AI for Cybersecurity Researcher

Raju Molla

MSc researcher in Cybersecurity & Digital Forensics building adaptive intrusion detection for edge–cloud–IoT systems, and a full-stack engineer who ships production software in .NET, Node.js and React.

London, United KingdomTryHackMe — Top 3% Global
Download CV
hybrid-ids — live monitor

[INFO] iot-cloud-sec :: benchmark stream initialised (edge + cloud + orchestration)

[MODEL] random_forest + xgboost :: ensemble vote → benign (p=0.981)

[MODEL] lstm-autoencoder :: reconstruction_error=0.043 :: within baseline

[DRIFT] concept-drift monitor :: distribution shift detected on window t+142

[ADAPT] retraining triggered :: federated update queued across 4 edge nodes

root@edge-node:~$ ▍

Raju Molla

University of Wales Trinity Saint David

MSc in Cybersecurity and Digital Forensics

Jun 2025 – Jun 2026 · London, United Kingdom

Dissertation: Hybrid Intrusion Detection System for IoT and Cloud Environments. Research areas: AI for Cybersecurity, Intrusion Detection Systems, IoT Security, Cloud Security, Explainable AI.

Eastern University

BSc in Computer Science and Engineering — GPA 3.74/4.00

Oct 2018 – Feb 2023 · Dhaka, Bangladesh

Research: Cardiovascular Disease Prediction Using Machine Learning. Relevant areas: Machine Learning, Data Mining, Software Engineering, Algorithms.

> about

A little about me

I'm Raju Molla, a software engineer and cybersecurity researcher currently reading for an MSc in Cybersecurity and Digital Forensics at the University of Wales Trinity Saint David in London. My dissertation builds a hybrid intrusion detection system for IoT and cloud environments — combining Random Forest, XGBoost and LSTM Autoencoder anomaly detection with explainable AI and privacy-preserving federated learning.

Before returning to research, I spent three years as a software engineer at Qtec Solution, Bimafy, A1DIGI and Bangla Institute, building backend systems, payment infrastructure and mobile applications for finance, insurance and healthcare products across Next.js, ASP.NET, Express.js and React Native. That production background is what keeps my research grounded — I care as much about whether a detection system can actually run at the edge as I do about its accuracy.

Key skills

  • Adaptive Intrusion Detection (Random Forest, XGBoost, LSTM Autoencoders)
  • Explainable AI for Security (SHAP)
  • Full-Stack Development (Next.js, ASP.NET, Express.js)
  • Mobile App Development (React Native)
  • Cloud, Edge & IoT Security
  • Penetration Testing (Kali Linux, Burp Suite, Metasploit)
  • Database Design (MongoDB, SQL Server, MySQL)
  • Federated & Privacy-Preserving Machine Learning

> research

Research & Publications

AI for CybersecurityAgentic AIFederated LearningExplainable AI (XAI)Adaptive Intrusion DetectionAdversarial Machine LearningTrustworthy & Robust MLEdge–Cloud–IoT SecurityConcept Drift AdaptationPrivacy-Preserving MLAnomaly DetectionDistributed Cyber Defence

Adaptive Intrusion Detection for Edge–Cloud–IoT

MSc Research · 2025 – 2026

  • Designed a hybrid intrusion detection framework integrating Random Forest, XGBoost, and an LSTM Autoencoder for anomaly detection across heterogeneous edge–cloud–IoT environments.
  • Built IoT-CloudSec, a multi-context synthetic cybersecurity benchmark spanning IoT telemetry, edge metrics, cloud infrastructure indicators, orchestration telemetry, and streaming-system features for leakage-aware intrusion detection evaluation — published on IEEE DataPort.
  • Ran temporal evaluation, robustness analysis, and SHAP-based explainable AI analysis for adaptive cyber threat detection.
  • Investigated concept drift, evolving attack behaviour, unseen-attack detection, telemetry corruption, scalability, and real-time adaptability across distributed infrastructures.
  • Proposed a privacy-preserving adaptive federated intrusion detection architecture for trustworthy cyber defence across distributed edge–cloud ecosystems.
IoT-CloudSec dataset on IEEE DataPort

Publications

Hybrid Intrusion Detection System for IoT and Cloud Environments

Preprint · Research Square

DOI: 10.21203/rs.3.rs-10144004/v1

Beyond Permissions: Multi-Layer Monitoring and Forensic Behaviour Graph Analysis for Detecting Hidden and Collusive Chrome Extensions

Submitted · Forensic Science International: Digital Investigation (Elsevier)

> skills

Skills & Technologies

Cybersecurity

Intrusion Detection SystemsNetwork SecurityCloud & IoT SecurityThreat Detection & AnalysisDigital ForensicsOWASP Top 10

Machine Learning & AI

Random ForestXGBoostLightGBMLSTM AutoencodersAnomaly DetectionExplainable AI (SHAP)Feature Engineering

Security Tooling

Kali LinuxBurp SuiteNmapMetasploitSQLMapFTK Imager

Frontend

React.jsNext.jsReact NativeTailwind CSSFramer Motion

Backend & Languages

Node.jsExpress.jsASP.NETPythonTypeScriptC / C++ / C#

Data & Infrastructure

MongoDBSQL ServerMySQLDockerGitGoogle Cloud

> projects

Selected Work

Research

Research

IoT-CloudSec Research Framework

Hybrid intrusion detection framework combining supervised learning with anomaly-aware sequence modelling, plus SHAP-based explainability and robustness evaluation.

