Andriy Miranskyy
Associate Professor
Department of Computer Science
Toronto Metropolitan University
Announcements
I am currently taking on undergraduate and graduate students with interests or expertise in my research areas. If you would like to work with me, please drop me a line.
I receive many applications and inquiries about open positions. While I review everything submitted, I regret that I am only able to respond if there is a suitable match.
Research Interests
My primary research interest lies in quantifying and mitigating risks in Software Engineering, with a particular focus on large-scale software systems. This includes Cloud computing systems, quantum computing systems, and systems that process and analyze Big Data. Examples of risks include:
- Improperly tested large databases for Big Data, leading to defect escapes and unplanned outages;
- Non-scalable algorithms, where identifying the root cause of system failures is too slow to prevent prolonged outages and customer dissatisfaction;
- Incorrect implementation of quantum algorithms, causing subtle inaccuracies in results that remain undetected until they critically impact dependent systems or workflows;
- Requirements creeping in late during development cycles, leading to budget overruns and schedule delays;
- A surge in defects rediscovered by clients, overwhelming support and maintenance teams.
Our work utilizes a diverse set of tools, including data mining, machine learning (such as deep learning), simulation, information theory, blockchain, quantum computing, high-performance computing, and cloud computing. These technologies enable precise identification and effective mitigation of Software Engineering-related risks.
Supporters
My work was made possible through the generous support of funding agencies, including the Alliance, NSERC, MITACS, and OCI, as well as industrial partners such as Environics Analytics, eSentire, IBM, Laipac, and Palomino.
Selected Awards
- Rogers Cybersecure Catalyst Fellow, 2023-2024
- IBM Centre for Advanced Studies (CAS) Best Project of the Year, 2021
- IBM CAS Project Honorable Mention, 2020
- ACM/IEEE International Conference on Software Engineering (ICSE), New Ideas and Emerging Results Distinguished Paper Award, 2020
- Dean's Scholarly, Research and Creative Activity Awards, 2017
- IBM CAS Faculty Fellow, 2014-current
- Winner of the IBM Canada Big Data Tech Challenge, 2013
- Guinness World Record: the largest data warehouse containing 3Pb of raw data (IBM DB2 VLDB team member), 2012
Group
Current Members
- Montgomery Gole, MSc student
- Mohammad Saiful Islam, PhD student
- William Pourmajidi, PhD student
- Mohamed Sami Rakha, Postdoctoral fellow
- Janakan Siva, BEng student
- Adam Sorrenti, MSc student
- Viral Thakar, MSc student
- Catherine Xia, MSc student
- Lei Zhang, Assistant Professor, University of Maryland, Baltimore County
Alumni
Click to expand
MSc Students
- Muad Abu-Ata, MSc (DS), Principal Data Scientist at Ingram Micro
- Zainab Al-zanbouri, MSc (CS), Professor at Sheridan College
- Janusan Baskararajah, MSc (CS), Software Developer at NAVBLUE, an Airbus Company
- Mayy Habayeb, MEng (MIE), Professor at Centennial College
- Kristie House-Senapati, MSc (DS), Senior Analyst at Ally Financial
- Mohammad Saiful Islam, MSc (CS), PhD student at TMU
- Mushahid Khan, MSc (CS), PhD student at UBC
- Jorge Lopez, MSc (CS), PhD student at TMU
- Sravya Polisetty, MSc (CS), Data Scientist II at Verisk
- William Pourmajidi, MSc (CS), PhD student at TMU
- Mefta Sadat, MSc (CS), Staff Software Engineer at Loblaw Digital
- Ali Senejani, MSc (DS), Data Scientist at Corus Entertainment
- Sarah Sohana, MSc (CS), Developer Analyst at Rogers Communications
- Iwona Sokalska, MSc (DS), PhD student at TMU
- Sokratis Tsakiltsidis, MSc (CS), Manager Ad-Tech & Data Engineering at Pelmorex
PhD Students
- Sedef Akinli Kocak, PhD (ENSCIMAN), Director at Vector Institute
- Sheik Mamun, Graduate Studies, Senior Data Architect at AWS
Postdoctoral Fellows
- Williams P. Nwadiugwu, Assistant Professor at Laurentian University
- Lei Zhang, Assistant Professor at the University of Maryland, Baltimore County
Undergraduate Students
- Amar Gupta, BSc (CS), Software Engineer R&D at Huawei Canada
- Jared Rand, BSc (CS), Senior Software Engineer at STRIVR
Selected Publications
You can find publications co-authored by me on Google Scholar. Below are selected examples showcasing my current research interests and collaborative efforts.
