An interdisciplinary researcher and practitioner at the convergence of business and computing, and a regular participant in RoboCup, focusing on developing AI-driven solutions that create measurable real-world value. My work spans robotics, industrial automation, healthcare, finance, smart homes, and energy systems, integrating Artificial Intelligence, machine learning, explainable analytics to solve complex challenges. I am currently affiliated with the ADAPT Centre, Ireland, and Technological University Dublin.
I have designed a novel Explainable AI-based for profit-aware customer churn prediction model, developed intelligent surveillance systems for autonomous drones, and optimized industrial robot performance for real-world deployments. My research bridges predictive accuracy with business relevance, while my teaching equips students to develop data-driven solutions that deliver tangible results.
I have contributed novel metrics to evaluate predictive models for both performance and financial impact and actively translate research into industry-ready solutions. I have supervised multiple projects to completion, including two Masters students at the University of Lahore, both awarded with Best Thesis. At TU Dublin, I supervised an MBA student from industry on his SaaS project leveraging AI to optimize business solutions.
Assistant Lecturer – School of Business Technology, Retail and Supply Chain
Technological University Dublin | Sep 2022 – Present
At TU Dublin, I deliver lectures, assessments, and guidance in marketing and entrepreneurship programs. I monitor and evaluate student performance, contribute to course development, and mentor students on academic and research projects.
Invigilator – Marketing and Entrepreneurship
Technological University Dublin | Sep 2022 – Present
Responsible for examination supervision, ensuring compliance with university regulations, preparing exam materials, and reporting irregularities.
Project Consultant – Graduate Business School
Technological University Dublin | Feb 2024 – Present
Supervise undergraduate and master’s research projects, providing expertise in research design, writing, and industry-relevant applications. Act as second reader for assessment moderation.
Business Development Intern (Hybrid)
JP Morgan | Jun 2023 – Sep 2023
Collaborated with cross-functional teams to enhance business applications, designing features that reduced client onboarding time by 20%. Conducted data analysis to improve system efficiency and user experience.
Research Engineer
LinkedIn | Jun 2022 – Sep 2022
Developed machine learning models for recommendation systems, improving content relevance by 15%. Collaborated on AI solutions and analyzed large datasets to enhance model performance.
Information Security Analyst
FITNESS Research Group | Sep 2020 – Mar 2022
Contributed to EU-funded Horizon 2020 projects (7SHIELD, AFLA, ROBORDER, SpaceApps – Horizon Europe successor: largest EU research & innovation programme, €80B, 27 countries). Developed AI-based threat detection, cybersecurity solutions, and autonomous surveillance systems for critical infrastructure, low-flying aircraft detection, and UAV operations.
Autonomous Robotics Engineer
FANUC, Japan | Oct 2018 – Jun 2020
At FANUC (Global leader in industrial automation), Optimized robotic arms for industrial automation and disaster-response systems. Developed AI-driven rescue robots deployed in disaster management, and deep learning for MRI imaging analysis in collaboration with Koninklijke Philips.
Associate Researcher
Information Technology University, Pakistan | Sep 2017 – Sep 2018
Conducted research in computer vision and network analysis. Developed multimodal face recognition with SJTU Multimedia Lab, China, and entity matching schemes for bibliographic databases (PSF-funded).
Lecturer – Computer Science
The University of Lahore | Sep 2017 – Aug 2018
Taught undergraduate and graduate courses, supervised award-winning student projects, and mentored students in research and thesis development.
Research Assistant
COMSATS University Islamabad | Mar 2016 – Aug 2017
Supported faculty research projects and assisted students with research and publications.
Software Developer
Averox | Sep 2014 – Apr 2016
Designed and implemented scalable web solutions for telecom clients with over 7 million subscribers. Built secure APIs and microservices, improving deployment speed by 60% and reducing response time by 40%.
