Aaqib Saeed
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Researcher, NGF AiNed Fellow, AI for Healthcare, Assistant Professor
I am a Senior Assistant Professor (tenured) at Eindhoven University of Technology (TU/e) and my research is supported by an NGF AiNed Fellowship Grant. I hold a Ph.D. cum laude from TU/e, where I conducted research in the Department of Mathematics and Computer Science, on self-supervised learning for sensory data (ECG, EEG, IMU, PPG and Audio). Previously, I completed MSc. cum laude in Computer Science with a specialization in Data Science and Smart Services at the University of Twente. My work experience includes research stints at Google Brain and at the University of Cambridge’s Mobile Systems Lab as an industrial fellow. Before joining TU/e as faculty, I worked as a Research Scientist in AI at Philips Research, where I contributed to advancing AI for sensing applications. My research interests span Agentic AI, Multimodal Language Models, Self-Supervised Learning, Federated Learning, Audio Understanding and their applications in Healthcare and High-tech Industries.
Eindhoven University of Technology
Doctor of Philosophy - PhD with Cum Laude , Computer Science
October 1, 2017 – July 1, 2021
University of Twente
Master’s Degree with Cum Laude, Computer Science - Data Science and Smart Services
January 1, 2015 – January 1, 2017
Karachi Institute of Economics & Technology (KIET)
Bachelor of Science - BSc with Distinction, Computer Science
January 1, 2011 – January 1, 2014
Eindhoven University of Technology
Assistant Professor (Tenured)
March 1, 2023 – Present
Eindhoven, North Brabant, Netherlands
University of Cambridge
Industrial Fellow
September 1, 2021 – September 1, 2022
Philips
Research Scientist AI
August 1, 2021 – February 1, 2023
Netherlands
Research Intern - Deep Learning
July 1, 2020 – October 1, 2020
Paris, France
Research Intern - Machine Intelligence
June 1, 2019 – September 1, 2019
Zurich, Switzerland
Eindhoven University of Technology
PHD Candidate
October 1, 2017 – June 1, 2021
Eindhoven, North Brabant, Netherlands
Philips
Research Intern - Deep Learning
November 1, 2016 – May 1, 2017
Eindhoven, North Brabant, Netherlands
TNO
Machine Learning Intern
July 1, 2016 – October 1, 2016
Eindhoven, North Brabant, Netherlands
PAF-KIET
Undergraduate Research Assistant
September 1, 2012 – September 1, 2013
Karachi
Hadoop Platform and Application Framework
Coursera Course Certificates
June 24, 2026 – Present
The Data Scientist’s Toolbox
Coursera Course Certificates
June 24, 2026 – Present
Web Application Architectures
Coursera Course Certificates
June 24, 2026 – Present
R Programming
Coursera Course Certificates
June 24, 2026 – Present
Machine Learning
Coursera Course Certificates
June 24, 2026 – Present
Introduction to Big Data Analytics
Coursera Course Certificates
June 24, 2026 – Present
Introduction to Big Data
Coursera Course Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily academic and research-oriented, with roles at universities and research divisions of large companies. This indicates a strong fit for an innovative, research-driven culture. The diversity of institutions (Eindhoven, Cambridge, Google, Philips) suggests adaptability. However, the lack of explicit project details makes it difficult to assess collaboration styles or experience in diverse team settings beyond academic research groups.
Soft Skills & Operational Fit
The candidate's academic and research background suggests strong analytical thinking, problem-solving, and independent research capabilities. Experience as an Assistant Professor implies good communication and mentoring skills. However, specific operational fit regarding agile methodologies, project management, or direct team collaboration in a corporate setting is not explicitly detailed in the provided experience descriptions.