FIELD NOTEBOOK · VOL. 01
SUDHANSHU VERMA 

A field notebook on multidisciplinary systems.

Building things
that notice.

A working record of experiments at the intersection of embedded systems, web development, and machine learning.

turn the page
Remember to
stay curious.— lab margin
01 / SPECIMEN NOTES

A generalist with a soldering iron.

I am an AI/ML student who likes to move between the physical and digital worlds — wiring sensors, shaping interfaces, and teaching machines to notice useful patterns. This notebook documents the experiments, questions, and systems I am building along the way.

FIELD CLASSIFICATIONEmbedded Systems × Web Development × AI/ML

STATUS: LEARNING IN PUBLIC
LOCATION: PHAGWARA, INDIA

EXAMINED
02 / GRADE REPORT

Academic profile

-- 02ACADEMIC DOSSIER

ACADEMIC
PROFILE

PROGRAMME

B.Tech Artificial Intelligence & Machine Learning

“Knowledge is experimental. Growth is iterative.”

INSTITUTION

Lovely Professional University

2024-28-LPUVERIFIED ENTRY
ACADEMIC SPAN2024 — 2028
CURRENT YEARYEAR 02 / 04
REGISTRATIONACTIVE
STATUSVERIFIED
CURRENT POSITION
03/ 08 SEMESTERS
YEAR 01YEAR 02YEAR 03YEAR 04
01
02
03
YOU ARE HERE
04
05
06
07
08
CUMULATIVE GPA
9.27/ 10.0
ACTIVE DISCIPLINES4/4
01

Data Structures

Algorithms · Complexity
ACTIVE
02

Computer Vision

Spatial Signal Processing
ACTIVE
03

Embedded Systems

Firmware · Hardware Control
ACTIVE
04

Human-Computer Int.

Ergonomics · Interface Models
ACTIVE
03 / TOOLBOX

Current instruments.

“Better Tools.
Bigger Ideas.”

— lab margin

“Same tools.
Bigger dreams.”

— bench note

“A system is only as good as the tools that power it.

HARDWARE / FIRMWARE

INTERFACE WITH REALITY
“Sensing the real world.”
Arduino● INTERMEDIATE
C/C++● INTERMEDIATE
ESP32○ BEGINNER
Sensors○ BEGINNER

WEB DEVELOPMENT

BUILDING INTERFACES
“Making systems people can use.”
React● INTERMEDIATE
TS
TypeScript● INTERMEDIATE
Next.js○ BEGINNER
FastAPI○ BEGINNER

AI / ML

TEACHING MACHINES TO NOTICE
“Teaching machines to notice patterns.”
Python● INTERMEDIATE
scikit-learn● INTERMEDIATE
Computer Vision○ BEGINNER
Prompt Design○ BEGINNER

⚡ SYSTEM BUS

ACTIVE

“Building across hardware, interfaces, and machine learning.”

04 / EXPERIMENT LOGS

Things I have tried to make.

Active project records served directly from FastAPI backend.

CLICK OR TAP A FOLDER TO INSPECT FILE ↘
PROJECT ARCHIVE
CLICK OR TAP ANY CASE FILE TO OPEN SPREAD
EXP-01SENTINEL / NEXAURA↗ INSPECT
[ CASE FILE ]

SENTINEL / NEXAURA

Design a responsive intelligence layer for monitoring complex signals.

PythonReactFastAPI
INSPECT FILE
EXP-02AquaSentinel↗ INSPECT
[ CASE FILE ]

AquaSentinel

Explore an affordable sensing system for water-quality awareness.

ArduinoC++Sensors
INSPECT FILE
EXP-03MIWA↗ INSPECT
[ CASE FILE ]

MIWA

Build a small conversational interface that feels calm and useful.

TypeScriptLLMsUX
INSPECT FILE
EXP-04Rocket Avionics↗ INSPECT
[ CASE FILE ]

Rocket Avionics

Understand how onboard systems report state under constraints.

Embedded CTelemetryCAD
INSPECT FILE
EXP-05Heartbeat Keychain↗ INSPECT
[ CASE FILE ]

Heartbeat Keychain

Make a tiny object that turns biometric rhythm into a tactile signal.

