Machine Learning, Smart TV, Telecommunications Expert Witness
Published peer-reviewed articles extensively in international conferences and journals, as well as book chapters. Presented to a wide range of audiences, such as boards of directors, conferences, and as a regular investor panelist.
As an expert, he has completed cases in:
- Patent infringement, ITC
- Trade secret
- Breach of contract
- Technical due diligence
- Pre-litigation discovery
- Technology architecture
He has been retained on cases involving major technology companies, including:
- Universal Electronics
- Unified Patents
- Berkshire Hathaway
Machine Learning, Artificial Intelligence:
- Neural networks, deep learning, graph-based data mining, social network analysis, supervised-, unsupervised-, reinforcement learning, clustering,
- Autonomous vehicles: Drive stack, simulation, robotics, drones, location technologies (GPS, SLAM, vSLAM, WiFi, etc.), sensors (Lidar, Radar, IR, SWIR, sonar, etc.)
- Smart TVs and set-top boxes, Media delivery, Streaming, MPEG, JPEG, content acquisition (digital cameras, cinematography, editing, coloring, encoding)
Internet of Things (IoT):
- Connected home, Smart home, connected vehicles, industrial applications, predictive maintenance and analytics
Augmented Reality and Virtual Reality (AR/VR)
- HMDs, optical subsystems, eye tracking, gesture recognition, remote rendering
- Internet protocols; TCP/IP suite, TCP, UDP, IP, Ethernet, 802.3, network protocols, network software applications, packet switching, PDSN, data center network architecture
- Mobile wireless: 3G, LTE, CDMA, FDMA, TDMA, SMS, instant messaging (chat), mobile devices, smartphone, Android
- Web applications, AWS, Heroku, SaaS, HTTP, e-mail, SMTP, POP, IMAP, file transfer/FTP, client-server, cloud computing,
High-Performance Computing (HPC):
- Parallel and distributed computing, MPI, Multi-threading, POSIX threads, Windows multi-threading, cluster computing, ROCKS clusters
Patent portfolio evaluation
- Commercialization, portfolio review and infringement mining. Past patent work with Interdigital, Google, Nortel Networks, Stanford, and Carnegie Mellon University, among others.
- Patent infringement (ITC, IPR, federal courts, interference)
- Authoring expert witness reports to both technical and non-technical audiences
- Litigation support and technology education in patent disputes and patent reexaminations
- Analysis of software products, technologies, patents and patent portfolios, claim charts, and patentability research
Areas of Expertise
Smart TV, Smart Phone, Social Networks.
Istvan Jonyer, PhD in the Social NetworksLinkedIn
Dr. Jonyer has wide ranging experience in industry as a software development engineer at Nortel Networks, in academia as assistant professor of computer science at Oklahoma State University, in product management as head of Google TV device partnerships at Google, in venture capital as an investment professional at three different venture capital funds, and in entrepreneurship as a serial founder. As a researcher, he had an NSF and FTA-funded research program in machine learning. He has also advised the technology transfer lab at Stanford on patent commercialization.
Awards & Honors
Best Doctoral Dissertation Award, The University of Texas at Arlington, 2003
Best Paper Award, second place, Florida International Conference for Artificial Intelligence, 2003
Special issue on FLAIRS 2007: Machine learning, data mining and neural networks
June 2008, International Journal of Artificial Intelligence Tools, 17(3).
Guest editors: Zdravko Markov, Lawrence Holder, Istvan Jonyer, David Bisant
Hybrid Neurocomputing: Selected Papers from the 2nd International Conference on Hybrid Intelligent Systems (HIS 2002). Neurocomputing, Volume 61, October, 2004.
Edited by A. Abraham, I. Jonyer, E.I. Barakova, R. Jain, and L. Jain
I. Jonyer, "Graph Grammar Learning” in Mining Graph Data. L.B. Holder & D.J. Cook (editors). Wiley and Sons, 2006.
L.B. Holder, D.J. Cook, J. Gonzalez, and I. Jonyer, "Structural Pattern Recognition in Graphs," D. Chen and X. Cheng (Editors) Pattern Recognition and String Matching, Kluwer Academic Publishers, 2002.
