Aadavn NimalthasNimalthas Imaging

I love creating images.

But editing them can be harder than capturing them.

What if transforming a photo felt as effortless as taking it?

Aadavn Nimalthas — software engineer, image maker, and builder of creative technology.

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The origin

Why any of this exists

  1. Photography and visual creation

    I loved creating images.

  2. The problem

    Editing became more complicated than creating.

  3. The question

    What if technology could handle the tedious parts?

  4. Engineering

    Computer science gave me a way to turn that question into systems.

  5. Nimalthas Imaging

    Now I build tools that make visual creation more capable and accessible.

Introducing Nimalthas Imaging

Tools for a more natural creative workflow

Modern photo and video workflows are powerful, but that power often arrives as friction. The creative idea gets buried beneath repetitive adjustments, disconnected tools, and technical overhead.

What it is

Nimalthas Imaging explores intelligent software that handles more of the tedious work while keeping creative decisions in the hands of the person making the image.

The vision

Make advanced imaging technology understandable, accessible, and genuinely useful.

Real output from the artifact-controlled upscaling work — limited detail on the left, reconstructed result on the right.

Computational imaging

HCAISSR

Problem
Meaningful visual information is lost when image detail is limited.
Idea
Explore intelligent reconstruction rather than simple enlargement.
Role
Designed and built the six-engine pipeline end to end.
Direction
Investigate practical, perceptually aware image restoration.
Explore HCAISSR
One image, separated into the red, green and blue information it is made of — then recombined

Imaging and color

Chroma

Problem
Color workflows can be powerful but difficult to reason about.
Idea
Make color relationships visible and controllable.
Direction
Explore better interfaces and systems for color decisions.
The same frame, before and after its tonal relationships resolve

Imaging and light

Luma

Problem
Tonal decisions influence what an image communicates.
Idea
Make luminance easier to understand and shape.
Direction
Explore intelligent assistance for light and tone workflows.
An ungraded mountain landscape, flat and low-contrastThe same landscape graded by MagicTrick
Photo by Ilya Bunin · graded by magictrickNET

Product

MagicTrick

Problem
Grading a picture well takes tools, time and expertise most people don't have.
Idea
Run the whole grade in the browser and ask the user for nothing but the picture.
Role
Founder — model, application, billing and accounts.
Direction
Demonstrate that serious imaging can be effortless and private.

Beta 2 in development

Explore MagicTrick
RequirementInterfaceServicesContentAuth · Data · Deploy

Four subdomains, one system: corporate, app, portfolio and support.

Product engineering

The Nimalthas platform

Problem
Building a coherent platform requires more than isolated screens.
Idea
Design the system and the experience as one product.
Role
Designed, built and operates the whole platform — site, app, blog, support and admin across four subdomains.
Direction
Demonstrate end-to-end product engineering.
Explore The Nimalthas platform

Method

Engineering is a sequence of decisions.

Modern tools can accelerate implementation. The engineering still lives in how the problem is framed, how the system is designed, and how the result is tested.

  1. 01Understand the problem

    What is actually broken, for whom, and why does it matter?

  2. 02Research possible solutions

    What exists, what failed before, and what constraint is doing the damage?

  3. 03Design the system

    Boundaries, data flow and failure modes before any implementation.

  4. 04Validate assumptions

    Prototype the risky part first; measure instead of hoping.

  5. 05Create implementation plans

    Small, testable stages with a defined finish line.

  6. 06Use appropriate tools to accelerate development

    AI-assisted where it helps, hand-written where it counts — judged, reviewed, owned.

  7. 07Review, test, and iterate

    Tests prove the behaviour; iteration earns the polish.

Software engineering

From requirement to running system

System design, architecture, technical planning and responsible AI-assisted development — proven across an offline C++ imaging pipeline, real-time AR reconstruction, and the platform this site runs on.

The software work in depth

Imaging and media

Domain knowledge, not decoration

Working with cameras, color, live production, and post-production gave me direct experience with the workflows I now want to improve through software.

North Shore Mountains View
Chureito Pagoda with Mount Fuji
Fushimi Inari Torii Gates
Pudong Skyline from the Bund

The story becomes the work.

Browse the work

Selected work

The work itself

The company

Nimalthas Imaging

Modern photo and video workflows are powerful, but that power often arrives as friction.

Make advanced imaging technology understandable, accessible, and genuinely useful.

Explore Nimalthas Imaging

Computational imaging

HCAISSR

Meaningful visual information is lost when image detail is limited.

Investigate practical, perceptually aware image restoration.

Explore HCAISSR

Product

MagicTrick

Grading a picture well takes tools, time and expertise most people don't have.

Demonstrate that serious imaging can be effortless and private.

Beta 2 in development

Explore MagicTrick

Product engineering

The Nimalthas platform

Building a coherent platform requires more than isolated screens.

Demonstrate end-to-end product engineering.

Explore The Nimalthas platform

Imaging and color

Chroma

Color workflows can be powerful but difficult to reason about.

Explore better interfaces and systems for color decisions.

Imaging and light

Luma

Tonal decisions influence what an image communicates.

Explore intelligent assistance for light and tone workflows.

Real-time AR

LiDAR 3D Hand Reconstruction

Flat hand tracking loses the depth that makes gestures spatial.

Real-time 3D hand skeleton reconstruction on-device, fusing Vision hand pose with ARKit depth through a modular RealityKit renderer.

Explore LiDAR 3D Hand Reconstruction
Aadavn Nimalthas

About Aadavn

Between a terminal and a viewfinder

I’m Aadavn Nimalthas, a Computer Science student at Simon Fraser University. I’m interested in the systems behind how we create, process, and experience visual media. My work brings together software engineering, AI, imaging, and hands-on creative production.

