and academic support contributed meaningfully to the fidelity of this archival mirror.
Research Lab · Overview · Pathways · Structure · Project Catalog · Usage Guidelines · License · About · Acknowledgments
Computer Engineering (B.E.) - University of Mumbai
Semester-wise curriculum, laboratories, projects, and academic notes.