Researching resource-efficient artificial intelligence and hardware acceleration — building open-source tools for AI, security, education and knowledge systems.
Doctoral research (NIT Goa) on hardware acceleration of Generative Adversarial Networks for FPGA-based edge devices — evolutionary and multifractal methods to stabilise training, and hardware-aware design for low-latency, low-power inference.
Multifractal Detrended Fluctuation Analysis embedded in the discriminator for stable, hardware-optimised synthetic image generation — without changing the core GAN architecture.
Genetic-algorithm-optimised generator with wavelet-based discrimination, synthesised on the AMD Kintex-7 KC705 with the lowest area footprint among compared implementations.
A 2D multifractal discriminator for fast synthetic-data generation, deployed on the Kintex-7 KC705 through the NNGen framework with verified hardware results.
Research and software are treated as one pipeline. Each paper is linked to its method, implementation and (where it exists) source code.
Some publications have no public code yet — those are listed as paper-only rather than inventing links. Verified implementations are shown with their exact repository.
Open-source tools, research implementations and degree projects from the charudatta10 profile — every card links to its exact repository or live site, no generic profile links.
A ~160-line minimalist LLM framework for Lua. Zero dependencies, zero vendor lock-in; agents, workflows and RAG in one file.
Static site with a client-only RAG chatbot over the founding figures of forensic science — WebLLM in the browser, no server, no API keys.
A composable, SPDX-compatible licensing framework — modular legal clauses instead of rewriting licenses, with monetisation built in.
Aggregated link hub — a curated, categorised collection of useful resources with custom link icons and fast setup.
Automates init, deploy, licence, readme and maintenance tasks across projects (now maintained as PowerShell modules).
Agent framework, retrieval-augmented generation and code translation, each running on local models.
Generate project documentation with a local LLM, produce illustrations locally, and a lightweight local chat interface.
Secure single-download file sharing, and a Lua reverse-engineering sandbox with static and dynamic analysis.
Foam + Raito personal knowledge graph, and a Docsify-powered notes & wiki site.
Showcase projects as tiles, ship any Python script as a single-file PWA, and organise files by tags.
Handwritten Devanagari script recognition system from the Bachelor's project (2015) — the same line of work as the ISVLSI publication on FPGA pre-processing.
2019 GAN research implementation (perceptual adversarial training experiments) — part of the doctoral exploration into stable GAN training that led to the INDICON publication.
Machine learning-based character recognition system with FPGA pre-processing (GEC Goa). Published at ISVLSI.
MFDFA-based ionospheric pattern analysis for earthquake detection (GEC Goa & IIT Bombay). Presented at IAMG.
Evolutionary + backprop training framework for improved GAN convergence (NIT Goa). Published at INDICON.
Every entry verified against ORCID and Crossref. DOIs resolve to the publisher; the two conference papers without DOIs link to their ORCID records.
Writing to make complex topics learnable — for students, for the open-source community and for myself.
A snapshot of current focus — research, learning and building.
Building decentralized AI infrastructure that integrates governance, distributed learning, and hardware-efficient optimization into a scalable open research ecosystem.
I build systems with logic, explore ideas with curiosity, and live with awareness. The concrete facts — education, experience, skills and achievements.
I am Charudatta Gurudas Korde — an engineer, developer, researcher, and educator driven by curiosity and depth. I think in systems. I build with intention. I research with discipline. And I teach to simplify complexity. My work lives at the intersection of architecture and abstraction — where ideas become structured systems and theory becomes implementation. I am drawn to decentralized technologies, open knowledge, and designing solutions that are minimal yet comprehensive.
Beyond engineering, I am a lifelong learner — anime, food, gardening, reading, and coding as a creative outlet. I value rest and reflection as much as productivity, and I believe technology should not only advance capability but also elevate awareness. Growth for me is holistic — intellectual, creative, and inner.
Research focus: hardware acceleration of GANs on FPGA-based edge devices. National Institute of Technology Goa.
Master's project: multifractal analysis of ionospheric TEC as a seismic precursor (GEC Goa & IIT Bombay).
Bachelor's project: handwritten Devanagari script recognition with FPGA pre-processing (GEC Goa).
Teaching Incident Response and Vulnerability Assessment & Penetration Testing (VAPT), integrating applied cybersecurity practice with system-level analysis and research-informed instruction.
Laboratory instruction in Basic Electronics — circuit fundamentals, measurement techniques and applied engineering principles.
Doctoral research in FPGA-based AI acceleration — GAN architectures, hardware-software co-design, and resource-efficient intelligent systems. Academic mentoring and laboratory guidance as Teaching Assistant.
Validated Quartus tool flows, contributing to verification processes, workflow robustness and software quality assurance.
Analytical and software development projects spanning medical signal analysis, data-intensive systems and automation tooling; open-source utilities for documentation generation, file-system organization and programmatic graphics.
Research collaboration, hardware-accelerated ML, security education and mentorship.