I.J. Khor, J. Thomas, and I. Jonyer, "Sliding Window Protocol for Secure Group Communication in Ad-Hoc Networks". Journal of Universal Computer Science, Vol.11, No.1, pages 37-55. 2005.
I. Jonyer, L.B. Holder, and D.J. Cook “MDL-Based Context-Free Graph Grammar Induction and Applications". International Journal of Artificial Intelligence Tools, Volume 13, No. 1 pages 65-79, 2004.
D.J. Cook, L.B. Holder, S. Su, R. Maglothin, and I. Jonyer, “Structural Mining of Molecular Biology Data," IEEE Engineering in Medicine and Biology, Special Issue on Advances in Genomics, Volume 20, Number 4, pages 67-74, 2001.
I. Jonyer, L.B. Holder, and D.J. Cook, “Graph-Based Hierarchical Conceptual Clustering,” Journal of Machine Learning Research, Volume 2, pages 19-43, 2001.
I. Jonyer, L.B. Holder, and D.J. Cook, “Graph-Based Hierarchical Conceptual Clustering,” International Journal of Artificial Intelligence Tools, Volume 10, Number 1-2, pages 107-135, 2001.
M. Solano and I. Jonyer, “Performance Analysis of Evolutionary Search with a Dynamic Restart Policy,” Proceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, May 7-9, 2007, Key West, Florida, USA.
M. Solano, I. Jonyer, “Towards an optimal restart strategy for genetic programming.”
Proceedings of the Genetic and Evolutionary Computation Conference, July 7-11, 2007. London, England, UK.
I. Jonyer and A. Kikuchi, “Improving Modularity in Genetic Programming using Graph Based Data Mining,” Proceedings of the Nineteenth Annual Florida Artificial Intelligence Research Society, May 2006.
M. Cai, I. Jonyer, and M. Paprzycki, “Improving Parallelism in Structural Data Mining” Proceedings of the Sixth International Conference On Parallel Processing And Applied Mathematics, 2005.
I. Jonyer, P. Apiratikul, and J. Thomas, “Source Code Fingerprinting Using Graph Grammar Induction,” Proceedings of the Eighteenth Annual Florida Artificial Intelligence Research Society, May 2005.
J. Khor, J. Thomas, and I. Jonyer, "Sliding Window Protocol for Group Communication in Ad-Hoc Networks," Proceedings of the Hawaii International Conference on System Sciences, January, 2005.
I. Jonyer, L. B. Holder, and D. J. Cook, "Attribute-Value Selection Based on the Minimum Description Length," Proceedings of the International Conference on Artificial Intelligence, 2004.
A. Gilbert, J. Thomas, and I. Jonyer, "Modeling Work Flow in Hierarchically Clustered Distributed Systems", Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, 2004, Volume 3.
J. Thomas, T. Alam, and I. Jonyer, "Reducing Latency in Ad Hoc Networks by Pre-Fetching," Proceedings of the International Conference on Pervasive Computing and Communications, 2004.
I. Jonyer, L.B. Holder, and D.J. Cook, “MDL-Based Context-Free Graph Grammar Induction,” Proceedings of the Sixteenth Annual Florida Artificial Intelligence Research Society, 2003.
Best Paper Award, Second Place.
I. Jonyer, L.B. Holder, and D.J. Cook, “Concept Formation Using Graph Grammars,” Proceedings of the Knowledge Discovery in Databases Workshop on Multi-Relational Data Mining, pages 71-79, 2002.
J. Gonzalez, I. Jonyer, L.B. Holder, and D.J. Cook, “Efficient Mining of Graph-Based Data,” Proceedings of the American Association for Artificial Intelligence Workshop on Learning Statistical Models from Relational Data, pages 21-28, 2000.
I. Jonyer, L. B. Holder, and D. J. Cook, “Graph-Based Hierarchical Conceptual Clustering in Structural Databases,” Proceedings of the 7th Conference on Artificial Intelligence and of the 12th Conference on Innovative Applications of Artificial Intelligence, page 1073, 2000.
