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Vol. 26 / Edition I2026
A portfolio byPragadeeswaran K
Tiruvannamalai, IN · —Available for work
§ HelloI'm an engineer

PragadeeswaranKbuilding human-centered AI.

I'm Pragadeeswaran K — an AI/ML engineer building human-centered AI products. I take machine learning ideas from notebook to production with fast experiments, clean engineering, and interfaces people actually want to use. CGPA 9.39 / 10.

Source codeView work
Portrait of Pragadeeswaran K, AI/ML Engineer based in Tiruvannamalai, IN
fig. 01 — authorest. 2004
12.22°N · 79.07°EIST · UTC+5:30
Computer VisionReinforcement LearningAgentic SystemsGenerative ModelsComputer VisionReinforcement LearningAgentic SystemsGenerative ModelsComputer VisionReinforcement LearningAgentic SystemsGenerative ModelsComputer VisionReinforcement LearningAgentic SystemsGenerative Models
/ Affiliations & trust

Programs &
institutions

NPTEL
SRMIST
—/ Console — A nostalgic detour

Try the $ help command.

01/ About — A short profile

Notebook to production,
with a designer's eye.

Pragadeeswaran K — AI/ML Engineer profile picture

Pragadeeswaran K

AI/ML Engineer

Open to work

Hello, I'm Pragadeeswaran K — an AI/ML engineer building human-centered AI products. I ship reliable machine learning systems with clean, production-ready UX, turning quick research experiments into stable products that people actually use. My focus is computer vision, agentic systems, and efficient ML on the edge and in the cloud.

A B.Tech AI graduate from SRM Institute of Science and Technology with a CGPA of 9.39/10. I love taking research-grade ideas — diffusion models, deep reinforcement learning agents, vision transformers — and pairing them with thoughtful design so they feel obvious to use.

Computer VisionDeep LearningReinforcement LearningAgentic AIEfficient/Accelerated MLApplied Statistics
02/ Research — Areas of focus

What I'm obsessing over.

These are the research and engineering threads I keep pulling on — from computer vision and deep learning to reinforcement learning, agentic AI, generative models and efficient ML for the edge. Together they shape the kind of human-centered AI products I most enjoy building.

01
/ area

Computer Vision

Building intelligent systems that perceive and interpret visual data — from object detection to 3D scene reconstruction.

DetectionSegmentation3DNeRFs
02
/ area

Deep Learning

Architecting deep neural networks to solve complex, high-dimensional problems in perception, language and reasoning.

TransformersCNNsOptimizationBackprop
03
/ area

Reinforcement Learning

Developing agents that learn optimal policies through trial, error, and reward maximization across simulated and real-world tasks.

Q-LearningPolicy GradientsMulti-AgentSim-to-Real
04
/ area

Agentic AI

Designing autonomous AI agents capable of multi-step reasoning, tool use, planning and self-correction over long horizons.

CoTTool UseMemoryAutonomy
05
/ area

Efficient/Accelerated ML

Optimizing model architecture and inference pipelines for edge devices, GPUs and low-latency, cost-aware applications.

QuantizationPruningDistillationTensorRT
06
/ area

Applied Statistics

Applying statistical rigor to extract meaningful, defensible insights from noisy, messy real-world datasets.

Hypothesis TestingBayesianRegressionEDA
07
/ area

NLP

Bridging human-computer interaction through advanced understanding and generation of natural language at scale.

BERTGPTTokenizationRAG
08
/ area

Generative Models

Exploring the frontiers of synthesis — high-fidelity images, text and audio generated from rich latent representations.

DiffusionGANsLLMsPrompting
03/ Stack — Tools of the trade

The technical arsenal.

Pragadeeswaran K works across the full ML stack — from Python, PyTorch and TensorFlow for deep learning research, to Next.js, React and Tailwind for shipping AI products. The trade-craft below is grouped by the layer it serves: languages, AI/ML frameworks, data science, web, cloud and developer tools.

LLanguages
AAI / ML
DData Science
WWeb
CCloud / DevOps
TTools
04/ Education — Academic foundation

Where I learned to think.

