Dr. Panos Patros , CPEng

Contact Details

Email: panos.patros@waikato.ac.nz
Room: G.1.11
Phone: +64 7 838 4651
Extension: 4651

About Panos

Panos is a Chartered Professional Engineer (CPEng) in Information Engineering (Software Engineering, Telecommunications Engineering and Electronics Engineering). He is interested in Self-Adaptation in Clouds, Language Runtimes and Embedded Systems, focusing on the Testing and Satisfaction of Nonfunctional Requirements as well as Systems' Security. He joined the the University of Waikato in July 2018; soon after, he started the Oceania Researchers in Cloud and Adaptive-systems (ORCA) lab. Additionally, he is serving as an Adjunct Professor in the Faculty of Computer Science at the University of New Brunswick in Canada.

Panos is a key researcher in the $12.5M Ahuora project 2020-2026. Ahuora aims to decarbonize the process heat sector of New Zealand, via Adaptive Digital Twin technology. The project comprises a sizable Software component: we'll be needing many Software Engineers over the following years. Take NCEA Calculus Level 3 and study Software Engineering!

Panos received his Bachelors in Informatics and Telecommunications from the University of Athens in 2010. He worked for four years as a Software Engineer, Consultant and Academic Tutor before moving to Canada and the University of New Brunswick for graduate school. He completed his Master's in Computer Science in 2014 and his PhD in 2018, both as a member of the IBM/UNB Centre of Advanced Studies - Atlantic. While in Canada, he taught CS courses (after completing a Diploma in University Teaching in 2014) and participated in industrial R&D projects.

For his BSc thesis, Panos constructed a converter of Conjunctive Grammars (Context-Free plus Intersection) to their respective automata and vice-versa. For his master's thesis, he enhanced the IBM J9 JVM with a tool that measured thread-park contention in the Java Util Concurrent library. For his PhD thesis, he explored numerous performance, modelling and resource allocation issues in the intersection of platform clouds and language runtimes, in a work that also resulted into two patents and four defensive anti-patent disclosures. He is also a member of the Verilog-To-Routing FPGA CAD tool open source community, where he contributes and conducts research related to improved synthesis of circuits for embedded systems.

Twitter

Google Scholar

LinkedIn

Engineering New Zealand

ORCID iD 0000-0002-1366-9411

About ORCA

The Oceania Researchers in Cloud and Adaptive-systems (ORCA) [also known as Ohu Rangahau Kapua Aunoa in Te Reo Māori] lab was founded in January 2019. Its mission is to facilitate excellent research in the fields of Self-Adaptive and Self-Organizing software systems focusing on Cloud, Language Runtime and Embedded Systems.

Self-Adaptive Software is an exciting new field merging ideas from traditional Software Engineering and Computer Systems, with Artificial Intelligence (AI), Machine Learning (ML), Control Theory, Data-Driven Control, Game Theory, etc. Its goal is to enable applications to satisfy dynamically changing requirements in a dynamically changing environment.

The ORCA lab comprises multiple Waikato research students and involves Waikato, New Zealand and International Academics. It maintains active international collaborations with researchers from the UNB/IBM Centre of Advance Studies-Atlantic at the University of New Brunswick, Canada; the Chair of Computer Architecture and Parallel Systems at the Technical University of Munich, Germany; and ASRC Federal in the United States.

To date, the ORCA lab has contributed in the following funded projects:

• STRATUS
• Huri Whakatau
• Optimizing Node.js for the Cloud (IBM, Red Hat and UNB Canada)
• Self-learning EBike (Nerra Drive Systems & Callaghan)
• Ahuora

Current Research Students

Graduated Research Students

Research Students' Theses Supervised

1. Burroughs, S. (2021). Towards predictive runtime modelling of Kubernetes microservices (Thesis, Master of Science (Research) (MSc(Research))). The University of Waikato, Hamilton, New Zealand. Retrieved from https://hdl.handle.net/10289/14091
2. van Zijl, M. (2020). Model checking for cloud autoscaling using WATERS (Thesis, Master of Science (Research) (MSc(Research))). The University of Waikato, Hamilton, New Zealand. Retrieved from https://hdl.handle.net/10289/13602
3. McCarthy, H. G. A. (2020). Control-theoretical stress-testing for cross-platform compliance (Thesis, Master of Science (Research) (MSc(Research))). The University of Waikato, Hamilton, New Zealand. Retrieved from https://hdl.handle.net/10289/13687
4. Bradley, N. C. (2020). Hokohoko: A comprehensive framework for evaluating artificial intelligence-based and statistical techniques for foreign exchange speculation (Thesis, Master of Science (Research) (MSc(Research))). The University of Waikato, Hamilton, New Zealand. Retrieved from https://hdl.handle.net/10289/13752

