Merging Technology With
Human Values
Driven by a personal motto to "create AI that serves humanity," I am an ACM Published Researcher (1st Author, HCAI-EP '26) bridging the gap between rigorous theory and production engineering.
I architect scalable, legally compliant systems (EU AI Act) across three high-impact domains: Fintech, Healthcare, and Environmental AI—ensuring algorithms are not just accurate, but transparent and fair.
Selected Publications
An Explainable Multimodal Framework for Real-Time Bitcoin Forecasting
Developed a leakage-safe 15-minute resolution forecasting system aligning on-chain metrics, Fear and Greed Index (FGI), sentiment (News/Reddit), and technical indicators. Integrated a dual-layer explainability framework using SHAP attributions and LLM-generated narratives.
AI for Emergency Department Predictions: Fairness & Compression
Evaluated ML models (XGBoost, DNN) on the MIMIC-IV-ED dataset to predict patient admission. Conducted rigorous fairness analysis across age/gender subgroups and demonstrated that model quantization could reduce latency by 50% without accuracy loss.
Education
MSc Human-Centred Artificial Intelligence
Technological University Dublin (Ireland)
Focus & Impact: This program bridged the gap between cutting-edge engineering and regulatory compliance. I moved beyond standard model development to mastering the entire lifecycle of trustworthy AI systems—focusing on risk assessment, transparency, and the legal frameworks (EU AI Act, GDPR, ISO) required for deploying AI in the real world.
- Human-Centric Deep Learning: designing architectures that prioritize explainability and fairness without sacrificing performance.
- Emerging Technologies: Analyzing and implementing state-of-the-art methods in Generative AI and Multimodal systems.
- Risk & Compliance Engineering: rigorous training in data privacy (GDPR), algorithmic auditing, and adhering to the EU AI Act for high-risk applications.
Leveraging the research methods learned in this course, I authored and published a peer-reviewed paper on Explainable AI & Ethical Frameworks at ACM HCAI-EP 2026 (First Author).
BSc (Hons) Computer Systems Engineering
University of Sunderland (UK)
Focus & Impact: This degree provided my foundational engineering rigor. It taught me to think in terms of systems architecture—optimizing for scale, security, and performance.
- System Architecture: Gained deep proficiency in Data Structures, Algorithms, and Advanced DBMS.
- Applied Engineering: Hands-on development of mobile applications and intelligent systems.
- Project Management: Mastered the methodologies required to lead technical lifecycles from concept to deployment.
BTEC HND in Computing
Pearson (UK)
Focus & Impact: Established a versatile full-stack foundation, gaining a practical understanding of how software interacts with underlying infrastructure and networks.
- Core Tech Stack: Practical mastery of Web Development, Programming, and Databases.
- Infrastructure: Fundamentals of Networking protocols and security.
Engineering Experience
Lead Mobile Application Engineer
Edap Technology, Nepal
Led the mobile engineering team with a strong focus on scalable architecture, practical decision‑making, and clear technical direction. Took ownership of how mobile clients communicated with backend systems by enforcing solid API structures and dependable data-sync workflows.
- Leadership & Mentorship: Guided junior developers and interns, set coding standards, ran detailed code reviews, and kept sprint goals on track.
- Enterprise Systems: Built a Real-time Workorder Management System for internal task tracking and a Timesheet Management System, both optimized for offline use and reliable state handling.
- System Design: Architected scalable REST APIs and data pipelines supporting 1,500+ active users across distributed mobile clients.
Flutter Developer
Mavorion Systems & Webhost Nepal
Worked across the full mobile development lifecycle—turning business requirements into reliable, cleanly architected applications that performed consistently across platforms.
- Norvic Hospital Ecosystem: Built the Patient App (lab reports, appointments, service purchases) and a Doctor’s App for day‑to‑day practice workflows.
- Logistics & E‑Commerce: Developed Yellow Express, a courier tracking solution, along with a fully custom E‑commerce platform.
- Technical Execution: Applied Clean Architecture, advanced state management, and secure integrations with third‑party APIs.
Core Competencies
I combine the rigor of classical machine learning with advanced deep learning architectures, ensuring every solution is grounded in responsible AI governance.
Honors & Achievements
"Research in Practice; boost your Research Proposal"
Successfully participated in both virtual and physical learning activities focused on Human-Centred Artificial Intelligence.
Professional Certifications
I learned how to audit high-risk AI systems to ensure they comply with the EU AI Act. This included strategies to prevent algorithmic bias and protect Generative AI models from security threats like prompt injection.
Solidified my practical skills in Deep Learning. I built and trained Convolutional Neural Networks (CNNs) for image recognition and Recurrent Neural Networks (RNNs) for NLP, using TensorFlow.
TensorFlow Computer Vision TransformersFocused on scalable NLP solutions in the cloud. I acquired skills in text processing, sentiment analysis, and implementing topic modeling algorithms to solve real business problems.
Cloud Computing NLP Sentiment AnalysisExecuted deep learning workflows on GPU infrastructure. I implemented transfer learning to optimize performance and applied advanced data augmentation techniques for complex datasets.
GPU Computing Transfer Learning Data AugmentationEstablished a framework for data-driven decision making. I developed proficiency in SQL querying, data cleansing, and effective data visualization.
SQL Data Analysis VisualizationResearch Interests & Career Focus
Target Roles
PhD / Research Roles
I am actively seeking PhD opportunities and research positions in Human-Centred AI. My goal is to work on trustworthy, high-stakes decision-making systems that require both technical excellence and ethical rigor.
Machine Learning Engineer
I am ready to architect scalable, production-ready ML systems. I bring a strong engineering discipline to the table—focusing on reliability, MLOps monitoring, and ethical governance in deployment.
Research Interests
Fintech AI
Fraud detection, risk scoring, and real-time multimodal forecasting for transparent financial decision systems.
Healthcare AI
Fairness auditing, bias reduction, and building trustworthy clinical support tools for sensitive patient data.
Environment & Climate AI
Environmental risk modeling and climate forecasting using multimodal data to drive sustainability goals.
Ready to Build Trustworthy AI?
I am actively seeking Research and development opportunities and Machine Learning Engineering roles.
If you are looking for someone who can bridge the gap between theoretical research and production-grade systems, I would love to hear from you.
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© 2025 Dipesh Badal.
Dublin, Ireland • Open to Relocation