Dr. Happy N. Monday
Dr. Happy N. Monday
About Me
About Me
Dr. Happy Nkanta Monday is an Associate Professor and Applied Artificial Intelligence Strategist with a proven record of delivering scalable, explainable, and high-performing AI systems that move beyond research prototypes into production environments.
He blends technical depth with business understanding, bridging data science, cloud engineering, and product delivery to create measurable value in sectors such as healthcare, energy, and industrial automation.
Over the past decade, he has built and deployed intelligent systems that integrate machine learning, deep learning, large language models (LLMs), retrieval-augmented generation (RAG), and computer vision. His projects consistently focus on accuracy, reliability, interpretability, and deployment speed, using frameworks such as TensorFlow, Keras, Scikit-learn, LangChain, LangGraph, Streamlit, and FastAPI.
Dr. Monday currently leads AI initiatives that unify model development, data governance, and system integration across multi-disciplinary teams. His work transforms raw data into actionable insights through end-to-end ML pipelines, covering data ingestion, preprocessing, feature selection, model training, hyperparameter tuning, validation, and front-end deployment with Streamlit, FastAPI, and cloud-native tools.
His industrial and applied portfolio includes:
- Clinical AI systems : Developed an Adaptive Focal Cross-Entropy ECG model that improved minority-class recall by 12% and increased diagnostic stability by 18%.
- Explainable ML frameworks : Designed the Fusion-based Feature Selection (FFS-IML) pipeline using SHAP and LightBoost, reducing feature redundancy by 45% with zero AUC loss.
- Enterprise Knowledge Assistants : Built multi-format document retrieval assistants using LLM + RAG pipelines with LangChain and ReAct for contextual enterprise search and summarization.
- Imaging and Vision Systems : Engineered super-resolution neural networks (mESRGAN, RCAN) that enhanced low-quality CT and CXR diagnostics, reducing review time by 25%.
- Energy and Sustainability Platforms : Designed predictive dashboards integrating ML models with real-time APIs and Supabase to forecast consumption and carbon intensity for smart-grid applications.
Beyond engineering, Dr. Monday is a results-oriented leader recognized for his ability to translate complex AI concepts into deployable business solutions. He collaborates across functions, working with clinicians, data engineers, and product teams to ensure every AI solution aligns with operational objectives, compliance requirements, and end-user experience.
His leadership style emphasizes mentorship, innovation, and code excellence. He has guided cross-functional engineering teams through agile delivery cycles, implemented model versioning and monitoring pipelines, and institutionalized responsible-AI review processes to ensure fairness, transparency, and reliability at deployment scale.
With experience spanning North America, Asia, and Africa, Dr. Monday brings a global perspective to data-driven transformation. His career has been defined by measurable impact, boosting model accuracy, cutting deployment latency, reducing cost-to-insight, and enabling faster decision-making through intelligent automation.
He continues to explore next-generation directions in generative AI, multi-modal perception systems, agentic AI architectures, and AI-powered sustainability analytics. Whether collaborating on industrial process optimization or leading applied research teams, his mission remains clear: build AI that performs, explains, and scales responsibly.
Research Interest
.
Medical Image Processing and Analysis
.
Large Language Model (LLM)
.
Retrieval-Augmented Generation (RAG)
.
Agentic AI
.
Medical Image Disease Diagnosis
.
Biomedical informatics
.
Artificial Intelligence
.
Industrial Informatics
.
Machine Learning
.
Agricultural Informatics
.
Environmental Sustainability
.
Energy Informatics
.
Deep Learning
.
Pattern Recognition
.
Business Intelligence and Informatics
News
[Recognition Award]
Dr. Happy Monday is honored to receive the
Outstanding Instructor Award,
becoming the first foreign lecturer
in Chengdu University of Technology history
to earn this recognition. This award was presented in acknowledgment of his role as
Co-Lead Instructor for the
first CSC-sponsored Summer School Program
in CDUT history.
This recognition underscores his dedication to academic excellence, international collaboration,
and advancing innovative teaching in Artificial Intelligence.
