Shaheen Syed Email & Phone Number

Trondheim, Trøndelag, Norway

• Expertise in anomaly detection using 2D autoencoders for fiber optical data (DAS, DTS)• Experience implementing CI/CD pipelines for efficient model development and deployment• Proficient in using Azure ML Studio for machine learning model development and deployment.• Knowledge of MLOps principles and best practices for managing the end-to-end machine learning lifecycle.• Member of the Equinor Responsible AI core team

Tromsø, Troms Og Finnmark, Norway

• Proven experience in developing and publishing novel algorithms in reputable journals for the analysis of physical activity using raw accelerometer data• Adjunct research position at the Department of Computer Science, with a focus on the application of machine learning techniques to analyze complex data sets• Supervising PhD students in the field of machine learning and data analysis, providing guidance and mentorship in the development of research projects and theses.

Tromsø, Troms Og Finnmark, Norway

• Proven expertise in designing and implementing machine learning and deep learning models for the analysis of complex tri-axial accelerometer and ECG data, resulting in open source repositories and several published scientific articles.• Senior engineer position at the Department for Computer Science

Tromsø, Troms Og Finnmark, Norway

• Implemented custom LinkNet models with DenseNet encoders to effectively perform semantic segmentation and object detection of parasites in white fish using hyperspectral imaging data.• Successfully optimized preprocessing, inference, and post-processing to meet strict industrial latency requirements.• Conducted extensive research on the utilization of class activation maps for weakly supervised semantic segmentation of t2-weighted MRI data, and published work in respected journals.• Led research efforts in the application of deep learning for classification and segmentation of MRI data, resulting in several publications in respected journals.

Manchester, England, United Kingdom

• Research utilizing natural language processing (NLP) and machine learning (ML) techniques to uncover patterns, trends, latent topics, social networks and clusters from textual data, specifically scientific research articles.• Project funded by the European Union Horizon2020 - Marie Curie - European Training Network• Research into: semantic lexicon bootstrapping, topic models, latent Dirichlet allocation, Bayesian priors, author-topic models, coherence scores, social network analysis, sentiment analysis, web scraping.

Tromsø, Troms Og Finnmark, Norway

• Developing a web crawler to automatically collect, parse, classify, centralize, and synthesize news articles related to food fraud incident reports by utilizing machine learning and natural language processing techniques together with the development of a web interface to easily maintain, monitor, and extend the settings of the crawler, classifier, and parser.• Experience with: Scikit-Learn, TensorFlow, Machine Learning, Python, Django, MongoDB, Ubuntu, Google Developer APIs, web scraping.• Project-based contract (EU Horizon2020)

Rotterdam, South Holland, Netherlands

• Data migration (ETL) of 1.5 million customers from SAP to Dynamics AX for Dutch energy company.• Creating software to automatically calculate NAFTA duty reductions for highly complex chemical substances.• Automating REACH and GHS regulatory compliance for US Fortune 500 company.• Converting single client web applications to Software as a Service.• Programming: .NET, ASP.NET, C#, VB.NET, Perl, HTML5, CSS3, JavaScript,JQuery.• Data: SQL, T-SQL, PL-SQL, XML, SQL Server, Oracle, DB2, Excel, VBA, SAP.

Utrecht, Netherlands

• As part of my master thesis, and in collaboration with dr. Slinger Jansen, we developed a regression formula that is able to predict open source project failure with 70% accuracy. We adopted the method from E. Altman, the so called Z-score model to predict corporate bankruptcy. We used data mining techniques to mine open source project determinants from SourceForge, and used multiple discriminant analysis (MDA) to predict project failure and non-failure.• Experience with: Social Network Analysis, SPSS, Graph Theory, Regression, Data mining, R, Open Source.

Utrecht, Netherlands

• Elected and paid position with a workload of 10 hours a week.• Representing students in bi-weekly department meetings.• Meetings with full professors and members of the (beta) Faculty• Optimizing the curriculum within the management team.

Utrecht, Netherlands

• Assistant for the course ’Scientific Research Methods’ followed by both bachelor and master students.• Guiding and helping students with statistics, methods, projects and workshops.

Rotterdam, South Holland, Netherlands

• Specialized in all software and hardware related repairs of mobile phones, tablets, laptops and other electronic devices.• Experience with software flashing, EEprom programming, BGA repairs, SMD rework.

Doctor Of Philosophy - Phd, Computer Science

EU Horizon 2020 Marie Skłodowska-Curie fellowship. Dissertation: Topic Discovery from Textual Data: Machine Learning and Natural Language.

Master Of Science (M.Sc.), Business Informatics

Cum Laude, GPA 4.0/4.0

Bachelor Of Science (B.Sc.), Computer Science

Awarded best student propaedeutic phase