Pragadeeswaran K is a B.Tech Artificial Intelligence graduate of SRM Institute of Science and Technology, with a CGPA of 9.39/10. Coursework spans deep learning, computer vision, reinforcement learning, statistics and modern ML systems — complemented by independent research and open-source projects.

01
SRM Institute of Science and Technology

B.Tech, Artificial Intelligence

SRM Institute of Science and TechnologyChennai, India

2022 — 2026
9.39
/ 10.0CGPA
02
Jeeva Velu International School

Higher Secondary (Class 12)

Jeeva Velu Intl. School

2022
81.8
/ 100Score
03
Sri Siksha Kendra International School

Secondary (Class 10)

Sri Siksha Kendra Intl. School

2020
83.4
/ 100Score
05/ Experience — Where I've shipped

From firmware to applied AI.

A condensed timeline of where I've shipped real software — from embedded firmware on ESP32 devices to AI/ML student research and production-grade open-source work. Each role below pairs a clear outcome with the practices that made it repeatable.

01 Active
Jan 2024 — Present
Remote

Technical Projects & Open Source

Independent Work

  • 01Built Acadion Mobile; portfolio with Next.js 14 & Tailwind; CI/CD and testing workflows
  • 02Contributed to open-source (Seat Finder, Acadion Mobile, Raspberry Pi Security Camera)
02
Jun 2023 — May 2026
Chennai, India
SRM

AI/ML Student Researcher

Self-Directed Study and Coursework, SRMIST

  • 01Designed and executed ML experiments; reproducible pipelines and ablations
  • 02Statistical analysis with Python/SPSS: hypothesis tests, correlation, regression
  • 03Baseline replication and literature review; presented findings and mentored peers
03
Feb 2025 — Feb 2026
Denmark (Remote)
Protechme

Embedded Firmware Engineer

Linucare / Protechme • SRM University

  • 01Developing ESP32 firmware modules for communication logic, peripheral control, and device telemetry.
  • 02Optimizing power budgets through task scheduling, sleep-state strategies, and hardware-level tuning.
  • 03Improving signal acquisition, data handling, and system responsiveness for low-power connected devices.
  • 04Driving power profiling efforts and contributing to core firmware documentation and architecture decisions.
04

Internships & Virtual Programs

AICTE Eduskills, Google Android Developer, ALTAIR

  • 01AWS AI-ML Virtual Internship: SageMaker, deployment, MLOps
  • 02AWS Data Engineering: pipelines, ETL, warehousing
  • 03Android Dev: Material Design, architecture components
  • 04ALTAIR Data Science Master: analytics, visualization, modeling
06/ Selected work — Builds & experiments

A small archive of things I've made.

A curated set of AI/ML and full-stack projects that show how I move from research ideas to reliable, shipped products — from GPU-accelerated pipelines to production-ready tools and education apps.

·04 results
Preview of the acadion mobile repository — built with TypeScript
Open
01

acadion mobile

Fast, privacy‑conscious SRM Academia app with attendance insights, schedule, and grades.

TypeScript
Preview of the EduSmartBot repository — built with Python
Open
02

EduSmartBot

AI-native study studio built with Flask featuring timetable planning, vision-enhanced OCR, adaptive quiz generation, intelligent web research, and an Ollama-powered tutoring chatbot.

Python
Preview of the seat finder repository — built with TypeScript
Open
03

seat finder

SRMIST Exam Seat Search: Parallel scraper with clean UI; export results as PNG/PDF; share via WhatsApp.

TypeScript
Preview of the Self driving car repository — built with Python
Open
04

Self driving car

🚗🤖 AI Autonomous Driving Simulation using Deep Q-Learning Neural Networks with real-time PyTorch training, GPU acceleration, and interactive pygame visualization. Watch AI evolve from crashes to championship-level driving!

Python
07/ Credentials — Verified skills

Things I've studied & passed.

Verified credentials from AWS Academy, Oracle Cloud, NPTEL and SRMIST hackathons — covering machine learning, data engineering, cloud foundations, generative AI and core CS topics. Filter by issuer or search to jump directly to the certificate you're curious about.