PhD in Business Technology, Retail and Supply Chain
Technological University Dublin | 2022 – Present
Research focuses on bridging predictive performance with business relevance in customer churn using a profit-aware and explainable AI framework. Developed the e-Profit metric to evaluate AI models based on business impact and accuracy, incorporating XAI techniques (LIME, SHAP, counterfactual analysis).
MSc in Computer Science
COMSATS University Islamabad | 2015 – 2017
CGPA: 3.93 / 4.0
Focused on Machine Learning, Artificial Neural Networks, Digital Image Processing, Computer Vision, Computer Graphics, and Advanced Algorithms.
BSc in Computer Science
Hazara University, Pakistan | 2011 – 2015
CGPA: 3.78 / 4.0
Manzoor, A., Qureshi, M. A., Kidney, E., & Longo, L. (2025). e-Profits: A business-aligned evaluation metric for profit-sensitive customer churn prediction. arXiv preprint arXiv:2507.08860. (Under review at International Journal of Data Science and Analytics)
Qureshi, M. A., Noor, A. A., Manzoor, A., et al. (2025). Explainability in action: A metric-driven assessment of five XAI methods for healthcare tabular models. medRxiv (Under revision at PLOS ONE)
Noor, A. A., Manzoor, A., Mazhar Qureshi, M. D., et al. (2025). Unveiling explainable AI in healthcare: Current trends, challenges, and future directions. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 15(2), e70018.
Manzoor, A., Qureshi, M. A., Kidney, E., & Longo, L. (2024). A review on machine learning methods for customer churn prediction and recommendations for business practitioners. IEEE Access.
Manzoor, A., Judge, M. A., Almogren, A., et al. (2020). A priori multiobjective self-adaptive multi-population based jaya algorithm to optimize DERs operations and electrical tasks. IEEE Access, 8, 181163–181175.
Manzoor, A., Javaid, N., Ullah, I., et al. (2017). An intelligent hybrid heuristic scheme for smart metering based demand side management in smart homes. Energies, 10(9), 1258.
Imtiaz, Z. B., Manzoor, A., ul Islam, S., et al. (2021). Discovering communities from disjoint complex networks using multi-layer ant colony optimization. Future Generation Computer Systems, 115, 659–670. (Pinicipal Investigator and Supervisor of the project)
For a full list of publications, please visit: Google Scholar
Robot Arm Optimization – Industrial automation at FANUC, Japan
Rescue Robots (“Rescue Dogs”) – Disaster management at FANUC in colab with JST, Japan
MRI Imaging Analysis – AI deep learning collaboration with Koninklijke Philips, Japan
Intelligent Threat Detection for Critical Systems – 7SHIELD (EU H2020, now Horizon Europe, €80B, 27 countries)
Low-Flying Aircraft Detection – AFLA (H2020)
Autonomous Border & Coast Surveillance – ROBORDER (H2020)
Vehicle Recognition System & Multimodal Face Recognition – SJTU Multimedia Lab, China
Bibliographic Entity Matching & Network Community Detection – PSF-funded, Pakistan
Postgraduate Scholarship for PhD, Irish Research Council (2021)
Young Talent Leadership, JST, Japan (2019)
Best Supervisor Award, The University of Lahore (2018)
Best Paper Award, CISIS Conference (2017)
Laptop Awards, PM Youth Scheme & Chief Minister Scheme, Pakistan (2013 & 2016, respectively)
Merit Scholarship, HEC Pakistan (2012–2015)
English: C2 (Proficient)
Japanese: B1 (Intermediate / Independent User)
Italian: A1 (Beginner / Basic User)
MATLAB, RapidMiner, Eclipse Java, Google Colab, Python, C# | TensorFlow/Keras | Data Analysis & Business Intelligence | Robot Training & Testing | Cyber Threat Intelligence
Email: ✉️ awais.manzoor@adaptcentre.ie ✉️ awais.manzoor@tudublin.ie ✉️ malik.awaismanzoor@gmail.com