I received my Ph.D. from the
Department of Computer Science
at
ETH Zurich,
where I was a member of Professor Hans-Jörg Schek’s
Database Research Group (DBS)
of Prof. Hans-Jörg Schek.
After completing my doctoral studies, I joined Professor Heiko Schuldt’s
Database and Information Systems (DBIS)
group of Prof. Heiko Schuldt in the
Department of Computer Science
at the
University of Basel (UNIBAS)
as a researcher.
I later worked as an engineer with the Data Integration team at the
Functional Genomics Center Zurich,
contributing to the development of B-Fabric, a data management platform for the life sciences.
Subsequently, I served as an assistant professor in
the Department of Computer Engineering
at Hacettepe University in Ankara.
I currently work as a freelance professional and teach part-time at the
University of the Potomac in Washington, D.C.
My primary research interests are applied artificial intelligence (AI)
and large language models (LLMs). I have developed user-friendly,
machine-learning-based applications to support physicians in diagnosing
diseases and interpreting medical images, including microscopic and radiological images.
I have extensive experience collaborating with researchers in medicine and the
life sciences and remain open to new research collaborations.
I also occasionally explore problems in finance through personal projects.
Some keywords that sound interesting to me = { ai, llm, machine learning, deep learning, computer vision, nlp, big data, cloud computing, databases }
I am always looking for graduate students who are interested in building machine learning based applications.
Thesis: Curriculum Learning Guided Multimodal and Multitasking Deep Learning Model for Diagnosis and Lesion Localization of Cystic Fibrosis and Non-Cystic Fibrosis Bronchiectasis
Thesis: Generative AI in Healthcare: A Turkish Chatbot for Symptom Assesment and Tailored Recommendations
Thesis: Proposing a Hybrid Method for Mitotic Figure Detection and Counting, and Calculation of Ki67 Index Used for Grading Histopathological Images of Neuroendocrine Tumors
Ayoub Abid
Thesis: Development of a Machine Learning Based
Application for Diagnosing Autoinflammatory Diseases
Thesis: Impact of the Covid-19 Era on the Central
Banks' Monetary Policy Communication: An Analysis of
FOMC Minutes using NLP Techniques (2023)
Thesis: Detection of Transaction Based Manipulations in
Capital Markets (2022)
Thesis: Detecting Tubules and Spermatogonial Stem Cells
in Mouse Testis Micrographs by Using Image Analysis
Techniques (2021)
Thesis: A Hybrid and Reliable Method Integrating Depth
Analysis with Machine Learning Techniques to Predict
Stock Price Directions (2019)
Thesis: Detecting Design Patterns in Object-Oriented
Models by Using a Graph Mining Approach (2016)
Işıkdemir, Y. E., Akal, F.: Attention Based Energy Demand Forecasting in Smart Grid Environments. Firat University Journal of Experimental and Computational Engineering (2024), 3(3), 227-240. https://doi.org/10.62520/fujece.1423120
Taskin, B., Akal, F.: Tales of Turbulence: BERT-based Multimodal Analysis of FED Communication Dynamics Amidst COVID-19 Through FOMC Minutes. Comput Econ (2024). https://doi.org/10.1007/s10614-023-10533-w
Yücel, Z., Akal, F., and Oltulu, P.: Yücel Z, Akal F, Oltulu P.: Automated AI-based grading of neuroendocrine tumors using Ki-67 proliferation index: comparative evaluation and performance analysis. Med Biol Eng Comput. 2024 Feb 27. doi: 10.1007/s11517-024-03045-8. Epub ahead of print. PMID: 38409645.
Tasci, K., Akal, F.: Transforming Temporal-Dynamic Graphs Into Time-Series Data for Solving Event Detection Problems. Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 31: No. 5, (2023). https://doi.org/10.55730/1300-0632.4023
Yücel, Z., Akal, F., and Oltulu, P.: Mitotic Cell Detection in Histopathological Images of Neuroendocrine Tumors Using Improved YOLOv5 by Transformer Mechanism. SIViP 17, 4107–4114 (2023). https://doi.org/10.1007/s11760-023-02642-8
Batu, E.D., Sener, S., Akgün, Ö., Balık, Z., Tanatar, A., Bayındır, Y., Kızıldağ, Z., Torun, R., Günalp, A., Coşkuner, T., İşgüder, R., Aydın, T., Haşlak, F., Cüceloğlu, M.K., Esen, E., Akçay, U., Başaran, Ö., Kısaarslan, A., Akal, F., Yüce, D., Özdel, S., Bülbül, M., Bilginer, Y., Ayaz, N.A., Sözeri, B., Kasapçopur, Ö., Ünsal, E., and Özen, S.: A score for predicting colchicine resistance at the time of diagnosis in familial Mediterranean fever: Data from the TURPAID registry. Rheumatology (2023).
