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In Summary, I am...

academically astute.

Masters Degree 3.93/4
umd Human Computer Interaction University of Maryland
๐Ÿ‡บ๐Ÿ‡ธ College Park Aug 2021 โ†’ May 2023

Details

Grade 3.925 of 4 GPA Awards
  • Goldhaber Travel Award
  • Skills
  • UX Design
  • UX Research
  • Data Visualization
  • Bachelor of Technology Degree 3.82/4
    srm Computer Science and Engineering SRM Institute of Science and Technology
    ๐Ÿ‡ฎ๐Ÿ‡ณ Kattankulathur Aug 2016 โ†’ May 2020

    Details

    Grade 9.55 of 10 GPA Honors
  • First class with Distinction
  • Awards
  • Special Merit Scholarship
  • Outstanding Technical Presentation
  • Skills
  • Data Science
  • Machine Learning
  • Software Development
  • Lectures
  • Linked Lists
  • Semantic Web
  • Subnetting Networks
  • Deterministic Finite Automata
  • research oriented.

    ๐Ÿ“„ Research Papers

    Masters Thesis Sep 2022 โ†’ Apr 2023 AnalogiLead: Improving Selection of Analogical Inspirations with Chunking and Recombination Creativity and Cognition Conference 2023
    Joel Chan
    Joel Chan Advisor
    Niklas Elmqvist
    Niklas Elmqvist Committee Member
    Susannah Paletz
    Susannah Paletz Committee Member
    To address this problem of identifying relevant analogical leads and prevent premature rejection or design fixation, this system proposes unique approach by incorporating the cognitive mechanisms of chunking and recombination as a medium of interaction for selecting beneficial analogies.
    Computational Analogy Large Language Models Quantitative Analysis Within Subjects Study OpenAI React Next.js Firebase
    iSchool Advising Redesign Graphic

    Abstract

    In this thesis, A novel computational support system for analogical innovation is proposed that employs the cognitive mechanisms for chunking and recombination as mediums of interaction. Chunking involves identifying and extracting meaningful chunks or segments from a design problem into interactive tiles called magnets, while recombination involves combining these magnets to generate insightful questions that elicit divergent thinking.

    To evaluate the effectiveness of the system, a within-subjects study involving 23 participants was conducted, comparing the proposed interface with a baseline. The study found that using chunking and recombination as interactive mechanisms helped prevent premature rejection of useful analogical leads, resulting in 4 times fewer ignored analogical leads. Participants were also found to make 12 times fewer changes to their decisions, given a minor increment in processing time in the order of 1.5 minutes.

    Overall, these results suggested that our proposed intervention is an effective tool for facilitating the selection of beneficial analogies, fostering analogical innovation through computational support.
    Fluid Transformers and Creative Analogies: Exploring Large Language Modelsโ€™ Capacity for Augmenting Cross-Domain Analogical Creativity
    Zijian Ding, Arvind Srinivasan, Stephen MacNeil, and Joel Chan. 2023.
    https://doi.org/10.48550/arXiv.2302.12832

    Objective

    Cross-domain analogical reasoning, a challenging creative ability, has received limited systematic exploration in the context of Large Language Models (LLMs). This paper investigates LLMs' potential to augment cross-domain analogical reasoning.

    Contribution

    Performed rigorous Qualitative coding for 200+ analogies to understand and make sense of the reformulation behaviours amongst participants, keeping track of what details were added or changed to the understanding of the design problem.

    Frequent analogical reformulations, primarily adding information, positively correlated with helpfulness ratings. This suggests that LLMs can augment cross-domain analogical reasoning by generating analogical reformulations that are helpful to humans.

    ๐Ÿ“ฝ๏ธ Research Presentations

    Poster Presentation Jan 2022 โ†’ Oct 2022 Hotshots: Tennis Visualization System IEEE Vis Conference 2022
    Niklas Elmqvist
    Niklas Elmqvist Advisor
    Abhinav Kannan Collaborator
    Designed and developed the interactive prototype of a tennis court representation that enables its users to gain deeper insights about player behavior.
    Data Visualization Svelte D3.js Interactive Prototyping
    iSchool Advising Redesign Graphic

    Early Explorations

    Prior to arriving at the current iteration of the stick-and-ball representation, ideated and tested different ways tennis data can be represented.

