I am a PhD candidate at Birkbeck, University of London, working with Prof. Paul D. Yoo. I build AI tools that help predict how rare mental health conditions—and the technologies that support care—may change over time. I aim to give doctors, planners, and researchers clear forecasts and to show how confident we are in each one. I design everything with privacy and safety in mind so people’s data stays protected. I also hold an MSc (Distinction) in Cyber Security from UWE Bristol and have hands-on experience in data science and security.
Birkbeck, University of London — PhD Candidate, Computer Science & Information Systems
Jan 2025 – Present
Research: “Forecasting Mental Diseases and Pertinent Technologies.”
Focus: Graph Neural Networks, Time-Series Forecasting, Uncertainty Quantification, AI for Health.
Supervisor: Prof. Paul D. Yoo.
University of the West of England (UWE Bristol) — MSc Cyber Security (Distinction)
Sep 2021 – Oct 2022
Key coursework: Computer & Network Security, Cyber Security Analytics, IoT System Security, and Research Project.
PhD Researcher in Computer Science
Birkbeck, University of London | Jan 2025 – Present
Building AI-driven forecasting systems integrating 94,000+ time-series observations across 266 months from clinical databases, research publications, and trial registries
Developing graph neural networks and spatio-temporal models for trend detection and uncertainty-aware predictions
Designed scalable data infrastructure using SQL Server and Oracle, implementing ETL pipelines and validation workflows
Published peer-reviewed research on federated learning, explainable AI, and privacy-preserving machine learning
Lab Demonstrator – Data Science & Python Programming
Birkbeck, University of London | Apr 2025 – Jun 2025
Supported undergraduate students in Python programming, machine learning, and cybersecurity lab sessions
Provided technical guidance on experimental methodologies, statistical analysis, and code debugging
Security Researcher
Rochester Institute of Technology (Remote) | May 2023 – Jul 2023
Applied machine learning models to cybersecurity datasets for anomaly detection
Conducted feature engineering and built experimental ML models using Python and PyTorch
Presented research findings to interdisciplinary teams
Assistant Manager – Business Development (Tech Solutions)
ADN DigiNet Ltd | Mar 2021 – Sep 2021
Translated client business problems into practical Data Science, AI/ML, and cloud solution proposals
Developed analytics dashboards, AI chatbots, predictive analytics systems, and automation platforms
Defined project requirements including data needs, system features, and implementation roadmaps
Collaborated with technical teams to deliver feasibility studies and solution architectures
Senior Assistant Manager – AI/ML Infrastructure
Navana Group | Jun 2014 – Feb 2020
Built data analysis infrastructure for Civil Aviation Authority, Bangladesh Police, and Bangladesh Railway
Deployed computer vision models, time-series forecasting systems, and biometric authentication pipelines across critical infrastructure ($1M+ projects)
Developed integrated analytics platforms combining ML pipelines for baggage scanners, explosive detectors, and access control systems
Translated stakeholder requirements into ML system specifications for 20+ government clients
Led technical proposal development and presented ROI analysis to executives
Network Engineer
Prime Net Limited | Dec 2013 – Jun 2014
Configured enterprise networking devices (Cisco, MikroTik, Motorola) ensuring reliable data transmission
Managed Windows Server, Active Directory, DNS, DHCP, and security systems
Analyzed network performance metrics and troubleshooting logs to optimize system reliability
Senior ARC Engineer
EZZY Group | Feb 2012 – Nov 2013
Monitored real-time alarm data from GSM sensors for 24/7 security operations
Conducted R&D on GSM security cameras, home automation systems, and digital security devices
Produced data-driven reports supporting sales targeting and business growth
Teacher – Electronics & Electrical Engineering
Ahsanullah Institute of Technical Education | Oct 2009 – Aug 2011
Rajdhani Polytechnic & Textile College | Nov 2008 – Sep 2009
Delivered lectures, tutorials, and laboratory sessions for diploma-level students
Designed teaching materials, assessments, and practical demonstrations
Supervised electronics labs and mentored students from diverse backgrounds
Key Skills: Machine Learning • Data Science • Python • SQL • Graph Neural Networks • Time-Series Forecasting • Computer Vision • Predictive Analytics • Federated Learning • NLP • Statistical Modeling • ETL Pipelines • Cloud Solutions
🧠 Published Paper:
"Privacy-Enhanced Sentiment Analysis in Mental Health: Federated Learning with Data Obfuscation and Bidirectional Encoder Representations from
Transformers." [peer-reviewed, open access journal]
Authors: Shakil Ibne Ahsan, Djamel Djenouri, Rakibul Haider
DOI: https://doi.org/10.3390/electronics13234650
Funding: This work partly contributes to the REMINDER project, funded under the EU CHIST-ERA program (Grant EP/Y036301/1 from EPSRC, UK).
GitHub Repo: https://github.com/mail2sia/FL_DO.git
An Explainable Ensemble-based Intrusion Detection System for Software Defined Vehicle Ad-hoc Networks. [peer-reviewed, open access journal]
Authors: Shakil Ibne Ahsan, Phil Legg, SM Alam
DOI: https://doi.org/10.1016/j.csa.2025.100090
GitHub Repo: https://github.com/mail2sia/X-IDS_VANET.git
🧾 Preprint
"Privacy-Preserving Intrusion Detection in Software-defined VANET using Federated Learning with BERT".
DOI: https://doi.org/10.48550/arXiv.2401.07343
GitHub Repo: https://github.com/mail2sia/FL_BERT_IDS.git
Co-authors: Prof. Dr. Phil Legg (UWE-Bristol) and Dr. S M Iftekharul Alam (Intel Labs)
🧪 Reviewer Experiences
- Reviewed papers for the 29th IEEE Symposium on Computers and Communications (ISCC), 2024.
- Reviewed papers for the Journal of Cyber Security and Applications.
- Reviewed papers for the 2024 IEEE Future Networks World Forum (FNWF)
The protection of computer systems and networks from attack by malicious actors that may result in unauthorized information disclosure.
That uses statistics, scientific computing, scientific methods, processes, algorithms, and systems to extrapolate knowledge and insights from structured, and unstructured data.
A field of inquiry devoted to understanding and building methods that "learn" – methods that leverage data to improve performance on some set of tasks.
That is able to perform tasks that ordinarily require human intelligence.
CCNA Exploration_Routing LAN, Switching and WirelesSs.pdfCCNA Exploration_Routing LAN, Switching and WirelesSs.pdfCCNA Exploration Routing Protocols and Concepts.pdfCCNA Exploration_Network Fundamental.pdfCCNA Exploration_Network Fundamental.pdf
Just wrapped up an inspiring day at Flower UK Health & Life Sciences Day in Cambridge . The sessions on federated AI and healthcare were right in my wheelhouse. Huge thanks to Prof. Nic and the Department of Computer Science and Technology, University of Cambridge for the invitation and warm hospitality. Grateful for the connections, presentations, and ideas to take forward. Onward to building trustworthy, privacy-first AI for health.
Delighted to receive an Elsevier Certificate of Reviewing for contributions to Cyber Security and Applications. Grateful to support rigorous, reproducible research at the intersection of cybersecurity, privacy, and trustworthy AI.