Kahveci, B., Önen, S., Akal, F., and Korkusuz, P.: Detection of spermatogonial stem/progenitor cells in prepubertal mouse testis with deep learning. J Assist Reprod Genet (2023). https://doi.org/10.1007/s10815-023-02784-1
Akal, F., Batu, E.D., Sönmez, H.E., Karadag, S.G., Demir, F., Ayaz, N.A., and Sözeri, B.: Diagnosing Growing Pains in Children by Using Machine Learning: A Cross-sectional Multicenter Study. Med Biol Eng Comput (2022). https://doi.org/10.1007/s11517-022-02699-6
Erdogan, U., Isildar, A.B., Gurgen Erdogan, T., and Akal, F.: Do Lunar Cycles Affect Bitcoin Prices? The International Conference on Computing, Intelligence and Data Analytics (ICCIDA), September 16-17, 2022, Kocaeli, Turkey.
Korkmaz, E., Kunduracioglu, E., Gurgen Erdogan, T., and Akal, F.: Effects of Different Parameters on Sleep Quality. The International Conference on Computing, Intelligence and Data Analytics (ICCIDA), September 16-17, 2022, Kocaeli, Turkey.
Uslu, N.C. and Akal, F.: Borsa Istanbul'da işlem Bazlı Manipülasyonların Yapay Sinir Ağlarıyla Tespit Edilmesi. 7. Uluslararası Bilgisayar Mühendisliği Konferansı (UBMK 2022), 14-16 Eylül 2022, Diyarbakır.
Uslu, N.C., Akal, F.: A Machine Learning Approach to Detection of Trade-Based Manipulations in Borsa Istanbul. Computational Economics, July 2021, https://doi.org/10.1007/s10614-021-10131-8.
Erdal Sag, Fuat Akal, Erdal Atalay, Ummusen Kaya Akca, Selcan Demir, Dilara Demirel, Ezgi Deniz Batu, Yelda Bilginer, Seza Ozen: Anti-IL1 treatment in colchicine-resistant paediatric FMF patients: real life data from the HELIOS registry. Rheumatology, Volume 59, Issue 11, November 2020, Pages 3324–3329, https://doi.org/10.1093/rheumatology/keaa121
Z. Karhan and F. Akal: Covid-19 Classification Using Deep Learning in Chest X-Ray Images. 2020 Medical Technologies Congress (TIPTEKNO), Antalya, 2020, pp. 1-4, doi: 10.1109/TIPTEKNO50054.2020.9299315.
Z. Karhan and F. Akal: Comparison of Tissue Classification Performance by Deep Learning and Conventional Methods on Colorectal Histopathological Images. 2020 Medical Technologies Congress (TIPTEKNO), Antalya, 2020, pp. 1-4, doi: 10.1109/TIPTEKNO50054.2020.9299277.
I. Karabey , A. Yelkuvan and F. Akal: Bulut Bilişim ve Genomik Verilerin Gizliliği. Uluslararası Bilgi Güvenliği Mühendisliği Dergisi, vol. 6, no. 2, pp. 72-88, Dec. 2020
Fuat Akal: Role of Life Sciences Research Centers in Genomic Data Management. International Conference of Genomics and Bioinformatics (ICGB), November 1-4, 2018, Kuşadası, Aydın, Turkey.
Zehra Karhan, Fuat Akal: Detecting and Counting Sister Chromatid Exchange (SCE) Using Image Processing Techniques. International Symposium on Health Informatics and Bioinformatics, October 27-27, 2018, Antalya, Turkey.
Fuat Akal: Life Sciences Research Center and Data Management. 21st National Biomedical Engineering Meeting (BIYOMUT), 24-26 November 2017, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey.
Murat Oruc, Fuat Akal, Hayri Sever: Detecting Design Patterns in Object-Oriented Design Models by Using a Graph Mining Approach. The 4th edition of the International Conference in Software Engineering Research and Innovation (CONISOFT 2016), April 27-29, Puebla, Mexico.
Can Türker, Fuat Akal, Ralph Schlapbach: Life Sciences Data and Application Integration with B-Fabric. Journal of Integrative Bioinformatics, 8(2):159, 2011.
Can Türker, Fuat Akal, Dieter Joho, Christian Panse, Simon Barkow-Oesterreicher, Hubert Rehrauer, Ralph Schlapbach: B-Fabric: On-the-Fly Integration of Life Sciences Applications (Demonstration). 7th International Conference on Data Integration in the Life Sciences (DILS 2010), 25-27 August, 2010, Göteborg, Sweden.
