Building high-performance systems at the intersection of Deep Learning, Scalable Web Architecture, and Product Design.
I architect intelligent web applications that bridge the gap between complex data and intuitive user experiences. My work ranges from restoring ancient history through Multi-modal Vision-Language (VL) OCR to building real-time FinTech pipelines. I specialize in end-to-end systems that combine deep learning research with scalable cloud architecture.
- 🔭 Current Focus: Multi-modal VL OCR for ancient text restoration, Scalable Data Pipelines & Optimizing Chess Engine intuition models.
- 🌱 Learning: Advanced ONNX optimization, AWS Lambda for inference scaling, and fine-tuning Vision-Language Models (VLMs).
- 💬 Ask me about: Next.js, PyTorch, Chess theory, or litigation funding systems.
| Category | Tools & Technologies |
|---|---|
| UI & Styling | Tailwind CSS, HeroUI, Shadcn UI, Lucide React, Framer Motion |
| Frontend | Next.js, React, TypeScript, PHP |
| Backend | Node.js, Flask (Python), NGINX, Laravel |
| Databases | PostgreSQL, MongoDB, Supabase |
| AI / Data | PyTorch, ONNX, Deep Learning (NLP/CV), Matlab, Data Ingestion Pipelines |
| Systems & Hardware | C, C++, VHDL, Arduino, Raspberry Pi |
| DevOps | AWS (S3/EC2), Vercel, Docker Compose, GitHub Actions |
- Ancient Text Restoration (UATRIAL): Developed models using Deep Learning to restore and attribute ancient epigraphy, merging history with state-of-the-art NLP.
- Neural Chess Engines: Training models on FEN/PGN datasets to predict moves, served via Flask APIs to custom Next.js frontends. Experimenting with Stockfish fine-tuning and custom evaluation functions.
- AI File Converter: Built an end-to-end application that converts various file formats into standardized PDFs, enabling seamless RAG-based inference for AI models.
- AxiaFunder: Architected real-time investment dashboards and robust CSV ingestion pipelines for litigation funding using Node.js and PostgreSQL.
- Hack Cambridge: Maintained critical administration platforms for one of the UK’s premier hackathons.
- End-to-End Pipelines: Specialized in "Browser → Cloud Storage → Background Worker → Database" workflows for high-frequency data processing.
"Build systems that are interactive, intelligent, and scalable. Prioritize clean architecture over quick hacks, and use AI to simplify — not complicate — the user experience."
I’m always open to collaborating on intelligent systems, web platforms, or anything chess-related.
- 🌍 Portfolio: Visit my site
- 💼 LinkedIn: linkedin.com/in/pragash-mohanarajah
- 🔥 Current Streak: 0 days
- 🏆 Longest Streak: 26 days
- ✨ Total Commits: 9,008
- 💖 Commit Breakdown: 561 public (6.2%), 8,447 private (93.8%) · 5,742 owned (63.7%), 3,266 contributed (36.3%)
- 🚀 Repositories: 90 (35 public (38.9%), 55 private (61.1%))
- 👤 Ownership: 86 owned (95.6%), 4 contributed-to (4.4%)
- ⭐ Stars: 39 · 👀 Watchers: 38 · 🍴 Forks: 18 · 🗄️ Archived: 21
- 🧠 Estimated Lines of Code: 1,771,673
- 🤝 Followers: 1 · Following: 11
- 📅 Account age: 1,994 days
C ██████████ 38.04% (673,946 LOC)
TypeScript ███ 13.72% (243,135 LOC)
Jupyter Notebook ███ 12.38% (219,406 LOC)
Python ███ 10.00% (177,251 LOC)
HTML ██ 6.46% (114,454 LOC)
JavaScript █ 5.74% (101,772 LOC)
Makefile █ 3.50% (62,016 LOC)
Roff █ 3.05% (54,070 LOC)
JavaScript ████ 17.72% (42 repos)
Python ███ 13.92% (33 repos)
CSS ███ 12.24% (29 repos)
TypeScript ███ 10.13% (24 repos)
HTML ██ 9.28% (22 repos)
Shell ██ 7.17% (17 repos)
Jupyter Notebook █ 5.49% (13 repos)
Dockerfile █ 4.64% (11 repos)
C ██████████ 38.04% (33,697,286 bytes)
TypeScript ███ 13.72% (12,156,707 bytes)
Jupyter Notebook ███ 12.38% (10,970,320 bytes)
Python ███ 10.00% (8,862,452 bytes)
HTML ██ 6.46% (5,722,638 bytes)
JavaScript █ 5.74% (5,088,560 bytes)
Other ████████████████ 64.44% (58 repos)
AI / ML ████ 17.78% (16 repos)
Web Apps ███ 11.11% (10 repos)
Data Systems ██ 6.67% (6 repos)
AI / ML ████████████████ 63.97% (1,133,411 LOC)
Other ███████ 27.28% (483,293 LOC)
Web Apps ██ 6.81% (120,592 LOC)
Data Systems 1.94% (34,377 LOC)
