AI engineer Founder Theatre artist

Gargeya Sharma.

Architecting intelligence. Curating art.

Founder & Lead AI Architect at Edudojo.ai

I build AI systems for learning, assessment, and automation, combining research with product engineering.

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The work, so far

Experience

Technical depth.
Human intuition.

From research and financial data to building AI products. A career shaped by making things work for people.

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May 2026 – Present Current role

Edudojo.ai

Founder & Lead AI Architect

Building Socratic AI for learning and assessment, shaped around how each learner thinks.

English and Hindi today, with an architecture designed for more languages.
Developing with Parishkar College (Autonomous) as a 3,000-student research lab, drawing on its director’s expertise in pedagogy and human development.
Building progress tracking for learners, teachers, and evaluators to measure support over time. Individual journeys help teachers and AI tailor its content, approach, and timing.

AI architecture
Generative AI
Education strategy

Nov 2025 – May 2026London, UK

Evvolv

Founding AI Engineer / Member

Co-founded and engineered a multi-agent system to automate business workflows for small and medium enterprises.

Multi-agent systems
n8n
Business automation

Jul 2024 – Nov 2025London, UK

RVS Consensus+

Data Scientist & Automation Specialist

Built data pipelines and real-time dashboards processing 10M+ transaction rows from SIX, Reuters, and 15+ global Tier-1 banks.

Standardized Python prototyping and dashboard templates across the team, making the path from idea to demo to production approximately 20× faster.
Automated bank rate-submission operations around mid-month and month-end reporting, saving 5+ hours daily.

Python
SQL
Data pipelines
Dash / Plotly

Jul 2023 – Oct 2023London, UK

Imperial College London

Machine Learning Consultant

Developed data-driven control methods for flapping-wing micro-aerial vehicles at the Flapping Wing MAV Lab.

Machine learning
Robotics
Control systems

Alongside the technical work

Dec 2022 – Nov 2025London, UK

Working with people, in real time.

VIP Bartender · Mitchells & Butlers / Compass Group

Worked at AllBarOne Leicester Square while pursuing my master’s. A hands-on education in reading a room, teamwork under pressure, and thinking on my feet.

Education

A foundation of curiosity.

The theory behind the practice.

Sep 2022 – Sep 2023London, UK

Distinction

M.S. in Artificial Intelligence

Queen Mary University of London

Deep learning, computer vision, and large language models. Dissertation on unsupervised machine translation using visual signals as rewards for reinforcement learning.

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Jun 2018 – Aug 2022Dehradun, India

8.77 CGPA · With Honors

B.Tech. in Computer Science

University of Petroleum & Energy Studies

Specialized in Cyber Security and Forensics; independently studied machine learning and deep learning. Student Placement Representative in the final year.

Computer science
Cyber security
Machine learning

Selected work

Ideas, made tangible.

Independent tools, research, and writing.
From experiments to published work.

Desktop dictation

Odicto

Speak into any desktop app. Your words appear at the cursor, without switching away from your work.

My contributionBuilt a hold-to-talk workflow with local Whisper or cloud transcription, plus optional AI replies.

Dictation
Whisper
Python
Desktop

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Android voice keyboard

Odicto Mobile

Dictate directly into Android text fields, with transcription running through the phone and no desktop connection.

My contributionBuilt a voice keyboard with streaming text, a floating microphone control, and a choice of AI providers.

Android
Kotlin
Capacitor
Speech-to-Text

Explore the code

Journal paper 2022

Automatic surface crack detection using segmentation-based deep-learning approach

Read paper

Deepa Joshi, Thipendra P. Singh & Gargeya Sharma

Engineering Fracture MechanicsVol. 268 · Article 108467

Pixel-level surface crack detection using deep learning, with a manually annotated dataset of 3,000 images.

Book chapter 2022

Object Detection Frameworks and Services in Computer Vision

Read chapter

Sachi Choudhary, Rashmi Sharma & Gargeya Sharma

Object Detection with Deep Learning Models: Principles and ApplicationsChapter 2 · pp. 23–47 · Chapman & Hall/CRC

A coauthored guide to the frameworks and services used to build object detection systems in computer vision.

Open source

proof

A verification-first plugin for coding agents. One router sends each task to a matching workflow (grilling, test-driven development, codebase design, writing for agents) and treats done as passing checks. It works the same on Claude Code, Codex, Grok and other Agent Skills hosts.

Open source

Adversary-Planner-Loop

An agent loop that challenges generated plans with a simulated adversary, then refines them before code execution.

Open source

TwinAatma

A personal AI agent exploring how custom knowledge and speech patterns can shape a digital counterpart.

Open source

Portfolio-CV-Webpage

The source for this digital CV: a responsive Next.js site with research citations, project filters, and a printable layout.

Open source

Documenter-MCP

An MCP server that scans codebases for documentation gaps and generates improvements using AI agents.

Open source

DataCleanOpenEnv

Automated data-cleaning submission for the OpenEnv Hackathon organized by Scaler School, Meta, and Hugging Face.

Research

MSc AI Research

Research code from an AI master’s completed with Distinction at QMUL, exploring reinforcement learning and computer vision.

Technical writing

Analytics Vidhya

17+ articles explaining computer vision and neural networks, including denoising autoencoders and YOLO object detection.

More of what I’m making, thinking, and exploring.

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