[ Projects Motherboard ]
# Hover over nodes to explore projects • Scroll to navigate
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Engineering Domains
Core expertise areas spanning hardware, software, and intelligent systems
Robotics Systems
Autonomous robots and intelligent control systems
Embedded Engineering
ESP32 • Arduino • Sensors • Microcontrollers
Machine Learning
Real-world AI applications and data analytics
IoT Systems
Environmental monitoring and smart automation
The Engineer Behind the Machines
Jenish is an enthusiastic engineering student who transforms ideas into intelligent systems. With a passion for robotics, embedded systems, and machine learning, he combines hardware and software expertise to create practical, innovative solutions.
Each project represents a commitment to engineering excellence and continuous learning in the rapidly evolving fields of robotics, automation, and intelligent systems. His approach blends meticulous engineering principles with creative problem-solving.
< Skills Dashboard >
# Core competencies across robotics, embedded systems, and intelligent systems
→ Embedded Systems
→ Programming
→ AI & Data
→ Mechanics & Robotics
→ Web & Frontend
→ Tools & Platforms
[ Projects Lab ]
# A collection of robotics projects blending engineering excellence with innovation
Fire Fighting Robot
Detects flames and extinguishes them automatically
Gesture Controlled Mecanum Wheel Car
Robot car controlled using hand gestures with ESP32 and MPU6050 motion sensor
Line Following Pesticide Spraying Robot
Agricultural robot that follows a line path using IR sensors and sprays pesticide automatically
Environmental Monitoring System
IoT system using ESP32 with MQ gas sensors, BMP280 pressure sensor, and GPS
Health Monitoring System
System using MAX30100 pulse oximeter sensor to measure heart rate and blood oxygen
$ Each project demonstrates integration of hardware, software, and intelligent systems
> View details on projects above or check GitHub repositories
[ Research & Academic ]
# Advanced research in machine learning and signal processing
Audio Transcription of Customer Support Calls
$ Using Machine Learning Algorithms
Manual analysis of customer support call recordings is time-consuming and resource-intensive. Organizations struggle to extract insights from conversations at scale.
Implementing automatic speech-to-text transcription using advanced machine learning algorithms. The system processes audio data and converts it into actionable text, enabling automated analysis of customer interactions.
This research enables efficient quality assurance, sentiment analysis, and pattern recognition in customer support calls. Businesses can now identify trends, improve training, and enhance overall customer experience systematically.
< Achievements >
# Milestones and recognitions in engineering and innovation
Quiz Competition Participant
Participated in technical quiz competitions showcasing knowledge in engineering and robotics
Arts & Literature Interest
Active participant in art, literature, and cultural appreciation activities
Business & Economics Knowledge
Knowledge in business concepts, economics, and entrepreneurship
Sports & General Knowledge
Keen interest in sports, current affairs, and general knowledge domains
IOST Entrance Exam
Participated in the IOST entrance examination for BSc CSIT under Tribhuvan University
Multiple Robotics Projects
Successfully designed and implemented 5+ advanced robotics and embedded systems projects
[ Contact Terminal ]
# Reach out to discuss robotics, engineering projects, or collaborations
$ connect jenish
jenish@example.com
GitHub
github.com/jenish
linkedin.com/in/jenish
Location
Ready for remote work
> Thank you for exploring Jenish Lab
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