JavaScript ████████████ 46.67% (42 repos)
Python █████████ 36.67% (33 repos)
CSS ████████ 32.22% (29 repos)
TypeScript ███████ 26.67% (24 repos)
HTML ██████ 24.44% (22 repos)
Shell █████ 18.89% (17 repos)
Jupyter Notebook ████ 14.44% (13 repos)
Dockerfile ███ 12.22% (11 repos)
Batchfile ██ 6.67% (6 repos)
PLpgSQL █ 5.56% (5 repos)
- Pragash-Mohanarajah/dashboard-axiafunder — AxiaFunder Internal Dashboard Application built with Next.js and Vercel (Fork... (Web Apps · 1956 commits · private)
- Pragash-Mohanarajah/exambank-ai-frontend — Exambank AI - Frontend Code Repository (forked from AlphaFactory/exambank-fro... (AI / ML · 474 commits · private)
- Pragash-Mohanarajah/axia-lm-optimizer — Convert to PDF (Other · 376 commits · private)
- Pragash-Mohanarajah/ai-hdr-file-converter — Desktop File Converter Application: Local Conversion of Supported Files to PD... (AI / ML · 373 commits · private)
- Pragash-Mohanarajah/ai-hdr-inference — AI HDR Case Reviewer Software for Inference from large PDF files (AI / ML · 353 commits · private)
- AxiaFunder/dashboard-axiafunder (Other · 1992 commits · private)
- AxiaFunder/axiafunder — Monorepo for Axiafunder Applications (Other · 12 commits · private)
Night (00-06) 0.60% (21 commits)
Morning (06-12) █████████████ 53.43% (1,883 commits)
Afternoon (12-18) ████████ 31.87% (1,123 commits)
Evening (18-24) ████ 14.10% (497 commits)
Sunday ██ 8.15% (757 contributions)
Monday ███ 13.84% (1,286 contributions)
Tuesday █████ 18.14% (1,685 contributions)
Wednesday █████ 20.14% (1,871 contributions)
Thursday ████ 16.79% (1,560 contributions)
Friday ████ 16.36% (1,520 contributions)
Saturday ██ 6.59% (612 contributions)
AxiaFunder/dashboard-axiafunder ██████ 22.11% (1,992 commits)
Pragash-Mohanarajah/dashboard-axiafunder █████ 21.71% (1,956 commits)
Pragash-Mohanarajah/exambank-ai-frontend █ 5.26% (474 commits)
Pragash-Mohanarajah/axia-lm-optimizer █ 4.17% (376 commits)
Pragash-Mohanarajah/ai-hdr-file-converter █ 4.14% (373 commits)
Pragash-Mohanarajah/ai-hdr-inference █ 3.92% (353 commits)
Pragash-Mohanarajah/taec-examportal █ 3.12% (281 commits)
- Pragash-Mohanarajah/ai-hdr-inference — experiment: remove claimant_contact_concern_confidence score field from prompt and output schema
- Pragash-Mohanarajah/ai-hdr-inference — experiment: remove claimant_contact_concern_confidence score field from prompt and output schema
- Pragash-Mohanarajah/ai-hdr-inference — experiment: remove claimant_contact_concern_confidence score field from prompt and output schema
- Pragash-Mohanarajah/ai-hdr-inference — experiment: update ongoing prompt to capture client contact confidence score and narrative based status field
- Pragash-Mohanarajah/ai-hdr-inference — experiment: update ongoing prompt to capture client contact confidence score and narrative based status field
- Pragash-Mohanarajah/axia-lm-optimizer — fix: mark history log files as failures in conversion results to avoid pdf cleaning
- Pragash-Mohanarajah/axia-lm-optimizer — feat: clean history log lines with regex before passing to output folder
- Pragash-Mohanarajah/axia-lm-optimizer — release: v1.8 with hard-coded categorisation through config option
- Pragash-Mohanarajah/axia-lm-optimizer — Merge branch 'main' into feat/classification
- Pragash-Mohanarajah/axia-lm-optimizer — chore: move the history log processing to the file processor for ease of access
- Pragash-Mohanarajah/taec-examportal — Add export data function for priveleged users in attendance and written reports
- Pragash-Mohanarajah/taec-examportal — Add export data function for priveleged users in attendance and written reports
- Pragash-Mohanarajah/taec-examportal-backend — Add export data function for priveleged users in attendance and written reports
- Pragash-Mohanarajah/taec-examportal-backend — Optimised written routes to handle reports with data pipeline
- Pragash-Mohanarajah/taec-examportal — Correct endpoint calls for written attendance and report
- unoconv/unoserver
- moodle/moodle
- n15hsy/axia-lm
Last updated on Mon, 29 Jun 2026 02:33:47 GMT