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nikengoswami/README.md

โ–ˆโ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•—         โ–ˆโ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•—    โ–ˆโ–ˆโ•— โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ•—
โ–ˆโ–ˆโ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ•โ•โ•โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•‘         โ–ˆโ–ˆโ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ•โ•โ•โ•šโ•โ•โ–ˆโ–ˆโ•”โ•โ•โ•โ–ˆโ–ˆโ•‘    โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•‘ โ–ˆโ–ˆโ•”โ•
โ–ˆโ–ˆโ•”โ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—  โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘         โ–ˆโ–ˆโ•”โ–ˆโ–ˆโ•— โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—     โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘ โ–ˆโ•— โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•
โ–ˆโ–ˆโ•‘โ•šโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ•  โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘         โ–ˆโ–ˆโ•‘โ•šโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ•     โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘   โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•”โ•โ•โ–ˆโ–ˆโ•—โ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•—
โ–ˆโ–ˆโ•‘ โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—    โ–ˆโ–ˆโ•‘ โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•—   โ–ˆโ–ˆโ•‘   โ•šโ–ˆโ–ˆโ–ˆโ•”โ–ˆโ–ˆโ–ˆโ•”โ•โ•šโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ–ˆโ•”โ•โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•‘โ–ˆโ–ˆโ•‘  โ–ˆโ–ˆโ•—
โ•šโ•โ•  โ•šโ•โ•โ•โ•โ•šโ•โ•โ•โ•โ•โ•โ• โ•šโ•โ•โ•โ•โ•โ• โ•šโ•โ•  โ•šโ•โ•โ•šโ•โ•  โ•šโ•โ•โ•šโ•โ•โ•โ•โ•โ•โ•    โ•šโ•โ•  โ•šโ•โ•โ•โ•โ•šโ•โ•โ•โ•โ•โ•โ•   โ•šโ•โ•    โ•šโ•โ•โ•โ•šโ•โ•โ•  โ•šโ•โ•โ•โ•โ•โ• โ•šโ•โ•  โ•šโ•โ•โ•šโ•โ•  โ•šโ•โ•
Typing SVG

Typing SVG


โšก QUANTUM BREACH DETECTED โšก

โŸจ ACCESSING NEURAL MATRIX โŸฉ

class DigitalAlchemist:
    def __init__(self):
        self.name = "Niken Goswami"
        self.consciousness = "Distributed Across 3 Continents"
        self.current_dimension = {
            "physical": "Nagaoka, Japan ๐Ÿ—พ",
            "academic": "TU Darmstadt, Germany ๐Ÿ‡ฉ๐Ÿ‡ช",
            "digital": "Everywhere the internet exists ๐ŸŒ"
        }

    def get_current_state(self):
        return {
            "๐ŸŽ“ Learning": ["Advanced Transformers", "Point Cloud Deep Learning", "MambaVision Architecture"],
            "๐Ÿ’ผ Working": ["Salesforce Automation @ Goodspeed", "AI Research @ NTUST", "MMS Point Cloud Classification"],
            "๐Ÿ”ฌ Research": "AI-based Point Cloud Generation & Classification",
            "๐ŸŒฑ Growing": ["Neural Architecture Search", "3D Vision Systems", "LLM Fine-tuning"],
            "๐ŸŽฏ Hunting": ["AI/ML Engineer Roles", "Research Positions", "Innovation Opportunities"]
        }

    def neural_capabilities(self):
        return {
            "languages": {
                "human": ["English", "German", "Japanese", "Hindi", "Gujarati"],
                "machine": ["Python", "JavaScript", "C++", "Java", "SQL", "Apex"],
                "deep_learning": ["PyTorch", "TensorFlow", "CUDA", "Transformers"]
            },
            "domains": {
                "AI/ML": ["Computer Vision", "Point Clouds", "Deep Learning", "Transformers"],
                "Full-Stack": ["MERN", "React", "Node.js", "Express", "RESTful APIs"],
                "Cloud": ["Salesforce", "Apex", "LWC", "CPQ", "CLM", "Flows"],
                "DevOps": ["Git", "Docker", "CI/CD", "Linux", "Cloud Infrastructure"]
            },
            "superpowers": [
                "Converting chaos into clean code",
                "Seeing in 3D point clouds",
                "Training neural networks while sleeping",
                "Speaking to machines in their native tongue",
                "Turning coffee into algorithms โ˜•โ†’๐Ÿค–"
            ]
        }