Research Interests

• Self-Adaptive and Self-Organizing Systems
• Cloud Computing
• Language Runtimes and Embedded Systems
• Performance Engineering

Awards

• 2018, John DeDourek Award for Best CS Graduate Thesis
• 2018, Excellence in Teaching Award, Faculty of Computer Science, University of New Brunswick
• 2016, IBM CAS Project of the Year (Lead Student), IBM Canada
• 2014-2018, IBM PhD CAS Fellowship, IBM/UNB Centre of Advanced Studies - Atlantic

Perspective Students

I am always on the lookout for star research students with strong mathematical and computer/software systems skills. Academic publications and/or relevant industrial expertise will be highly appreciated. The University of Waikato offers competitive PhD and Master's Scholarship to the best applicants; contact me if you think you are a fit!

I occasionally take in strong undergraduate interns; however, I cannot provide any relevant funding.

Interested High School Students

So, you want a career in Software Engineering? Great choice! Ensure you complete Level 3 Calculus! I recommend you score Excellent or Merit in the following NZ NCEA subjects:

It'd be great, however, to also gain a broader comprehensive knowledge. Remember that Engineering is for the people and you need to be able to empathize and discover problems. Consider earning at least a Merit in the following NZ NCEA subjects:

Memberships

• Engineering New Zealand, MEngNZ
• IT Engineers NZ, Secretary of Steering Committee
• Software Innovation New Zealand
• ACM
• IEEE
• Cybersecurity Researchers of Waikato (CROW)
• STRATUS

Past Teaching (University of Waikato)

• COMPX529-20B, Engineering Self-Adaptive Systems
• COMPX304-20B, Advanced Networking and Cyber Security
• COMPX341-20A, Software Engineering Methodology
• COMPX529-19B, Engineering Self-Adaptive Systems
• COMPX304-19B, Advanced Networking and Cyber Security
• COMPX341-19A, Software Engineering Methodology
• COMP301-18B, Operating Systems
• COMP314-18B, Software Engineering Project

Past Teaching (University of New Brunswick)

• Winter 2018, CS1073, Introduction to Computer Programming (in Java)
• Fall 2017, CS1083, Introduction to Computer Programming || (in Java)
• Winter 2016, CS2333, Computability and Formal Languages
• Fall 2015, CS1073, Introduction to Computer Programming (in Java)
• Fall 2014, CS4735, Computer Graphics

Past Funded Research Openings

• STRATUS PhD Scholarship on Guaranteeing Self-Organized Backup Systems: $25K/p.a. and tuition fees for three years.
• STRATUS PhD Scholarship on Cloud Interference Security: $24K/p.a. and tuition fees for three years
• 2018 Summer Research Scholarship $6K. C/C++, OS, SWE skills needed

Research Service

• 2018, Program Committee, 29th International Symposium on RSP@ESWeek
• 2018-now, International Journal of Cloud Computing (Inderscience)
• 2017, Program Committee, 28th International Symposium on RSP@ESWeek
• 2017, Session Chair, 28th International Symposium on RSP@ESWeek
• 2016, Program Committee, 27th International Symposium on RSP@ESWeek

Teaching Commitments

Recent Publications

• Rodrigues, M., Mayo, M., & Patros, P. (2022). OctopusNet: Machine learning for intelligent management of surgical tools. Smart Health, 23, 100244. doi:10.1016/j.smhl.2021.100244

• Rodrigues, M., Mayo, M., & Patros, P. (2021). Interpretable deep learning for surgical tool management. In M. Reyes, P. Henriques Abreu, J. Cardoso, M. Hajij, G. Zamzmi, P. Rahul, & L. Thakur (Eds.), Proc 4th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC 2021) LNCS 12929 (pp. 3-12). Cham: Springer. doi:10.1007/978-3-030-87444-5_1 Open Access version: https://hdl.handle.net/10289/14577

• Phua, T. W., Patros, P., & Kumar, V. (2021). Towards embedding data provenance in files. In R. Paul (Ed.), Proc 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (pp. 1319-1325). USA, Virtual: IEEE. doi:10.1109/CCWC51732.2021.9375947 Open Access version: https://hdl.handle.net/10289/14235

• Patros, P., Spillner, J., Papadopoulos, A. V., Varghese, B., Rana, O., Dustdar, S., & Dustdar, S. (2021). Toward sustainable serverless computing. IEEE Internet Computing, 25(6), 42-50. doi:10.1109/mic.2021.3093105

Find more research publications by Panos Patros