I am a Computer scientist and data/machine-learning engineer focusing on large-scale data processing, computer vision, and trustworthy ML. At GEOMAR I work on 'AqQua', a modality-agnostic foundation model for aquatic life images. My supervisor is Prof. Dr. Rainer Kiko together with colleagues from Christian Albrechts University Kiel (CAU) and Max Delbrück Center for Molecular Medicine in Berlin.

My interests include self-supervised learning, multi-modal fusion (imagery + geospatial/environmental metadata), and efficient training/inference for ocean-scale datasets. Through 'MarDATA - the Helmholtz School for Marine Data Science' I am part of an interdisciplinary cohort bridging computer science and oceanography.

Skills and expertise

- Machine Learning
- Deep Learning (PyTorch, TensorFlow, Keras)
- Computer Vision & Image Processing (OpenCV)
- Data Engineering (Phyton, Apache Spark, Pandas, NumPy)
- Automation & Testing
- SQL
- Cloud (AWS/Azure)
- Reproducible Science & Data Visualization

Research Interests

• Self-supervised & foundation models for plankton and particle imagery
• Cross-device generalization (UVP, ZooScan, benchtop microscopes) and domain adaptation
• Multi-modal fusion: image + size, geo-temporal context, environmental metadata
• Efficient training on ocean-scale datasets; evaluation, uncertainty & bias in ML for ecology
• Optimization, Graph Theory, Machine Learning, Deep Learning

Education

• M.Sc., Computer Science - Memorial University of Newfoundland, Canada (coursework in Complex Networks, Evolutionary Computation, Computational Complexity, Applied Algorithms, Functional Differential Equations)
• M.Phil., Mathematics - National University of Sciences & Technology (NUST), Pakistan (Mathematical Modeling, Computational Mathematics, Graph Theory, Analysis)
• B.Sc., Mathematics & Statistics - Lahore College for Women University (LCWU), Pakistan (2008–2012; Dean’s List)

Experience

• 2021–2025: Software Test Engineer, 10Pearls - production monitoring, data QA; tools included PyTorch/TensorFlow, Pandas/NumPy, Spark; collaborated with DS/engineering on robust releases (Putty/WinSCP, Postgres, MongoDB, Jenkins, Azure)
• in 2020: Quality Assurance Analyst, Siemens Canada - requirements traceability (Jira), API & DB testing (SQL, Postman), release validation
• 2018-2025: Data Analyst (Freelance) - dashboards + documentation; efficient SQL; anomaly detection; ML pipelines; Tableau reporting
• 2017-2021: Teaching Assistant (CS), Memorial University, Newfoundland/Canada - intro programming, data structures & algorithms, complexity, scientific computing, machine learning
• 2014-2017: Lecturer (Mathematics), Lahore Leads University, Queen Mary College

Teaching & Outreach

Undergraduate CS labs & tutorials; assignment/project grading; preparation of lab manuals; math instruction spanning Discrete Math, Differential Equations, Graph Theory, Calculus and more.

Conference and project highlights

• COVID-19 CT image classification - feature extraction/selection + ML pipelines for diagnosis, extended dataset and methods
• 2018 - Aldrich Interdisciplinary Graduate Research Conference: US Airport Network Centralities — centrality analysis & visualization

Publications & academic projects

Peer-reviewed:

• Episciences: 'Pairwise Stability in Two-Sided Market with Strictly Increasing Valuation Functions, DMTCS'
• MDPI Resources: 'Integration of Regression Analysis and Monte Carlo Simulation for Probabilistic Energy Policy Guidelines in Pakistan'