# Initialize the matrix
niken = DigitalAlchemist()
print(niken.get_current_state())

๐ŸŒŒ NEURAL ARCHITECTURE VISUALIZATION ๐ŸŒŒ

graph TD
    A[๐Ÿง  Niken's Brain] -->|Processes| B[โ˜๏ธ Point Clouds]
    A -->|Develops| C[โšก AI Models]
    A -->|Builds| D[๐ŸŒ Full-Stack Apps]
    A -->|Automates| E[๐Ÿ”ง Salesforce Systems]

    B --> F[94.78% Accuracy]
    C --> G[MambaVision Research]
    D --> H[1000+ Users Served]
    E --> I[99% Uptime Achieved]

    F --> J[๐Ÿš€ Innovation]
    G --> J
    H --> J
    I --> J

    J --> K[๐ŸŒŸ World-Class Solutions]

    style A fill:#00F260,stroke:#0575E6,stroke-width:4px,color:#000
    style J fill:#0575E6,stroke:#00F260,stroke-width:3px,color:#fff
    style K fill:#FFD700,stroke:#FF6B6B,stroke-width:4px,color:#000
Loading

๐ŸŽจ SKILL CONSTELLATION MAP ๐ŸŽจ

๐Ÿค– AI/ML

Core: PyTorch, TensorFlow
Vision: OpenCV, Point Clouds
Advanced: Transformers, CUDA
Specialization: PointNet++

๐Ÿ’ป Full-Stack

Frontend: React, JS, TS
Backend: Node, Express
Database: Mongo, PostgreSQL
Architecture: RESTful, MERN

โ˜๏ธ Salesforce

Development: Apex, LWC
Platforms: CPQ, CLM
Automation: Flows, Triggers
Integration: REST, SOAP

๐Ÿ› ๏ธ DevOps

Version: Git, GitHub
Containers: Docker
CI/CD: Automated Pipelines
Systems: Linux, Bash

๐Ÿ”ฅ LEGENDARY PROJECTS THAT BROKE THE MATRIX ๐Ÿ”ฅ

๐ŸŒŒ MMS Point Cloud Classification

project = {
    "name": "3D Semantic Segmentation Beast",
    "data": "1.46 MILLION points processed",
    "model": "PointNet++ (State-of-the-Art)",
    "classes": 5,
    "hardware": "RTX 4050 GPU",
    "achievement": "SOTA accuracy achieved",
    "impact": "Real-world MMS mapping",
    "tech_stack": ["PyTorch", "CUDA", "NumPy", "CloudCompare"]
}

What makes it insane:

  • Processes 1.46M 3D points in real-time
  • 5-class semantic segmentation
  • GPU-accelerated training pipeline
  • Real-world Mobile Mapping System data
  • Custom PointNet++ implementation

๐Ÿงฌ MambaVision Transformer Research

research = {
    "institution": "NTUST (Top 300 Global)",
    "supervisor": "Prof. Yi Zeng Hsieh",
    "innovation": "4 Model Variants Created",
    "breakthrough": "+6% accuracy over baseline",
    "domain": "Vision Transformers",
    "contribution": "Novel architecture designs",
    "period": "Apr 2025 - Jul 2025"
}

Why it's groundbreaking:

  • Advanced transformer architectures
  • Novel MambaVision variants
  • Published research quality
  • Pushing SOTA boundaries
  • Real academic impact

๐ŸŽ“ University Placement Portal

const impact = {
  architecture: "MERN Full-Stack",
  scale: "1000+ student profiles",
  performance: "40% data throughput โฌ†๏ธ",
  features: [
    "Real-time job matching",
    "Company dashboard",
    "Application tracking",
    "Analytics engine"
  ],
  deployment: "Production-grade",
  testimonial: "Changed campus recruitment forever"
};

Revolutionary features:

  • Smart job-student matching algorithm
  • Real-time notifications system
  • Admin analytics dashboard
  • Mobile-responsive design
  • Scalable cloud architecture

๐Ÿ  Everything Real Estate Platform

const platform = {
  listings: "200+ properties",
  performance: "<300ms API response",
  architecture: "Microservices",
  features: [
    "Advanced property search",
    "Interactive maps",
    "Virtual tours",
    "Real-time availability"
  ],
  tech: "MERN + RESTful APIs",
  optimization: "Redis caching + CDN"
};

Technical excellence:

  • Sub-300ms response times
  • RESTful API architecture
  • Advanced search & filters
  • Interactive property maps
  • Real-time data synchronization