I. Jonyer, L. B. Holder, and D. J. Cook, “Graph-Based Hierarchical Conceptual Clustering,” Proceedings of the Thirteenth Annual Florida Artificial Intelligence Research Society, pages 91-95, 2000.
I. Jonyer, “Context-Free Graph Grammar Induction Using the Minimum Description Length Principle” Doctoral Dissertation. The University of Texas at Arlington. L.B. Holder, advisor. August, 2003.
I. Jonyer, “Hierarchical Conceptual Clustering Using a Graph-Based Knowledge Discovery System” Master's Thesis. The University of Texas at Arlington. L.B. Holder, advisor. May, 2000.
I. Jonyer, “Study of a Conversational Artificial Intelligence System” Undergraduate Honors Thesis. The University of Texas at Arlington. L.B. Holder, advisor. May, 1999.
FLAIRS 2007: Machine learning, data mining and neural networks - Preface
International Journal of Artificial Intelligence Tools, Volume 17(3), pages 411-414. June 2008.
Z. Markov, L.B. Holder, I. Jonyer, and D. Bisant
Special issue on hybrid neurocomputing - Preface
Neurocomputing. Volume 61, pages 1-3, October, 2004.
A. Abraham, E. I. Barakova, R. Jain, I. Jonyer, and L. Jain
I. Jonyer, J. Kukluk, I. Blader, M. Cai, L. Holder, D. Cook, and I. Blader, “Learning Motifs in Biological Structures Using Node Replacement Graph Grammars,” Technical Report, Oklahoma State University, 2007.
I. Jonyer and N. Samuel “Software Similarity Detection Using Grammatical Fingerprints,” Technical Report, Oklahoma State University, 2006.
I. Jonyer and M. Solano, “Towards a Globally Optimal Restart Policy for Evolutionary Search,” Technical Report, Oklahoma State University, 2006.
I. Jonyer, “Want to start a company? Work on an internal product at BigCo.” February 6, 2017. https://www.linkedin.com/pulse/want-start-company-work-internal-product-bigco-istvan-jonyer-ph-d-/
I. Jonyer, “Are you expected to write perfect code on your first attempt in tech interviews?” January 25, 2016. https://www.linkedin.com/pulse/software-engineering-job-interview-istvan-jonyer/
I. Jonyer, “The Fable of the Faster Horse” November 12, 2015. https://www.linkedin.com/pulse/fable-faster-horse-istvan-jonyer/
I. Jonyer, P. Dupont, T. Oates, and M. Sebban. Workshop on Challenges and Applications of Grammar Induction, in conjunction with the International Conference on Machine Learning, Corvallis, Oregon, June 20-24, 2007.
I. Jonyer, D. Bisant. Data Mining Special Track, 21st International Florida Artificial Intelligence Research Society Conference, May 15-17, 2008, Coconut Grove, Florida, USA.
I. Jonyer, D. Bisant. Data Mining Special Track, 20th International Florida Artificial Intelligence Research Society Conference, May 7-9, 2007, Key West, Florida, USA.
Expert Reviewer of Grant Applications and Scientific Publications
National Science Foundation, Multiple programs. 2005 - 2007.
IEEE Transactions on Knowledge and Data Engineering, 2007.
ACM Symposium on Applied Computing, 2007.
International Conference on Machine Learning and Applications, 2006.
IEEE International Conference on Computer and Information Technology, 2006.
First International Workshop on Semantic Web Applications, 2006.
International Journal on Artificial Intelligence Tools, 2006, 2007.
National Science Foundation, Biology directorate, 2005.
Machine Learning Journal, 2005.
European Conference on Genetic Programming, 2005.
The Florida Artificial Intelligence Research Society Conference, 2002-2007.
Americas Conference on Information Systems, 2005.
International Conference on Information Technology: Coding and Computing, 2004.
Journal of Information and Knowledge Management, 2004.
Special Issue of International Journal of Pattern Recognition and Artificial Intelligence, 2003.
Pattern Recognition and String Matching. Dechang Chen and Xiuzhen Cheng editors. Kluwer Publishing, 2002.
Ph.D., Computer Science And Engineering, Dissertation In Machine Learning, The University Of Texas At Arlington
MBA, Carnegie Mellon University, Tepper School Of Business