More than just a degree
Our team
Syed Danish Hassan is a Lecturer in Data Science & Artificial Intelligence at the University of Europe for Applied Sciences, Dubai campus.
Syed Danish Hassan
Field of Expertise: Artificial Intelligence, Data Science, Machine Learning, Deep Learning, Generative AI, Agentic AI, Learning Analytics, AI in Healthcare & Education
Campus: Dubai
Office Hours: By Appointment
Syed Danish Hassan is a Lecturer in Data Science & Artificial Intelligence at the University of Europe for Applied Sciences, Dubai campus. Syed Danish Hassan is an emerging academic with a growing international profile in both teaching and applied artificial intelligence for education. He is particularly interested in cross-disciplinary approaches that connect AI, data science, and real-world learning outcomes. His research interests focus on agentic AI, generative AI, learning analytics, human-centered AI systems, and AI-enabled education. His work extends beyond academia through his role in building and deploying AI-powered learning models at an EdTech platform, and his contribution as an international expert in higher-education quality assurance and accreditation for AI and Data Science programs.
Academic Experience:
2026 – Guest Faculty & Industry Expert, Cosmoversity, Sharjah, UAE
Delivers industry-aligned sessions on applied AI and education-focused machine learning, mentoring students through project-based learning
2025–2026 – Adjunct Faculty in Data Science & Artificial Intelligence, University of Europe for Applied Sciences, Dubai, UAE
Teaches and mentors students in Python, SQL, statistics, and applied AI, with emphasis on machine learning models for real-world and educational use cases
2019–2022 – Mathematics Teacher, RCC, India
Delivered mathematics instruction achieving a 100% student success rate against the required benchmark
Professional Experience:
2026–Present – International Expert, Institutional & Program Accreditation, National Quality Assurance Agency for Education, Republic of Uzbekistan
Evaluates institutional and program compliance in Computer Science, Data Science, and AI education models, contributing to expert panel accreditation decisions
2025–2026 – AI Growth & Engagement Manager, Buddiz AI, Dubai, UAE
Drives adoption of AI-powered learning models across educational institutions, translating learner-engagement data into product and pedagogical improvements
2024–2025 – Data Science Intern, Fission Labs, Sunnyvale, California, USA
Built predictive models and optimized SQL queries and dashboards to support internal analytics and product decision-making
2023 – Amazon Sorter Associate, Adecco, Berlin, Germany
Operated scanner-based routing systems in a KPI-driven logistics environment, maintaining 99.5%+ sorting accuracy under high throughput
2023 – Coca-Cola Representative, Zett Hospitality GmbH, Berlin, Germany
Collected structured guest feedback at the Special Olympics World Games Berlin 2023, supporting daily reporting on NPS, queue times, and service quality indicators
2026 – Guest Faculty & Industry Expert, Cosmoversity, Sharjah, UAE
Delivers industry-aligned sessions on applied AI and education-focused machine learning, mentoring students through project-based learning
2025–2026 – Adjunct Faculty in Data Science & Artificial Intelligence, University of Europe for Applied Sciences, Dubai, UAE
Teaches and mentors students in Python, SQL, statistics, and applied AI, with emphasis on machine learning models for real-world and educational use cases
2019–2022 – Mathematics Teacher, RCC, India
Delivered mathematics instruction achieving a 100% student success rate against the required benchmark
Professional Experience:
2026–Present – International Expert, Institutional & Program Accreditation, National Quality Assurance Agency for Education, Republic of Uzbekistan
Evaluates institutional and program compliance in Computer Science, Data Science, and AI education models, contributing to expert panel accreditation decisions
2025–2026 – AI Growth & Engagement Manager, Buddiz AI, Dubai, UAE
Drives adoption of AI-powered learning models across educational institutions, translating learner-engagement data into product and pedagogical improvements
2024–2025 – Data Science Intern, Fission Labs, Sunnyvale, California, USA
Built predictive models and optimized SQL queries and dashboards to support internal analytics and product decision-making
2023 – Amazon Sorter Associate, Adecco, Berlin, Germany
Operated scanner-based routing systems in a KPI-driven logistics environment, maintaining 99.5%+ sorting accuracy under high throughput
2023 – Coca-Cola Representative, Zett Hospitality GmbH, Berlin, Germany
Collected structured guest feedback at the Special Olympics World Games Berlin 2023, supporting daily reporting on NPS, queue times, and service quality indicators
- Doctor of Philosophy in Computer Science and Engineering (Ongoing). Amity University, India.
- Master of Science in Data Science. University of Europe for Applied Sciences, Germany.
- Bachelor of Technology in Electronics and Telecommunication Engineering. Government Engineering College, India.
- Master of Science in Data Science. University of Europe for Applied Sciences, Germany.
- Bachelor of Technology in Electronics and Telecommunication Engineering. Government Engineering College, India.
- Human-Centric Agentic AI for Educational Assessment, PhD Thesis, Amity University Chhattisgarh (2025–Ongoing) Investigates adaptive, human-centered AI-agent systems for intelligent and ethical educational assessment.
- RNN-Based Framework for Brain Tumor Segmentation, Master's Thesis, University of Europe for Applied Sciences, Potsdam, Germany (2023) Developed a hybrid RNN + LSTM architecture for MRI-based brain tumor segmentation, achieving a Dice score of 0.85; accepted in the Journal of Artificial Intelligence, Machine Learning and Neural Network (JAIMLNN) (2024) and presented at the 4th International Conference on Electrical, Communication and Computer Engineering (ICECCE 2023), Dubai.
- RNN-Based Framework for Brain Tumor Segmentation, Master's Thesis, University of Europe for Applied Sciences, Potsdam, Germany (2023) Developed a hybrid RNN + LSTM architecture for MRI-based brain tumor segmentation, achieving a Dice score of 0.85; accepted in the Journal of Artificial Intelligence, Machine Learning and Neural Network (JAIMLNN) (2024) and presented at the 4th International Conference on Electrical, Communication and Computer Engineering (ICECCE 2023), Dubai.