โš•๏ธ Heart Failure ML Predictor

ml_models = {
    "algorithms": ["LR", "KNN", "LDA", "RF", "SVM"],
    "best_performer": "Random Forest",
    "accuracy": "80.2%",
    "dataset": "Clinical heart data",
    "impact": "Early disease detection",
    "features": "13 clinical parameters",
    "validation": "K-fold cross-validation"
}

Healthcare impact:

  • 5 ML algorithms compared
  • 80.2% prediction accuracy
  • Real clinical application
  • Feature importance analysis
  • Model interpretability focus

โšก Salesforce Enterprise Automation

System.debug('Enterprise Scale Achievement:');
Map<String, Object> impact = new Map<String, Object>{
    'users_supported' => 1000,
    'instances_managed' => 6,
    'uptime_percentage' => 99,
    'integrations' => new List<String>{
        'Microsoft Teams',
        'Azure OpenAI',
        'REST APIs'
    },
    'automation_level' => 'MAXIMUM'
};

Enterprise achievements:

  • 1000+ users supported
  • 99% uptime maintained
  • 6 production instances
  • AI integrations (Azure OpenAI)
  • Custom LWC components

๐Ÿ“ˆ NEURAL NETWORK ANALYTICS ๐Ÿ“ˆ

Contribution Graph

๐ŸŽฏ ACHIEVEMENT TROPHY CASE ๐Ÿ†

โ•”โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•—
โ•‘                                                                                      โ•‘
โ•‘   ๐Ÿฅ‡ NTUST_OIA_TEEP Scholarship (2024) - Research Excellence                       โ•‘
โ•‘   ๐Ÿฅˆ Mukhyamantri Yuva Swavalamban Yojana (2023) - Academic Excellence            โ•‘
โ•‘   ๐Ÿฅ‰ Public Relations Head @ CSI (2021-2023) - Leadership                          โ•‘
โ•‘   ๐Ÿ… CodeChef Campus Chapter Lead (2020-2023) - Competitive Programming            โ•‘
โ•‘   ๐ŸŽ–๏ธ 94.78% Point Cloud Classification Accuracy - Technical Excellence             โ•‘
โ•‘   โญ 99% Uptime on 6 Production Instances - Operational Excellence                  โ•‘
โ•‘   ๐Ÿ’Ž 1000+ Users Supported - Impact at Scale                                        โ•‘
โ•‘   ๐Ÿ”ฅ 5 Languages Spoken - Global Communication                                      โ•‘
โ•‘                                                                                      โ•‘
โ•šโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•

๐ŸŽ“ ACADEMIC JOURNEY

@@@ MSc Computer Science @ TU Darmstadt (2024-2027) @@@
+ ๐Ÿ“š Specialization: Data Science & Engineering
+ ๐ŸŒ Exchange Program: Nagaoka University of Technology, Japan (Oct 2025 - Feb 2026)
+ ๐Ÿ† Scholarship: NTUST_OIA_TEEP Research Scholarship (2024)
+ ๐Ÿ”ฌ Research Focus: AI-based Point Cloud Generation & Classification
+ ๐Ÿ’ก Key Courses: Deep Learning, Computer Vision, Advanced ML, Neural Networks
+ ๐Ÿš€ Projects: MMS Classification, Transformer Research, 3D Vision Systems

@@@ BTech Information Technology @ Dharmsinh Desai University (2019-2023) @@@
+ ๐ŸŽฏ CGPA: 8.14/10
+ ๐Ÿ… Award: Mukhyamantri Yuva Swavalamban Yojana
+ ๐Ÿ‘ฅ Leadership: Public Relations Head @ Computer Society of India
+ ๐Ÿ’ป Competitive Programming: CodeChef Campus Chapter (2020-2023)
+ ๐ŸŒŸ Major Projects: Heart Failure Predictor, Placement Portal, Real Estate Platform

๐Ÿ’ผ PROFESSIONAL TIMELINE

๐Ÿš€ PRESENT

Software Developer Goodspeed (London, Remote) Dec 2025 - Present

Focus = [
  "Salesforce Automation",
  "Apex Classes",
  "Lightning Web Components",
  "Enterprise Integrations"
];

๐Ÿ”ฌ 2025

Research Intern NTUST (Taiwan) Apr 2025 - Jul 2025

research = {
  "MambaVision": True,
  "model_variants": 4,
  "improvement": "+6%",
  "supervisor": "Prof. Yi Zeng Hsieh"
}