Outstanding Instructor Award
July 28, 2025
Chengdu University of Technology
Recognition Award
[Prestigious Nomination]
Dr. Happy Monday is deeply honored to be nominated by the
Chinese Government Council under the
Chinese Scholarship Council (CSC) as one of the
Lead Instructors for the
2025 CDUT International Summer School on
AI-driven Sustainable Urban Development.
This prestigious selection reflects his continued commitment to excellence in teaching, research, international collaboration, and the advancement of cutting-edge AI solutions for global challenges.
CSC Nomination
June 14 – July 28, 2025
Chengdu University of Technology
International Summer School
[Event]
For the first time, the research achievements of our students guided by Dr. Happy and Dr. Grace have been published in a top-tier international journal, marking a significant milestone for the College of International Education, Chengdu University of Technology Oxford Brookes College. Impact Factor:8.9 Computers and Electronics in Agriculture.
[Service]
Happy N. Monday is serving as a member of the Technical Committee for the 2025 IEEE 8th International Conference on Pattern Recognition and Artificial Intelligence (PRAI 2025), August 15-17, 2025.
[Event]
Happy N. Monday is honored to be nominated as a co-lead Instructor for the 2025 CDUT International Summer School Program on AI, June 14 - July 28, 2025. Many thanks for the acknowledgment.
[Award]
Our work “Attention-Enhanced Ensemble Learning for Diabetic Retinopathy Classification with Interpretability” is selected as one of the 2024 ICAIT Best Oral Presentation Award.
[Activity]
Happy N. Monday was nominated as one of the foreign experts in China by the Ministry of Foreign Expert Bureau to join in the Foreign Expert Workshop "Walk into the Glamourous Chengdu", (2024/09).
[Service]
Happy served as a member of the Technical Committee, 8th International Conference on Algorithms, Computing and Systems (ICACS 2024: http://icacs.org), Hong Kong, October 11-13, (2024)
[Service]
Happy served as a member of the Technical Committee Member, International Computer Conference on Wavelet Active Media Technology and Information Processing, (2024)
[Service]
Happy N. Monday is the Co-Chair of the Computing Research Team at the Oxford Brookes University of Chengdu University of Technology, (2023)
[Event]
Happy N. Monday joined Oxford Brookes University of Chengdu University of Technology Computing Department and will teach CHC 6781 Machine Vision in Autumn 2022 and conduct research. (2022/08)
[Award]
Our work “The capability of multi-resolution analysis: A case study of COVID-19 diagnosis” is selected as one of the 2021 PRAI Best Paper Award. (2021)
Selected Publications
[1]
Xudong Li, Yutong Wang, Happy Nkanta Monday, Grace Ugochi Nneji,“A novel residual learning of multi-scale feature extraction model for the classification of rice grain varieties”, Computers and Electronics in Agriculture 237 (June 2025): 110491. [PDF]
[2]
Happy Nkanta Monday, Grace Ugochi Nneji, Md Altab Hossin, Kelvin Davies Mark, Edwin Sunday Umana, Goodness Temofe Mgbejime,Jianping Li, “Enhancing ECG Classification in Cardiac Diagnostics: A Novel Approach Using Adaptive Focal Cross-Entropy Loss Function”, IEEE Journal of Biomedical and Health Informatics 197 (May 2025) 150-157. [PDF]
[3]
Nneji, G.U., Monday, H.N., Pathapati, V.S.R. et al. “FFS-IML: fusion-based statistical feature selection for machine learning-driven interpretability of chronic kidney disease”, Int. J. Mach. Learn. & Cyber. (April 2025). [PDF]
Curriculum Vitae
Academic & Professional Timeline
📚 Lead ML Engineer | Associate Professor
CDUT-AI Center | Chengdu University of Technology, April 2025 – Present
🎓 Postgraduate Certificate in International Education (PGCiE)
Staffordshire University, UK. 2023
🧪 Senior AI Research | Assistant Professor
CDUT-AI Center | Chengdu University of Technology, Aug 2022 – Mar 2025
🎓 Ph.D. in Computer Science
University of Electronic Science and Technology of China (UESTC), 2022
🎓 MEng. in Electronic Science and Technology
University of Electronic Science and Technology of China (UESTC), 2018
🎓 BEng. in Engineering
Federal University of Technology, Akure (FUTA), 2014
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