Photography and videography taught me where creative workflows become frustrating. Computer science gave me a way to investigate those problems and build tools around them.

Profile

The same work, in detail — experience, education, skills and the full project list.

Résumé page and PDF

01

Experience

Vancouver, BC

FounderNimalthas Imaging

Building local-first intelligent imaging tools. Shipped MagicTrick end to end — the grading model, the web application, subscription billing and accounts.

  • Designed and shipped MagicTrick, a browser-based grading application
  • Built the company site, blog and support platform across four subdomains
  • Runs all image processing client-side so pictures never leave the browser
Vancouver, BC

Photographer, Videographer & Live ProductionIndependent

Photography, hybrid video and full live-event AV production for community events, weddings and broadcasts.

  • Ran sound and full AV for Gayatri Havan and other multi-camera live events
  • Self-taught OBS, live switching and streaming workflows from a phone setup
  • Shoots full-manual on Sony bodies; handles capture through post and delivery

02

Education

Burnaby, BC

Simon Fraser UniversityBSc Computing Science

Currently focused on image sampling and upscaling research, in the territory staked out by AMD FSR and NVIDIA DLSS.

8 relevant courses
  • CMPT 225 · Data Structures and ProgrammingData Structures · Big-O Analysis · Trees & Linked Structures · Algorithm Design
  • CMPT 125 · Programming IIC++ · Object-Oriented Programming · Recursion · Abstraction
  • CMPT 120 · Introduction to ProgrammingPython · Control Flow · Functions · Problem Solving
  • CMPT 105W · Computing Science WritingTechnical Communication · Critical Thinking · Structured Writing
  • MACM 101 · Discrete Mathematics ILogic · Proof Techniques · Combinatorics
  • MATH 232 · Linear AlgebraMatrix Operations · Vector Spaces · Transformations
  • MATH 152 · Calculus IIIntegration · Series · Pattern Recognition
  • MATH 150 · Calculus IDerivatives · Optimization · Mathematical Modeling
Vancouver, BC

Killarney Secondary SchoolSecondary

6 relevant courses
  • Computer Science 12Programming · Algorithms · Code Organization
  • Computer Science 11Programming · Algorithms · Logical Reasoning
  • Computer Programming 11Programming Fundamentals · Logic · Debugging
  • Computer Information Systems 12IT Systems · Systems Thinking
  • Electronics and Robotics 10Electronics Basics · Robotics · Systems Thinking
  • Pre-Calculus 12Advanced Functions · Trigonometry · Analytical Reasoning

03

Skills

Languages

  • C++

    CMPT 125 and CMPT 225 at SFU, focused on OOP, recursion and complexity-aware implementation; then HCAISSR.

  • Python

    Introduced in CMPT 120, then expanded through self-directed tooling and research prototypes.

  • Swift

    Self-taught through Swift Playgrounds, deepened via iOS and AR work with ARKit, RealityKit and Vision.

  • TypeScript
  • Java
  • C
  • MATLAB

Core Computer Science

  • Data Structures

    CMPT 225: linked structures, trees, sorting and searching, ADT design.

  • Algorithmic Complexity

    CMPT 225, analysing time and space complexity and validating tradeoffs under real constraints.

  • Recursion
  • Sorting & Searching
  • Trees & Graphs
  • Hashing

Low-Level & Memory

  • Pointers & Memory

    C and C++ implementation work, with emphasis on correctness, ownership and runtime behaviour.

  • Manual Memory Management
  • Low-Level Debugging
  • SIMD & Hardware Acceleration

Design & Architecture

  • Object-Oriented Design
  • Abstraction & Code Organization
  • API Design
  • Modular Pipeline Architecture

Systems & Performance

  • Performance Optimization
  • Profiling & Debugging
  • Architectural Thinking
  • Working Under Resource Constraints

Imaging

  • Signal Processing
  • Super-Resolution
  • Colour Grading
  • Live Multi-Camera Production
  • Post-Production

Transferable

  • Technical Writing
  • Documentation
  • Iterative Development
  • Cross-Disciplinary Thinking
  • Planning & Organization

04

Projects

  1. 01

    Classical Reconstruction-Based Super-Resolution

    A non-learning single-image SR pipeline posed as an inverse problem: progressive upscaling, edge-guided refinement and iterative back-projection.

    Python · NumPy
  2. 02

    Artifact-Controlled Image Upscaler

    A stable, explainable CLI upscaler built around artifact control — anti-ringing, edge protection, adaptive sharpening — rather than hallucinated detail.

    Python

Coursework and supporting work

05

Tools

  • C++5
  • Next.js2
  • Python2
  • TypeScript2
  • ARKit
  • CUDA
  • Java
  • MATLAB
  • Metal
  • NEON SIMD
  • NumPy
  • PostgreSQL
  • RealityKit
  • Spring Boot
  • Stripe
  • Supabase
  • Swift
  • TensorFlow.js
  • Thymeleaf
  • Vision
  • Vulkan

Superscript is the number of listed projects using it.

06

Contact

Currently looking for Software Engineering Co-op opportunities for 2026. If you are working on something interesting, I would like to hear about it.

Send a message

Insights

Notes on imaging, product decisions and the work in between.

  1. How to Take Better Night Photos With a Phone

    Find useful light, stabilize the phone and control bright signs without making the scene look like daytime.

  2. Claude Is Watermarking Its Output, and That Is the Smaller Half of the Story

    Anthropic has started marking Claude's output as AI-generated. The reason it matters has less to do with Claude than with where content provenance is heading for everyone building generative tools.

  3. Running Sound and Full AV for Gayatri Havan

    Behind the scenes of handling live sound and coordinating the full audiovisual operation for Gayatri Havan with a trusted team.

All of Nimalthas Insights

Résumé

Everything above, on one page.

View résuméDownload PDF résumé