Walter Forkel

I'm

About

Determined tech enthusiast with a love for efficiency, eager to solve complicated business problems in a complex environment. Interested in Start-Ups and people with a vision. Passionate about discussing bold ideas, their impact, and strategies for implementing them.

PhD, AI Specialist, Computer Scientist

I have a PhD in Artificial Intelligence (AI), in which I taught the computer to return better answers to complex questions using my strong background in Computational Logic, Computer Vision and Machine Learning. I have entrepreneurial experience with an own Start-up and look forward to founding my next one. In my free time I'm a black belt and martial arts teacher.

If you think we should talk, please contact me.

Resume

Ambitious computer scientist with strong background in Machine Learning and Computational Logic and a passion for efficient and scalable systems.

Professional Experience

Platform Architect, Knowledge Graph Engineer

2022 - present

COSMO CONSULT GmbH, Dresden, Germany

Design and development of an enterprise knowledge graph system to model the whole business domain of COSMO Consult and integrate the existing systems landscape.

Technical Director

2021 - 2022

akili:innovation GmbH, Dresden, Germany

Leading the development of software for Card- and Accessmanagement at airports, stealmills and universities.

Co-Founder, Technical Director

2012 - 2015

FingerCoding UG, Dresden, Germany

Lead the development of interactive E-books for children together with the Swiss book publisher Diogenes in a team of 4 developers.

Education

Ph.D. Knowledge Representation & Reasoning

2017 - 2020

Technical University of Dresden, Dresden, Germany

Improved methods for query answering over temporal data resulting in multiple publications.

Research Visit

2014 - 2015

Weizmann Institute of Science, Rehovot, Israel

Development of an enhanced algorithm for 3D reconstruction of objects from images.

Diploma (M.Sc.) Computer Science

2011 - 2017

Technical University of Dresden, Dresden, Germany

Specialized in Computational Logic, Artificial Intelligence and Machine Learning.

Publications

Computational Logic & Knowledge Representation

Automatic Translation of Clinical Trial Eligibility Criteria into Formal Queries

C. Xu and W. Forkel and S. Borgwardt and F. Baader and B. Zhou. In Proc. of the 9th Workshop on Ontologies and Data in Life Sciencs (ODLS’19), part of The Joint Ontology Workshops (JOWO’19). Ed. by M. Boeker, L. Jansen, F. Loebe, and S. Schulz. CEUR Workshop Proceedings. 2019. https://lat.inf.tu-dresden.de/research/papers/2019/XFB-ODLS15.pdf

Closed-World Semantics for Conjunctive Queries with Negation over \(\mathcal{ELH}_\bot\) Ontologies

S. Borgwardt and W. Forkel. In Proc. of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19). AAAI Press, 2019, pp. 6131-6135. https://dx.doi.org/10.24963/ijcai.2019/849

Closed-World Semantics for Conjunctive Queries with Negation over \(\mathcal{ELH}_\bot\) Ontologies

S. Borgwardt and W. Forkel. In Proc. of the 16th European Conf. on Logics in Artificial Intelligence (JELIA’19). Ed. by F. Calimeri, N. Leone, and M. Manna. Vol. 11468. Lecture Notes in Artificial Intelligence. Rende, Italy: Springer, 2019, pp. 371– 386.
https://dx.doi.org/10.1007/978-3-030-19570-0_24

Finding New Diamonds: Temporal Minimal-World Query Answering over Sparse ABoxes

S. Borgwardt and W. Forkel and A. Kovtunova In Proc. of Rules and Reasoning (RuleML+RR'19). Ed. by Fodor P., Montali M., Calvanese D., Roman D. Lecture Notes in Computer Science, vol 11784. Springer, Cham.
https://dx.doi.org/10.1007/978-3-030-31095-0_1

Patient Selection for Clinical Trials Using Temporalized Ontology-Mediated Query Answering

F. Baader and S. Borgwardt and W. Forkel. In Companion Proceedings of the The Web Conference 2018, pp. 1069-1074. 2018. https://dx.doi.org/10.1145/3184558.3191538

Fuzzing and verifying RAT refutations with deletion information

W. Forkel and T. Philipp and A. Rebola-Pardo and E. Werner. In the Thirtieth International Flairs Conference. 2017. https://aaai.org/ocs/index.php/FLAIRS/FLAIRS17/paper/view/15492

Machine Learning & Computer Vision

Solving uncalibrated photometric stereo using fewer images by jointly optimizing low-rank matrix completion and integrability

S. Sengupta and H. Zhou and W. Forkel and R. Basri and T. Goldstein and D. Jacobs. Journal of Mathematical Imaging and Vision, 60 no.4, 2018, pp. 563-575.
https://doi.org/10.1007/s10851-017-0772-y

Efficient likelihood learning of a generic CNN-CRF model for semantic segmentation

A. Kirillov and D. Schlesinger and W. Forkel and A. Zelenin and S. Zheng and P. Torr and C. Rother. In ArXiv abs/1511.05067, 2015.
https://arxiv.org/abs/1511.05067v2

Contact

If you think we should talk, don't hesitate to contact me.