Help & Supportcareers@gravityer.com
Hi! I am CS undergrad exploring systems, machine learning, and human thinking.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
artifact-to-pwa
June 3, 2026 – Present
Convert any Claude artifact (HTML/React/JSX) or URL into an installable PWA — zero build step, auto-migrates localStorage to IndexedDB
View Projectserverless-comm
February 17, 2026 – Present
PeerSpace is a decentralized collaboration workspace leveraging WebRTC for secure, serverless peer-to-peer video, chat, and file sharing. It integrates browser-based local AI via Web Workers to provide real-time audio transcription and automated meeting summarization.
View Projectadam
February 17, 2025 – May 30, 2025
A CLI tool that executes commands using voice recognition, enabling hands-free terminal interaction.
View Projectmedia-ears-web3
February 17, 2025 – July 2, 2025
🤖 ML-powered emotion detection + recommendation engine. Flask web app suggesting media based on real-time sentiment analysis.
View Projectdyslexia-accessibility-nlp
August 21, 2024 – Present
A multi-model ML pipeline that detects dyslexia indicators from handwriting images by combining a letter classifier, a CNN reversal detector, and an LSTM sequence analyser into a weighted ensemble. Built as a research capstone exploring how deep learning can assist early screening in under-resourced educational settings.
View Projectmy_ostep_projects
February 11, 2024 – May 14, 2024
This repo implements core OS utilities (wcat, wgrep, wzip, wunzip), a line-reversing tool, and key OS algorithms: CPU scheduling (FCFS, SJF, SRTF, RR, priority, lottery, stride), free-space management (best/first/next/worst fit), and paging (address translation + page replacement: FIFO, OPR, LFU, MFU, LRU, MRU).
View Projectml_algos
October 19, 2023 – May 27, 2024
This repo implements core ML algorithms: Decision Trees, Discriminative Linear Models (DLMs), Generalized Linear Models (GLMs), SVMs, Neural Networks (MLP), plus Unsupervised Learning (clustering, anomaly detection, recommendation systems) and Reinforcement Learning.
View ProjectCultural Fit Analysis
The candidate exhibits a strong inclination towards personal projects, demonstrating initiative and a passion for technology. The projects span various domains, from operating systems to web development and machine learning, indicating a broad technical curiosity. The focus on AI/ML projects aligns well with a Data Scientist role, suggesting a genuine interest in the field. However, the lack of team-based or collaborative project descriptions makes it difficult to assess their fit within a team-oriented professional environment. The 'dyslexia-accessibility-nlp' project shows potential for impact-driven work, which could be a positive cultural fit for organizations valuing social responsibility.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-directed learning approach, tackling complex technical challenges independently. The 'serverless-comm' project suggests an interest in innovative solutions and potentially good problem-solving skills. However, without formal assessment data (English Test, Psychometric Test) or interview interactions, it is difficult to fully assess communication clarity, teamwork, or stress handling. The breadth of personal projects suggests curiosity and a drive to explore diverse technical areas.