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ARMAN

ARMAN अरमान 阿尔曼 ارمان アルマン
"The mind is not a mystery to be feared — but a system to be mapped." — Arman
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ABOUT

I’m Arman, a B.Tech IT student working at the intersection of artificial intelligence and brain-computer interfaces. I build systems that translate human signals into real-world interaction, focusing on practical applications like emotion-based control and assistive technologies.

01

SYSTEM

Architecture of self

MODULE_01

Cognition

Systems thinking at every layer of decision-making. Pattern recognition over intuition. Logic over impulse.

MODULE_02

Discipline

Consistency as infrastructure. Habits as compiled subroutines. Routines as deployed systems.

MODULE_03

Architecture

Building structures — mental, technical, creative — that hold weight under pressure and scale with intent.

MODULE_04

Clarity

Noise reduction as a core skill. The signal matters; everything else is entropy to be filtered.

MODULE_05

Execution

Ideas without output are theoretical. Shipping is a discipline. Completion is the only benchmark that matters.

MODULE_06

Growth

Not linear. Not guaranteed. Recursive — each iteration rewrites the base layer, sharpens the edge.

02

SYSTEM ARCHITECTURE

Technical profile

ROLE
B.Tech in Information Technology
FOCUS
  • Artificial Intelligence
  • Brain-Computer Interfaces
  • Human-Computer Interaction
SKILLS
Logic
Python C++ Java C Java Script
Systems
Machine Learning EEG Signal Processing
Architecture
Next.js Streamlit Git
03

THE ARCHIVE

Selected work

BCI System Visualization
VOLUME 01
BCI EEG NEUROTECH

Emotion-Aware BCI System

Description

An EEG-based brain-computer interface that classifies emotional states using machine learning models and maps them into real-time outputs such as music control. Currently working on extending the system for prosthetic arm interaction using hardware integration.

Technologies

Python, OpenBCI, MNE, SVM, Random Forest, KNN

Work Done

- Processed EEG signals for emotion classification - Implemented ML models for prediction - Built a basic real-time response system

Status

Working Prototype

Models SVM, Random Forest, KNN
Output Real-time music control and Prosthetic arm
Status Working Prototype
GitHub Demo [TBD]
2025 SYSTEM_ACTIVE
Multimodal AI Dashboard
VOLUME 02
AI RESEARCH INTERN

AI Research Intern

Description

Worked on multimodal AI systems focused on generating code from text and images. Explored pipelines for converting design inputs into structured frontend components and logic.

Technologies

Python, PyTorch, HuggingFace, PIL

Work Done

- Built basic pipelines for text-to-code generation - Experimented with image-to-code concepts - Contributed to internal development tasks

Note

Project details are limited due to internal work.

Focus AI Research Intern
Work Text-to-code, Image-to-code
Access Internal Project
GitHub Internal Only
2025 COMPLETED
04

THE OBSERVATORY

Beyond the screen

DESIGNATION Citizen Scientist
DOMAIN Asteroid Detection
NETWORK Minor Planet Center

Beyond systems and code, the work extends into the unknown.

Actively participating in asteroid detection programs — scanning vast datasets, identifying anomalies, contributing to planetary-scale observation.

Patterns are universal. Whether in neural signals or distant objects — the task remains: detect, interpret, act.

FIELD // PLANETARY DEFENSE · PATTERN ANALYSIS
05

the link

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