Click to expand
Quantum Computing and Software Engineering
Software Engineering for Quantum Computing
- Challenges of Quantum Software Engineering for the Next Decade: The Road Ahead
ACM Transactions on Software Engineering and Methodology (TOSEM), 2025 (to appear) - Identifying Flakiness in Quantum Programs
International Symposium on Empirical Software Engineering and Measurement (ESEM), 2023 - Is Your Quantum Program Bug-Free?
International Conference on Software Engineering (ICSE), 2020
New Ideas and Emerging Results Distinguished Paper Award - On Testing Quantum Programs
International Conference on Software Engineering (ICSE), 2019
Quantum Computing for Software Engineering
- Using Quantum Computers to Speed Up Dynamic Testing of Software
International Workshop on Quantum Programming for Software Engineering (QP4SE), 2022 - Quantum Computing for Software Engineering: Prospects
International Workshop on Quantum Programming for Software Engineering (QP4SE), 2022
Crypto-agility
- Making existing software quantum safe: A case study on IBM Db2
Information and Software Technology (IST), 2023 - Quantum Advantage and Y2K Bug: Comparison
IEEE Software, 2021
Quantum Algorithms
- Comparing Algorithms for Loading Classical Datasets into Quantum Memory
International Workshop on Quantum Software Engineering and Technology, 2024 - EP-PQM: Efficient Parametric Probabilistic Quantum Memory with Fewer Qubits and Gates
IEEE Transactions on Quantum Engineering, 2022
Cloud Governance and Observability; Blockchain
- A Reference Architecture for Observability and Compliance of Cloud Native Applications
2023 - Anomaly Detection in a Large-scale Cloud Platform
International Conference on Software Engineering (ICSE), 2021 - On Automatic Parsing of Log Records
International Conference on Software Engineering (ICSE), 2021 - Anomaly Detection in Cloud Components
IEEE International Conference on Cloud Computing (CLOUD), 2020
Blockchain and Smart Contracts
- Immutable Log Storage as a Service on Private and Public Blockchains
IEEE Transactions on Services Computing (TSC), 2021 - Immutable Log Storage as a Service
International Conference on Software Engineering (ICSE), 2019 - Logchain: Blockchain-assisted Log Storage
IEEE International Conference on Cloud Computing (CLOUD), 2018
Big Data and Software Engineering
- Online and Offline Analysis of Streaming Data
International Conference On Software Architecture (ICSA), 2018 - Architecture for Analysis of Streaming Data
IEEE International Conference on Cloud Engineering (IC2E), 2018 - Operational-Log Analysis for Big Data Systems: Challenges and Solutions
IEEE Software, 2016 - Big Picture of Big Data Software Engineering
International Workshop on Big Data Software Engineering (BIGDSE), 2015
Knowledge Extraction
- Automated data validation: an industrial experience report
Journal of Systems and Software (JSS), 2023 - Term Interrelations and Trends in Software Engineering
Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2021
Defect Prediction, Mining Software Repositories, Testing and Maintenance
- On Usefulness of the Deep-Learning-Based Bug Localization Models to Practitioners
International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE), 2019 - On the Use of Hidden Markov Model to Predict the Time to Fix Bugs
IEEE Transactions on Software Engineering (TSE), 2018 - Building Usage Profiles Using Deep Neural Nets
International Conference on Software Engineering (ICSE), 2017 - Rediscovery Datasets: Connecting Duplicate Reports
International Conference on Mining Software Repositories (MSR), 2017 - Merits of Organizational Metrics in Defect Prediction: An Industrial Replication
International Conference on Software Engineering (ICSE), 2015
Teaching
Courses that I taught at TMU over the years:
- CPS109 - Computer Science I
- CPS406 - Introduction to Software Engineering
- CPS731 - Software Engineering I
- CPS847 - Software Tools for Startups
- CPS888 - Software Engineering
- CPS840/CP8207/CP8316 - Introduction to Quantum Computing and Quantum Software Engineering
- CP8102 & CP9102 - Computer Science Seminar
- CP8302 - Software Metrics
- DS8001 - Designs of Algorithms and Programming for Massive Data