Hello, I'm

Karan Panwar

Data Scientist / AI Engineer / Researcher

Applied AI engineer and researcher focused on Machine Learning, Generative AI, NLP, recommendation systems, and intelligent applications. I build practical AI systems that combine research with real-world engineering, from LLM-powered applications and personalised recommendation engines to Quantum Machine Learning research.

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Professional Experience

Research Assistant (Generative AI)

Klip Global

September 2025 – June 2026 | Cambridge, UK
  • Led the development of Klip Agent, a personalized digital wellbeing platform integrating LLMs, hybrid recommendation systems, and user behavioral analytics.
  • Designed a hybrid recommendation engine combining Transformer-based NLP, clustering, and NHS data integration to deliver evidence-based wellbeing guidance.
  • Built and deployed an LLM-powered conversational agent using LangChain and Hugging Face models, improving engagement and response quality.
  • Engineered scalable backend architecture using Django and integrated with Next.js frontend frameworks.
  • Collaborated with cross-functional teams (product, data, and research) to continuously improve AI model performance and system usability.

Research Assistant – Quantum Neural Networks

Anglia Ruskin University

Jan 2025 – Apr 2025 | Cambridge, UK
  • Conducted advanced research on Quantum Neural Networks (QNNs) for pattern recognition and image classification using Qiskit.
  • Designed and tested quantum circuits replacing classical layers, achieving a 15% accuracy boost over CNN baselines.
  • Authored detailed research documentation and contributed to a university publication on Quantum Machine Learning.

Selected Projects

KpAgent

AI-Powered Career Assistant

  • Developed comprehensive full-stack career services platform with AI-driven resume analysis and personalised job recommendations.
  • Engineered custom interview preparation tool generating role-specific questions based on user profiles.
  • Built modern responsive UI, delivering polished user experience across all devices.
Next.jsTypeScriptNLPTailwind

SmartStock

Financial Forecast Dashboard

Built an advanced stock prediction dashboard with dynamic time series analysis, predictive models, and financial sentiment analytics using real-time APIs.

PythonLSTM

EmotionSense

Real-Time Emotion Recognition

Created an AI tool detecting facial and vocal emotions with CNN and MFCCs, recommending personalized media content via adaptive algorithms.

OpenCVTensorFlowFlask

SignAI

Sign Language to Text Translator

Engineered an accessibility-driven system converting sign gestures into English text with over 95% accuracy using CNN-based visual models.

DjangoOpenCVDeep Learning

Cambridge Culture Portal

Interactive Cultural Platform

Led a 4-member team developing an interactive cultural platform showcasing Cambridge events and local communities.

DjangoHTMLCSSSQLite

Publications

A Scalable LLM-Based System for Early Mental Health Intervention and Workforce Resilience Using Genkit

Springer — Artificial Intelligence in Healthcare (AIiH 2026)

Published: 12 August 2026 | Cambridge, UK
  • First Author of a peer-reviewed conference paper published by Springer in the Lecture Notes in Computer Science (LNCS) series, Volume 16877.
  • Designed a novel Integrated Agent Architecture (IAA) combining dynamic user profiling, hybrid explainable recommendations, and an empathetic conversational AI framework.
  • Developed a Dynamic User Profiling Engine that synthesizes multimodal inputs including mood, goals, and engagement patterns into evolving user personas using LLMs and structured prompt engineering.
  • Designed a Hybrid Explainable Recommendation Model combining algorithmic filtering with LLM-based contextual re-ranking to provide personalized and transparent wellbeing recommendations.
  • Built the conversational AI layer using Google Genkit and Gemini LLM, with a modern application stack based on Next.js and TypeScript.
  • The work explores scalable, explainable, and personalized applications of Large Language Models, recommendation systems, and AI-driven digital health.
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Core Technical Skills

Programming

Python TypeScript JavaScript SQL Java

AI & Machine Learning

PyTorch TensorFlow Keras Scikit-learn NLP Deep Learning Computer Vision

Generative AI & LLMs

LLMs Google Gemini Google Genkit LangChain Hugging Face RAG Prompt Engineering

Data Science

Pandas NumPy Matplotlib Power BI Tableau

Backend & Web

Django FastAPI Next.js REST APIs TypeScript

Quantum AI

Qiskit Quantum Machine Learning Quantum Neural Networks

Education & Achievements

MSc Computer Science (Distinction)

Anglia Ruskin University, Cambridge, UK

Sep 2024 – Dec 2025

Key Modules: Machine Learning in Finance, AI for Imaging, Semantic Web Technologies, Cybersecurity and AI.

BSc Computer Applications (First Class)

St. Xavier’s College, Ahmedabad, India

May 2021 – May 2024

Key Modules: Data Structures, Big Data Analytics, Database Management, Python Programming, Statistical Modeling

Top Highlights

  • Achieved Distinction in MSc Computer Science (top 10% class ranking).
  • Selected by Klip Global to lead an industrial research project integrating AI with wellbeing analytics.
  • Published and presented university research on Quantum AI and Mental Health Technology.
  • Acted as Team Lead for four cross-functional AI & web development projects at ARU.
  • Received recognition for innovation in AI-based health technology from faculty mentors.

Certifications

AI & ML using Python

IIT Madras (Score: 86%)

AWS Cloud Practitioner

AWS

Python for Data Science

IBM

Software Engineering

JPMorgan Chase

Data Analytics & Viz

Accenture

Virtual Experience

Bank of America

Data Analytics

Quantium

Tech & Innovation

Lloyds Bank

Professional Strengths

Deep expertise in applied machine learning, NLP, and quantum computing with strong mathematical background.

Excellent communicator skilled in translating complex data insights into actionable business strategies.

Passionate about ethical AI, inclusivity, and deploying human-centric intelligent systems.

Adaptable to fast-paced environments with strong teamwork, leadership, and research skills.