PythonScikit-learnTensorFlowSHAP

Visit
UMIS-v2 (Microfinance)

Web Application

UMIS-v2 (Microfinance)

Distributed microfinance platform deployed across four countries.

ASP.NETSQL ServerReact.js

Visit
UMIS — Uganda / Kenya / Zambia / Tanzania

Web Application

UMIS — Uganda / Kenya / Zambia / Tanzania

Country-specific microfinance deployments serving East African markets.

ASP.NETRazor PagesSQL ServerAjax

Visit
JG Healthcare

Web Application

JG Healthcare

Web platform for healthcare services and patient workflows.

Next.jsExpress.jsMongoDBBootstrap

Visit
Visabee

Web Application

Visabee

Web platform for insurance solutions.

Next.jsExpress.jsMongoDBBootstrap

Visit
Backend / API

Backend / API

Secure Healthcare API System

Secure RESTful APIs for healthcare data management, with authentication, authorization and protected patient-information workflows.

Node.jsExpress.jsMongoDB

Bimafy

Mobile App (Android / iOS)

Bimafy

Mobile app to manage insurance claims, live on Google Play and the App Store.

React Native (Expo)ZustandReact Query

Visit
Bangla Institute

Mobile App (Android)

Bangla Institute

Android app for Bangla Institute's mobile services.

Node.jsExpress.jsMongoDB

Visit

> experience

Professional Experience

Software Engineer

Qtec Solution Limited

Mar 2024 – Jun 2025 Dhaka, Bangladesh
  • Designed and implemented scalable, secure backend systems for financial and healthcare applications, including a payment gateway built on Next.js and MongoDB.
  • Developed and maintained Uganda Microfinance software (UMIS), fixing and extending deployments across Uganda, Zambia, Kenya, and Tanzania (ASP.NET, Razor Pages, SQL Server).
  • Built JG Healthcare (jghealthcare.com) and Visabee (visabee.com.bd) — production platforms on Next.js, Express.js, MongoDB and Bootstrap.
  • Collaborated with international teams to deploy systems across multiple regions with an emphasis on data integrity and reliability.

Software Engineer (React Native)

Bimafy Limited

Oct 2023 – Feb 2024 Dhaka, Bangladesh
  • Developed and deployed cross-platform insurance-claims apps for iOS and Android using React Native, Zustand and React Query.
  • Integrated Google Cloud APIs and built OCR functionality with OpenCV-Python and EasyOCR, exposed via a Flask API.
  • Resolved complex bugs and led implementation of new features, contributing to a more stable release cycle.

Software Engineer

A1DIGI

Jun 2023 – Oct 2023 Dhaka, Bangladesh
  • Built software on the WhatsApp API with a Node.js backend, Next.js frontend and MongoDB.
  • Developed a full-stack website using the MERN stack and contributed to mobile development in React Native.
  • Mentored interns on React.js and Node.js.

Backend Engineer Intern

Bangla Institute

Dec 2022 – Jun 2023 Remote
  • Built backend services and secure authentication systems using Node.js and Express.js.
  • Designed scalable data models and optimised database performance on MongoDB.
  • Delivered a companion Android app for Bangla Institute's mobile services.

> achievements

Achievements & Competitive Programming

Top 3%

TryHackMe, Global

130+

Offensive & defensive security labs

ICPC 2023

Dhaka Regional participant

37th & 38th

Eastern University contests — Champion

Competitive Programming Record

  • ICPC Dhaka Regional Contest 2023
  • CEFALO SUST Inter-University Contest 2023
  • EU 38th Intra-Faculty Contest (2022) — Champion
  • EU 37th Intra-Faculty Contest (2022) — Champion
  • BUET Inter-University Programming Contest 2022
  • EU 36th Intra-Faculty Contest (2022) — 1st Runner-up
  • ICPC Preliminary Contest 2021
  • EU 34th Intra Contest (2021) — 6th Place
  • EU 33rd Intra Contest (2021) — 7th Place
  • Varendra Univ. Inter Contest (2019) — 36th Place
  • EU Intra Contest (2019) — 9th Place

> testimonials

What colleagues say

"Raju is a highly skilled and dedicated software engineer. His problem-solving abilities and commitment to quality are truly commendable. He was a valuable asset to our team."

Sagir Ahmed

Sagir Ahmed

Software Engineer Lead at Qtec Solution

"I had the pleasure of working with Raju on a complex project. His technical expertise, especially in React Native, was outstanding. He's also a great team player."

MD. Altaf Hossain

MD. Altaf Hossain

Senior Software Engineer at Qtec Solution

"Raju consistently delivered high-quality work on time. He's proactive, communicates effectively, and is always willing to go the extra mile. I highly recommend him."

Biprajit Karmakar

Biprajit Karmakar

Software Engineer

> contact

Let's connect