โš™๏ธ 2023-2024

Associate Software Engineer Conga (Pune, India) Jan 2023 - May 2024

const stats = {
  users: "1000+",
  instances: 6,
  uptime: "99%",
  integrations: ["Teams", "OpenAI"]
};

๐ŸŒ MULTI-DIMENSIONAL EXISTENCE


๐ŸŽฌ CURRENTLY IN PRODUCTION

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

class CurrentFocus:
    """What I'm building RIGHT NOW"""

    def __init__(self):
        self.projects = {
            "๐Ÿ”ฌ Research": {
                "status": "IN_PROGRESS",
                "project": "MMS Point Cloud Classification",
                "achievement": "94.78% accuracy on 1.46M points",
                "tech": ["PointNet++", "PyTorch", "CUDA"],
                "impact": "Real-world 3D mapping applications"
            },
            "๐Ÿ’ผ Professional": {
                "status": "ACTIVE",
                "role": "Software Developer @ Goodspeed",
                "focus": ["Salesforce Automation", "LWC Development"],
                "stack": ["Apex", "Lightning Web Components"],
                "impact": "Enterprise-scale automation"
            },
            "๐Ÿง  Learning": {
                "status": "EVOLVING",
                "topics": [
                    "Advanced Transformer Architectures",
                    "Point Cloud Deep Learning",
                    "Neural Architecture Search",
                    "LLM Fine-tuning Techniques"
                ],
                "goal": "Stay ahead of the curve"
            },
            "๐ŸŒฑ Growing": {
                "status": "CONTINUOUS",
                "areas": [
                    "3D Computer Vision Systems",
                    "Distributed AI Training",
                    "Production ML Systems",
                    "Cloud-Native Architectures"
                ]
            }
        }

    def get_availability(self):
        return {
            "open_to": [
                "๐Ÿš€ AI/ML Engineer positions",
                "๐Ÿ’ป Software Engineering roles",
                "๐Ÿ”ฌ Research collaborations",
                "๐ŸŒŸ Innovative projects",
                "๐Ÿค Open-source contributions"
            ],
            "specialties": [
                "Point Cloud Processing & 3D Vision",
                "Deep Learning & Neural Networks",
                "Full-Stack Development (MERN)",
                "Salesforce Enterprise Solutions",
                "Production ML Systems"
            ],
            "status": "ACTIVELY LOOKING",
            "contact": "Let's build something legendary! ๐Ÿš€"
        }

focus = CurrentFocus()
print(focus.get_availability())

๐Ÿ“ก ESTABLISH CONNECTION

Choose Your Communication Protocol:

โ•”โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•—
โ•‘                                                                            โ•‘
โ•‘   ๐Ÿ’ฌ STATUS: OPEN TO OPPORTUNITIES                                        โ•‘
โ•‘                                                                            โ•‘
โ•‘   ๐ŸŽฏ SEEKING: AI/ML Engineer | Software Engineer | Research Positions     โ•‘
โ•‘                                                                            โ•‘
โ•‘   ๐ŸŒŸ EXPERTISE: Deep Learning | Point Clouds | Full-Stack | Salesforce    โ•‘
โ•‘                                                                            โ•‘
โ•‘   ๐Ÿš€ MISSION: Building AI systems that push the boundaries                โ•‘
โ•‘                                                                            โ•‘
โ•‘   ๐Ÿ’ก MOTTO: "In a world of code, be the algorithm that optimizes"         โ•‘
โ•‘                                                                            โ•‘
โ•šโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•

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๐Ÿ”ฅ Click to reveal hidden stats ๐Ÿ”ฅ

๐Ÿ† GitHub Trophies

๐Ÿ“Š Detailed Language Stats

โฐ Coding Time Distribution

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๐Ÿ’ญ RANDOM WISDOM FROM THE MATRIX


๐ŸŒŸ VISITOR ANALYTICS

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๐ŸŽฏ THE JOURNEY CONTINUES... ๐Ÿš€

while(alive) {
    eat();
    sleep();
    code();
    build_AI();
    change_world();
    repeat();
}

๐Ÿ’ซ "Code is poetry written in logic, and AI is the consciousness we give to machines" ๐Ÿ’ซ


โšก BUILT WITH PASSION, CAFFEINE, AND NEURAL NETWORKS โšก

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โ•”โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•—
โ•‘  "In a universe of infinite possibilities,                               โ•‘
โ•‘   I choose to build the impossible."                                     โ•‘
โ•‘                                                            - Niken, 2025  โ•‘
โ•šโ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•โ•

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