    hotshots chord courts hotshots parallel coordinates hotshots 3d radar charts

    These representations also resulted in an early prototype that allowed for a matrix-like interactions

    iSchool Advising Redesign Graphic
    However, complex shot-by-shot analysis was difficult, hence, we explored a variation of our first approach of creating chord courts.
    UX Research Sep 2021 โ†’ Dec 2021 Redesiging iSchool Advising Workflow College of Information Studies Ron Padron
    Ron Padron Client
    Using Contextual Design Methods, gathered data and insights to come up with feasible, innovative solutions to improve the experience of advising for both the advising team and the students.
    Contextual Inquiry Interviewing Survey Design Affinity Mapping Identity Modelling
    iSchool Advising Redesign Graphic

    About the Client

    The significant growth of University of Maryland's School of Information Science, has prompted the undergraduate iSchool advising committee to address the challenges and explore ways to enhance the advising process as they anticipate the addition of three more undergraduate programs.

    Discovering the Disconnect

    Following several hours of Affinity mapping, I built an identity model with the goal of finding crucial insights into the tensions that affected the iSchool advising workflow.

    iSchool Advising Identity Model Graphic
    Through identity modelling, I uncovered that there was a mismatch between student and advisors' expectations.

    startup tested.

    ๐Ÿง‘๐Ÿปโ€๐Ÿ’ป Industrial Internships

    UX Intern ๐Ÿ‡บ๐Ÿ‡ธ Remote
    Tetrate Viewer An interface for Service Mesh Troubleshooting Tetrate
    Tetrate Milipitas, California
    Built an Interface for the API developed by the Silicon Valley Startup for Viewing the Service Mesh of an Organisation from multiple perspectives.
    Data Visualization Model Driven Development Data Driven Application Git Version Control React D3.js
    Tetrate TCC Viewer

    The Idea

    Given the dynamic nature of a typical API surface, with every new addition, a page might need to be added, each with its own composition before being built.

    This prototype instead defines a interface schema over the existing API surface to create a dynamic build-time code generator that automagically adds pages as the APIs change. The following are some screenshots.

    Tetrate TCC Viewer Tetrate TCC Viewer Tetrate TCC Viewer Tetrate
    Design Developer Intern ๐Ÿ‡ฎ๐Ÿ‡ณ Chennai
    GetMe Hub Local-first Application to facilitate Conversational Ordering of Groceries cuedin technologies
    Cuedin Technologies Chennai, India
    Built an Interface for the API developed by the Silicon Valley Startup for Viewing the Service Mesh of an Organisation from multiple perspectives.
    Experience Design Graphic Design Hybrid App Development Ionic
    Tetrate TCC Viewer

    Building to Empower

    Cuedin Technologies

    As an undergraduate, I worked on various projects during this role. I designed the logo and branding assets for a software called "GetMe Hub" and provided input to improve the application interface design for a user-friendly shopping experience. Additionally, I created marketing assets like flyers, pitch decks, and social media posts. Furthermore, I built a responsive, API-driven dashboard single-page application (SPA) to display usage metrics.

    GetMe Hub's ambitious initiative of empowering small vendors to have an online presence, struck a chord with me.

    ๐ŸŽ’ Academic Internships

    Academic Intern ๐Ÿ‡ธ๐Ÿ‡ฌ Singapore
    cuedin technologies Big Data and Artificial Neural Networks National University of Singapore
    Big Data Artificial Neural Networks Data Analysis Natural Language Processing Deep Learning Python
    Applied the fundamentals of Artificial Neural Networks learned during the Internship in a Private Kaggle Competition on Sentiment Analysis of Twitter Tweets organized by the professors and led my team of diverse backgrounds to the top five in the leaderboards.
    Academic Intern ๐Ÿ‡ธ๐Ÿ‡ฌ Singapore
    cuedin technologies Big Data and Hadoop Administration Hewlett Packard Enterprise
    Big Data Data Analysis Distributed Computing Hadoop Spark Scala Linode Hive
    Learned to apply the fundamentals of Big Data and Hadoop by setting up multi-node virtual machine-based clusters on Cloud. Gained hands-on experience by solving various problems ranging from Data Mining to Recommendation Systems using technologies such as Hadoop, Hive, and Spark using Scala.

    community driven.

