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Meet Prof. Dr. Raja Hashim Ali, a leading expert in Machine Learning and Data Science at UE Innovation Hub, Potsdam. Learn more here!
Prof. Dr. Raja Hashim Ali
Field of Expertise: Machine Learning, Deep Learning, Artificial Intelligence, Data Science, Bioinformatics.
Campus: UE Innovation Hub
Office Hours: By Appointment
Prof. Dr. Raja Hashim Ali is an accomplished academic and industry professional with over 13 years of teaching experience at prestigious institutions, including the University of Europe for Applied Sciences (Germany), Uppsala Universitet (Sweden), Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (Pakistan), and COMSATS Institute of IT (Pakistan).
In the industrial sector, Prof. Dr. Ali served for more than three years as a Quality Assurance Engineer at EnterpriseDB (Islamabad, Pakistan), a global software company headquartered in New York, USA. His research career spans over 13 years, with significant contributions at esteemed research centres such as the AI Research Lab and Machine Intelligence Group (GIK Institute, Pakistan), Whelan Lab (Uppsala University, Sweden), and Arvestad Lab (KTH Sweden).
Prof. Dr. Ali has demonstrated exceptional leadership and administrative acumen, having held positions such as Head of the Programme of BSc Digital Business and Data Science, Acting Dean of the Faculty of Computer Science and Engineering (FCSE), and member of numerous academic and administrative committees. He played a pivotal role in developing new academic programmes in Artificial Intelligence, Data Science, and Cybersecurity, as well as ensuring national-level accreditation for engineering programmes.
Recognised for his excellence in teaching and research, Prof. Dr. Ali has received multiple accolades, including several letters of appreciation and Best University Teacher Awards. He has also secured scholarships for advanced studies and managed multiple funded projects, collectively worth millions, supporting pioneering research in artificial intelligence, machine learning, and bioinformatics.
As a distinguished researcher, Dr. Ali has published 15 papers in high-impact journals, including Molecular Biology and Evolution and IEEE Transactions on Mobile Computing, along with over 50 conference papers presented at renowned IEEE and other forums. His research primarily focuses on the application of AI, machine learning, and deep learning to real-world problems, as well as theoretical foundations of bioinformatics.
Prof. Dr. Ali has supervised 32 graduate students and 16 undergraduate design projects, fostering the next generation of innovators in AI and bioinformatics. Additionally, he has played an active role in organising international conferences, delivering tutorials, and mentoring students and faculty on cutting-edge digital and AI technologies.
In the industrial sector, Prof. Dr. Ali served for more than three years as a Quality Assurance Engineer at EnterpriseDB (Islamabad, Pakistan), a global software company headquartered in New York, USA. His research career spans over 13 years, with significant contributions at esteemed research centres such as the AI Research Lab and Machine Intelligence Group (GIK Institute, Pakistan), Whelan Lab (Uppsala University, Sweden), and Arvestad Lab (KTH Sweden).
Prof. Dr. Ali has demonstrated exceptional leadership and administrative acumen, having held positions such as Head of the Programme of BSc Digital Business and Data Science, Acting Dean of the Faculty of Computer Science and Engineering (FCSE), and member of numerous academic and administrative committees. He played a pivotal role in developing new academic programmes in Artificial Intelligence, Data Science, and Cybersecurity, as well as ensuring national-level accreditation for engineering programmes.
Recognised for his excellence in teaching and research, Prof. Dr. Ali has received multiple accolades, including several letters of appreciation and Best University Teacher Awards. He has also secured scholarships for advanced studies and managed multiple funded projects, collectively worth millions, supporting pioneering research in artificial intelligence, machine learning, and bioinformatics.
As a distinguished researcher, Dr. Ali has published 15 papers in high-impact journals, including Molecular Biology and Evolution and IEEE Transactions on Mobile Computing, along with over 50 conference papers presented at renowned IEEE and other forums. His research primarily focuses on the application of AI, machine learning, and deep learning to real-world problems, as well as theoretical foundations of bioinformatics.
Prof. Dr. Ali has supervised 32 graduate students and 16 undergraduate design projects, fostering the next generation of innovators in AI and bioinformatics. Additionally, he has played an active role in organising international conferences, delivering tutorials, and mentoring students and faculty on cutting-edge digital and AI technologies.
- Visiting Lecturer / Professor at Department of Data Science Feb. 2022 – Present University of Europe for Applied Sciences, Potsdam Campus, Germany
- Taught Machine Learning Graduate course in Spring 2022. Main topics included preprocessing of datasets, handling missing data, feature selection techniques, supervised learning techniques, fundamentals of neural networks, unsupervised learning techniques, evaluation metrics, and case study, with examples in Python for each topic on Titanic survival dataset. The pre-requisite for the course was Programming in Python course. The course evaluation was not received.
- Taught Pre-Course Programming graduate preparatory course spanning one month in Winter 2022/2023 and in Winter 2023/2024. Main topics included setting up jupyter notebook on Macintosh and Windows, introduction to python, python syntax – variables, data types, basic operations, comments, and indentation, control structure – conditional statements (if, elif, else), loops (for and while), return and continue statements, and logical operators (and, or, not), functions – defining and calling functions, and parameters and return values, handling inputs and outputs – reading user input and displaying output, working with files, error handling – exceptions and handling errors with try except blocks, and using built-in modules and libraries. There was no pre-requisite to this course. The course evaluation was 100%.
- Taught Introduction to Programming in Python graduate elective course in Summer 2023. Main topics included all the topics taught in Pre-Course Programming course. Additionally,more advanced topics taught in this course included data structures in python – Lists, tuples, amd dictionaries, string manipulation – slicing, and formatting, using advanced libraries – pandas, numpy, and matplotlib, and exploratory data analysis and visualization of a dataset using Titanic survival dataset as a case study. The course had no pre-requisite. The course evaluation was 100%.
- Assistant Professor Aug. 2018 – June 2023 | Associate Professor Jul. 2023 – Present GIK Institute of Engineering Sciences & Technology, Topi, Pakistan at Department of Artificial Intelligence, Faculty of Computer Science & Engg.
- Mar. 2016 – May 2018 Uppsala Universitet, Uppsala, Sweden Researcher at Evolutionary Biology Center (EBC) Assisted in courses related to Bioinformatics and Molecular Biology.
- Tutor Nov. 2010 – Feb 2016 Kungliga Tekniska Hogskolan (KTH), Stockholm, Sweden at Department of Computational Biology, School of Comp. Science & Comm.
- Aug. 2009 – Sep 2010 COMSATS Institute of Information Technology, Islamabad, Pakistan Lecturer at Department of Biosciences
- Jun 2006 – Aug 2009 EnterpriseDB PK (SMC-Private) Private Limited, Islamabad, Pakistan Software Quality Assurance Engineer in QA Department
- Kungliga Tekniska Högskolan (KTH) Stockholm, Sweden, PhD in Computer Science (spec. in Comp. Biology)
- Chalmers University of Technology Göteborg, Sweden, MSc in Information Technology (spec. in Bioinformatics)
- Ghulam Ishaq Khan (GIK) Inst. of Engg. Sciences & Tech. Topi, Pakistan, BSc in Computer Systems Engineering
- Artificial Intelligence: Intro to AI (BSc), Artificial Neural Networks (BSc), Algorithms for Machine Learning and Inference (MSc), Computational Python (PhD).
- Bioinformatics: Sequence Bioinformatics (MSc), Structural Bioinformatics (MSc), Algorithmic Bioinformatics (PhD), Classical Papers in Bioinformatics (PhD).