Can Türker, Fuat Akal, Dieter Joho, Christian Panse, Simon Barkow-Oesterreicher, Hubert Rehrauer, Ralph Schlapbach: B-Fabric: The Swiss Army Knife for Life Sciences (Demonstration). 13th International Conference on Extending Database Technology (EDBT), March 22-26, 2010, Lausanne, Switzerland.
Laura Cristiana Voicu, Heiko Schuldt, Fuat Akal, Yuri Breitbart, Hans-Jörg Schek: Re:GRIDiT ‚Äì Coordinating Distributed Update Transactions on Replicated Data in the Grid. 10th IEEE/ACM International Conference on Grid Computing (Grid 2009), October 13-15, Banff, Alberta, Canada.
Can Türker, Dieter Joho, Fuat Akal, Christian Panse, Simon Barkow-Oesterreicher, Hubert Rehrauer, Ralph Schlapbach: The B-Fabric Life Sciences Data Management System. Daten in den Lebenswissenschaften: Vom Paper über Datenbanken zur integrierten Informationsquelle, ILW/GMDS/FGIR Workshop im Rahmen der GI Jahrestagung 2009, September 29, Lübeck, Germany.
Can Türker, Dieter Joho, Christian Panse, Simon Barkow-Oesterreicher, Fuat Akal: Application Coupling and Data Feeding in an Integrative Life Sciences Data Management System. International Conference on Bioinformatics, Computational Biology, Genomics and Chemoinformatics (BCBGC-09), July 13-16 2009, Orlando, FL, USA.
Can Türker, Fuat Akal, Dieter Joho, Ralph Schlapbach: B-Fabric: An Open Source Life Sciences Data Management System. 21st International Conference on Scientific and Statistical Database Management (SSDBM-09), June 2-4 2009, New Orleans, Louisiana, USA.
Fuat Akal, Heiko Schuldt, Hans-Jörg Schek: Toward replication in grids for digital libraries with freshness and correctness guarantees. Concurrency and Computation: Practice and Experience 20(17): 1981-1993 (2008).
Hayri Sever, Fuat Akal, G. Köse. Kavram Tabanli Bilgi Geri Getirim Yaklasimi. Bilgi Dünyasi, vol. 8(1):pp. 49-75, 2007.
Leonardo Candela, Fuat Akal, Henri Avancini, Donatella Castelli, Luigi Fusco, Veronica Guidetti, Christoph Langguth, Andrea Manzi, Pasquale Pagano, Heiko Schuldt, Manuele Simi, Michael Springmann, Laura Voicu: DILIGENT: integrating digital library and Grid technologies for a new Earth observation research infrastructure. International Journal on Digital Libraries (IJDL) 7(1-2): 59-80 (2007)
Fuat Akal, Can Türker, Hans-Jörg Schek, Yuri Breitbart, Torsten Grabs, Lourens Veen: Fine-Grained Replication and Scheduling with Freshness and Correctness Guarantees. VLDB 2005: 565-576, Trondheim, Norway.
Fuat Akal, Klemens Böhm, Hans-Jörg Schek: OLAP Query Evaluation in a Database Cluster: A Performance Study on Intra-Query Parallelism. ADBIS 2002: 218-231, Bratislava, Slovakia.
Akal, F.:
Can AI Replace Rheumatologists?
The 29th European Paediatric Rheumatology Congress, 28 September - 1
October, Rotterdam, Netherlands, 2023.
Akal, F.:
AI vs. Rheumatologist
2. Romatolojiye Panoramik Bakış Sempozyumu, 4-7 Mayıs, NG Enjoy
Hotel, Sapanca, 2023.
Akal, F.:
How Machines Learn Diabetes Mellitus?
4. Diyabet Teknolojileri Sempozyumu, 15-17 Aralık, Grand Hotel
Ankara, 2022.
I teach several interesting classes every semester. One class I always
volunteer to give is the Introduction to Programming course. It allows
me to get in touch with freshmen. It also helps me keep my Python
abilities sharp. In the data-intensive applications class, I teach
students how to use machine learning in problem-solving. I cover big
data processing architectures and platforms in the cloud computing and
next generation databases classes.
I started
The Good Class
recently. I must admit that I did not create much content yet. But, I
promise to improve it. I want to share my thoughts, experiences, and
knowledge for free with all interested parties. I intend to stay mostly
technical. I will focus on data science, machine learning, and Python.
Visit thegoodclass.net Home Page!
Or, you can find two sample blog posts below for your easy access.
There are several metrics we can use for evaluating a machine learning (ML) model. One of them is accuracy... ...
Let us say you developed a machine learning model to diagnose
Growing Pains (GP) in children. It is a disease, ...
Let's assume you have a prediction model that returns a probability score to indicate how likely a tumor tissue sample ...
Read