    ๐Ÿ”ฅ Personal Projects

    2022 โญ๏ธ 12
    cuedin technologies Matercolor ๐Ÿ“ฆ 77K downloads โ€ข โค๏ธ 57 likes
    A tiny, zero-dependency libary for building harmonious material palettes for any color. Also created a supporting plugin to use with Figma.
    Material Design Figma Typescript Ava Test Runner
    Matercolor Github
    2022 โญ๏ธ 4
    cuedin technologies Chromanomer ๐Ÿ“ฆ 369 downloads
    A perceptually intuitive color naming system based on the HSLuv color space that covers a sizeable spectrum of colors while boasting a negligible learning curve.
    Design Systems Color Nomenclature Perceptually Uniform Color Space Accessibility Sass Node.js
    Chromanomer Github

    ๐Ÿ’ก Notable Contributions

    Maintainer โญ๏ธ 41.4K
    React Typescript Cheatsheets Cheatsheets for experienced React developers getting started with TypeScript
    TypeScript Documentation Automation Github Actions
    Contributor โญ๏ธ 26.4K
    SpaCy Industrial-strength Natural Language Processing (NLP) in Python
    Natural Language Processing Python Language Training

    tech curious.

    The following are all things technology currently on my radar, categorised by exploration status and sorted by confidence in working with them.

    ๐Ÿณ Techniques

    These are some Paradigms and Workflows of Software Design and Development I'm familiar with or curious to adopt.
    ๐Ÿ‘† Tap the card for more

    ๐Ÿณ Techniques

    These are some Paradigms and Workflows of Software Design and Development I ๐Ÿงญ explore and ๐Ÿ”ฌ experiment to become an ๐Ÿ… expert in them.
  • Model Driven Development
  • Event Driven Architecture
  • Data Driven Applications
  • Experience Driven Development โœจ
  • Backend as a Service
  • Continuous Integration + Deployment
  • Functional Programming
  • Microservices Architecture โœจ
  • Backend For Frontend
  • Data Flow Programming โœจ
  • Prompt Driven Development โœจ
  • ๐Ÿงฐ Tools

    These are some tools I'm familiar with or curious to adopt.

    ๐Ÿ‘† Tap the card for more

    ๐Ÿงฐ Tools

    These are some tools I ๐Ÿงญ explore and ๐Ÿ”ฌ experiment to become an ๐Ÿ… expert in them.
  • Git Version Control
  • Node Package Manager
  • Yarn Package Manager
  • Visual Studio Code
  • Github Actions
  • Ava Test Runner
  • Vite
  • PostCSS
  • Feathers โœจ
  • XCode
  • Gulp
  • zx โœจ
  • Hygen โœจ
  • Esbuild โœจ
  • ๐Ÿš€ Platforms

    These are some platforms I'm familiar with or curious to adopt.
    ๐Ÿ‘† Tap the card for more

    ๐Ÿš€ Platforms

    These are some platforms I ๐Ÿงญ explore and ๐Ÿ”ฌ experiment to become an ๐Ÿ… expert in them.
  • MongoDB
  • Firebase
  • Vercel
  • OpenAI
  • Docker
  • HuggingFace
  • Elasticsearch
  • Google App Engine
  • Google Cloud Run
  • Amazon Serverless
  • Kubernetes
  • LiveBlocks โœจ
  • Ionic โœจ
  • Flutter โœจ
  • AWS Amplify โœจ
  • Amazon SageMaker โœจ
  • Google Maker Suite โœจ
  • ๐Ÿ’ป Languages and Frameworks

    These are some frameworks I'm familiar with or curious to adopt.
    ๐Ÿ‘† Tap the card for more

    ๐Ÿ’ป Languages and Frameworks

    These are some frameworks I ๐Ÿงญ explore and ๐Ÿ”ฌ experiment to become an ๐Ÿ… expert in them.
  • Pythonlanguage
  • Javascriptlanguage
  • Typescriptlanguage
  • Reactlibrary
  • Next.jsmeta framework
  • Express.jsframework
  • 11ty.jsframework
  • D3.jslibrary
  • Golanglanguage
  • Reduxlibrary
  • Svelteframework
  • Feathers.jsmeta framework
  • Webstrates.js โœจframework
  • Three.js โœจlibrary
  • Aframe โœจframework
  • WebXR โœจframework
  • Swift โœจframework
  • Angularframework
  • Astro.js โœจframework
  • Solid.js โœจframework
  • Xstate.js โœจframework
  • Rust โœจlanguage