ESP32Pulse sensor3D print
INSPECT FILE
05 / PRACTICE DATA

Repetition is a feature.

Find the work, the half-built ideas, and the clean commits on the board.

GITHUB
github.com/flickstrokefs
LINKEDIN
linkedin.com/in/flickstroke
CODING
leetcode.com/u/flickstroke
RESUME
PDF / available soon
EMAIL
sudhanshuvermafs@gmail.com

“Active log ·
Syncs w/ git repos.”

— lab board
06 / FIELD EXPEDITIONS

Outside the classroom

[ FIELD EXPEDITIONS ]EXPERIENCES, COMPETITIONS, ACHIEVEMENTS & CREDENTIALS
01 / ACADEMIC JOURNEY2025.08 – PRESENT

B.Tech Journey Begins

Lovely Professional University

Pursuing B.Tech in Computer Science & Engineering with specialization in Artificial Intelligence & Machine Learning. Grounded in algorithms, sensor architectures, and autonomous systems.

CUMULATIVE CGPA9.27 / 10.0
“Foundation for heavy engineering.”
02 / EMBEDDED PROJECT2026.01 – 2026.03

Smart Water Management System

ESP32ArduinoIoTSensorsSupabase

Engineered an automated IoT-based irrigation and reservoir awareness telemetry system. Deployed multi-sensor probes for real-time soil moisture, thermal gradient, precipitation, and ultrasonic water-level monitoring.

SOIL MOISTURE68% OPTIMAL
TEMPERATURE24.2°C
WATER LEVEL82% STABLE
RUNNER-UPIIT MANDI ROCKETRY
03 / COMPETITION2026.03

IIT Mandi Rocketry Competition

ALT: 420mBURNOUT: 2.4s

Constructed high-g telemetry avionics and calibrated motor burn timing under extreme environmental constraints. Secured Runner-Up across national university teams.

NATIONAL RUNNER-UP LAUREL
04 / INTELLIGENT SYSTEM2026.05

NeuroLean

AI/MLWeb ArchitecturePersonalized Learning

An AI-assisted cognitive learning platform focused on personalized recommendation graphs, adaptive question pacing, and real-time student mastery modeling.

STUDENT STATE
KNOWLEDGE GRAPH
PROMPT ENGINE
4TH PLACE // IIT ROPAR
05 / ROBOTICS PLATFORM2026.06

WALL-e Line Following Robot

ArduinoSensorsMotorsControl Logic
8-SENSOR ARRAY

Designed and assembled a high-speed differential-drive line-following robot with custom PID control loops, IR sensor arrays, and sub-millisecond path correction.

06 / APPOINTMENTSCONTINUOUS

Roles & Leadership

Leadership appointments, institutional responsibilities, and competitive delegations:

Hardware HeadPresent
CREST-DSRP, Lovely Professional University
Runner-UpJan 2026
SPECTRA, LPU Inter-University Competition
Events Organized & Participated2026
Innotek 2026 · Cognitia 2026 · Smart India Hackathon (SIH)
Runner-UpMar 2026
IIT Mandi Rocketry Competition
[ CREDENTIALS & APPOINTMENTS ]INSTITUTIONAL MEMBERSHIPS & RECOGNITION
CRED-01

Core Member

AI Club · LPU
CRED-02

Project Lead

Robotics Lab
CRED-03

Coordinator

Campus Tech Fest
CRED-04

Mentor

Peer Learning Circle
07 / FUTURE TRAJECTORY

The route is still being drawn.

01
NOW / SEM 03● ACTIVE

Embedded Linux & Spatial Vision

Building deterministic pipelines on ARM targets and exploring OpenCV sensor fusion.

02
NEXT / SEM 04○ NEXT

Edge Tensor Runtime & Low-Power RF

Quantizing neural network weights for microcontrollers using micro-TVM and LoRa.

03
LATER / YEARS 03-04◇ LATER

Autonomous System Deployment

Field validation of multi-agent robotic networks under unreliable link conditions.

08 / OPEN CHANNEL

Send a signal.

CONTACT CARD / SUDHANSHU

Let's build a
useful experiment.

DOWNLOAD RESUME