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NAMASTE! I'M

KARTIKCHOUHAN

Software Engineer | Full-Stack Developer | AI/ML & Computer Vision

Building intelligent software systems that combine modern web technologies, backend engineering, machine learning, and computer vision to solve real-world problems.

About Me

Background & Focus

Building Intelligent Software Systems.

I am a final-year Information Technology student at Manipal University Jaipur with a strong interest in software engineering, full-stack development, artificial intelligence, and computer vision. I enjoy building end-to-end systems that combine modern web technologies, backend infrastructure, machine learning models, and real-world automation. My projects range from AI-powered review analysis and computer vision applications to full-stack platforms designed to solve practical problems. Currently, I focus on developing scalable software solutions while continuously exploring machine learning, intelligent systems, and backend architecture.

Information Technology student at Manipal University Jaipur focusing on software engineering, full-stack development, AI/ML, and computer vision.

FOCUS

Full-stack development, AI/ML applications, computer vision systems, and intelligent automation.

APPROACH

Building practical software solutions by combining clean architecture, scalable backend systems, and data-driven intelligence.

BEYOND CODE

Active technical community contributor, event organizer, and continuous learner exploring emerging technologies and real-world problem solving.

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Major Projects
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Students Impacted
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Professional Certifications
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DeceptiScan Model Accuracy

Featured Projects

Selected Creations & Systems

Engineering Lab

Tinkering with models, scripts, and algorithms

Active Sandbox Experiments

deceptiscan-inference.py
python
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification

def analyze_review(review_text: str):
    # Load fine-tuned DeBERTa model and tokenizer
    tokenizer = AutoTokenizer.from_pretrained("microsoft/deberta-v3-small")
    model = AutoModelForSequenceClassification.from_pretrained("./deceptiscan-model")
    
    inputs = tokenizer(review_text, return_tensors="pt", truncation=True, max_length=512)
    with torch.no_grad():
        outputs = model(**inputs)
        probs = torch.softmax(outputs.logits, dim=1)
    
    # Returns probability of review being deceptive (Class 1)
    return probs[0][1].item()

prob = analyze_review("Excellent product! Very highly recommended.")
print(f"Deceptive Probability: {prob:.4f}")
Experiment Metrics & Benchmark
Model Accuracy: 96.8% | Average Inference Latency: ~12ms

Inference runner for DeceptiScan. Loads a fine-tuned DeBERTa-v3 sequence classification model using Hugging Face Transformers to evaluate and output the probability of a product review being deceptive.

Skills & Technologies

Expertise Depth & Domain Map

AI & Machine Learning

Python
PyTorch
Computer Vision
Scikit-Learn
OpenCV
Transformerslearning
YOLOv8learning

Backend & Data

Node.js
FastAPI
Django
MongoDB
PostgreSQL
Express.js
SQLite

Frontend

React.js
TypeScript
Tailwind CSS
Figma

DevOps & Tools

Git
Linux

Engineering

C++

Career Journey

Timeline of Experiences & Milestones

2024 – 2025
Meta, IBM & Oracle

Professional Certifications

achievement

Acquired foundational industry certifications including the Meta Backend Developer Professional Certificate, Meta JavaScript Certificate, IBM Data Analysis with Python, and Oracle Database Programming with SQL to strengthen my programming and data infrastructure skills.

Meta BackendData AnalysisSQL
Sep 2023 – May 2025
LearnIT Technical Club

Senior Coordinator

work

As Senior Coordinator of the LearnIT club, I organized various technical workshops, coding competitions, and hackathons. Coordinating volunteer committees and event logistics allowed me to impact over 400 students while fostering a culture of collaborative peer-to-peer technical learning.

LeadershipCommunity BuildingHackathons
Aug 2023 – May 2027
Manipal University Jaipur

B.Tech — Information Technology

education

Pursuing my Bachelor of Technology degree with an 8.62 CGPA. Core coursework covers data structures, algorithms, databases, operating systems, and computer networks, complemented by elective focus in machine learning and computer vision architectures.

Manipal JaipurInformation TechnologyComputer Science
2023
Bal Bhawan School, Bhopal

CBSE Class XII

education

Completed senior high school education under the CBSE board. Rigorous training in physics, chemistry, and mathematics established the strong logical thinking and problem-solving framework required for my engineering degree.

Science & MathsHigh School
2021
Bal Bhawan School, Bhopal

CBSE Class X

education

Completed secondary high school under the CBSE board, scoring highly across science and computing classes. This period sparked my early curiosity about computer science, software logic, and automated systems.

CBSE BoardFoundational Science

Contact Me

Get in touch or start a project

Let's build something intelligent.

Whether you need to scale an ML inference pipeline, orchestrate a high-throughput distributed backend, or build a responsive interface, I'm always open to discussing new opportunities.

Based in Bhopal, India — Remote Friendly