NPTEL
Verified

NPTEL: Programming in Java

ID — R2MO53View
NPTEL
Verified

NPTEL: Database Management System

ID — 2X2F1IView
NPTEL
Verified

NPTEL: Computer Architecture

ID — 34H7TXView
Verified

Oracle Cloud Infrastructure 2024 GenAI Certified Professional

ID — 1Q72Z7View
Verified

Oracle Cloud Computing Foundations

ID — 24I2K4View
Verified

AWS Academy: Machine Learning Foundations

ID — 49UKACView
Verified

AWS Academy: Data Engineering

ID — 1C14IDView
Verified

AWS Academy: Cloud Foundations

ID — 2UB5GDView
Hackathon
Verified

Hackathon: CINTEL Digithon

ID — 2ICQECView
Hackathon
Verified

Hackathon: Hackstreet 3.0

ID — 3EYKOEView
Hackathon
Verified

Hackathon: Webathon 2.0

ID — 59K5SDView
08/ Honors — Recognition

Small badges & big lessons.

A handful of recognitions earned along the way — top-decile academic performance, national virtual internships, multi-cloud certifications, hackathons and open-source experience kits. Each one came with a lesson that's shaped how I approach AI/ML engineering today.

SRMIST
No. 01

Top Decile CGPA — 9.39/10

SRM Institute of Science and Technology2022 — 2026

Ranked in the top decile with a 9.39 CGPA while completing AI core labs, electives, and project work.

CGPA9.39 / 10
FocusAI labs & electives
Academic ExcellenceSRMIST
No. 02

AICTE x AWS Virtual Internship (AI-ML + Data Eng)

AICTE Eduskills • AWS Academy2024

Completed national virtual internship tracks focused on SageMaker workflows, MLOps, and analytics pipelines with weekly mentor reviews.

TracksAI-ML & Data
DeliverablesEnd-to-end labs
NPTEL
No. 03

Multi-cloud & NPTEL Certification Streak

Oracle • AWS Academy • NPTEL2023 — 2024

Finished 9 industry-backed credentials spanning Oracle Cloud, AWS cloud/data/ML, and NPTEL core CS courses to reinforce fundamentals.

Credentials9 issued
DomainsCloud • ML • CS
SRMIST
No. 04

Rapid Hackathon Builder

CINTEL Digithon • Hackstreet 3.0 • Webathon 2.02024

Led small teams to deliver polished MVPs for social impact, developer workflows, and education challenges within 24–36 hour hackathons.

Events3 shipped
RoleLead dev & UI
No. 05

Open-source Experience Kits

GitHub CommunityOngoing

Documented and released reproducible guides for projects like Acadion Mobile, Seat Finder, and a Raspberry Pi security camera to help peers learn faster.

Projects4+ shipped
FocusDocs & UX
Open SourceDocumentation
09/ Leadership — Impact & community

Building with people, not just for them.

Building human-centered AI is a team sport. The work below — leading hackathon pods, maintaining open-source experience kits and facilitating community programs — is where I've practiced moving from solo prototypes to shared, reusable software with teammates and contributors.

SRMIST
No. 01

Hackathon Pod Lead

CINTEL Digithon • Hackstreet 3.0 • Webathon 2.0

2024 — 2025

Formed cross-functional pods and shepherded AI + UX MVPs from idea to demo-ready builds under 24–36 hour hackathon timelines.

3 shippedHackathons
4–6 buildersTeam size
See proof
No. 02

Open-source Maintainer & Docs Steward

GitHub Community

2022 — Present

Package personal projects (Acadion Mobile, Seat Finder, Raspberry Pi Security Camera) into plug-and-play templates with walkthrough docs and Loom-style demos.

4 releasedStarter kits
35+Clones/Forks
See proof
No. 03

Community Programs & Labs

AICTE Eduskills • Google Android • Altair & more

2023 — 2024

Active in national upskilling cohorts and virtual internships, sharing recap notes, mini-projects, and curated resources so peers can keep pace with fast-moving ML trends.

5+ cohortsPrograms
8 shippedMini projects
10/ Contact — Say hello

Let's build something.

Send a message.

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