Marco Paolieri

Senior Research Associate
Department of Electrical and Computer Engineering
University of Southern California

Homepage: https://qed.usc.edu/paolieri

Email: paolieri@usc.edu

Telephone: +1 (213) 740-2579

Office: Powell Hall (PHE) in Room #536, or Ronald Tutor Hall (RTH) in Room #316, or Ginsburg Hall (GCS) in shared spaces

Address: 3710 McClintock Ave, Los Angeles, CA 90089-0781, USA

Connect: LinkedIn

• June 2026: I will be General Co-Chair of DSN 2027 in Berlin!
• May 2026: I attended the Dagstuhl Seminar on Emerging Technologies for Performance and Dependability Assessment
• Oct. 2025: New paper at MASCOTS 2025 (Analytical Characterization and Efficient Simulation of Batched Arrivals in the Kafka Broker)
• Sep. 2025: New paper on IEEE Transactions on Parallel and Distributed Systems (Compositional coordinated resource provisioning in workflows with stochastic durations)
• Mar. 2025: New paper on Performance Evaluation journal (Approximation of cumulative distribution functions by Bernstein phase-type distributions)
• Oct. 2024: New paper on IEEE Transactions on Biomedical Engineering (Estimating Ground Reaction Forces from Inertial Sensors)
• Sep. 2024: Best paper award at QEST 2024 (Approximation of cumulative distribution functions by Bernstein phase-type distributions)
• Aug. 2024: New paper on Performance Evaluation journal (Inference latency prediction for CNNs on heterogeneous mobile devices and ML frameworks)
• Jun. 2024: Best presented paper award at EPEW 2024 (Approximation of first passage time distributions of compositions of independent Markov chains)
• Apr. 2024: I received the 2024 Viterbi Teaching Award for part-time faculty! (details)
• Sep. 2023: Best paper award at QEST 2023 (Equilibrium analysis of Markov regenerative processes)

Research

I completed my PhD in Computer Engineering at the University of Florence, Italy (2015).
From August 2016 to November 2018, I was a postdoc at USC in the Quantitative Evaluation and Design Group.
Since December 2018, I am a Senior Research Associate at USC.

My research focuses on:

• Stochastic models for performance and reliability evaluation;
• Solution techniques for non-Markovian processes;
• Systems modeling (to improve performance and reliability), including
  • AI systems (e.g., mobile and edge AI, distributed training, agentic AI),
  • cloud systems (e.g., hybrid clouds and task offloading),
  • networks (e.g., satellite networks, transportation networks, water/gas/power distribution).

Teaching

• In Fall 2026, I am teaching the class "Introduction to Computer Programming for Electrical Engineers" (EE 155) in the Electrical and Computer Engineering department.
  This class introduces students to C/C++ programming, algorithm analysis, elementary data structures. Check the class website for up-to-date information and office hours.
• During 2019-2026 (15 Spring/Fall semesters), I have taught the class "Computer Systems" (CSCI 356) in the Computer Science department
  (featuring x86 and ARM assembly, buffer overflow attacks, out-of-order CPU architectures with static/dynamic scheduling, caches, virtual memory, heap management).

Software Tools

I am a main developer of the ORIS Tool (featured on Transactions on Software Engineering). The tool allows:

• State space analysis of time Petri nets using DBM zones;
• Transient analysis of stochastic time Petri nets (STPNs) with generally-distributed timers (and underlying GSMP process);
• Regenerative transient analysis of STPNs (symbolic integration over DBM zones and numerical solution of integral equations).

Professional Activities

I served as reviewer, PC member and chair of conferences in the area of performance, reliability, and quantitative system analysis.

• QEST (International Conference on Quantitative Analysis of Systems): PC chair (2022), PC member (2019, 2020, 2021, 2023, 2024, 2025), publicity chair (2014, 2021, 2025), publications chair (2014), tools chair (2017), external reviewer (2014, 2015, 2016, 2017).
• DSN (IEEE International Conference on Dependable Systems and Networks): general co-chair (2027)
• ISSRE (IEEE International Symposium on Software Reliability Engineering): PC member (2015, 2023, 2024, 2025), publicity chair (2020, 2023, 2025).
• EPEW (European Workshop on Performance Engineering): PC chair (2016), PC member (2015, 2017, 2018, 2019, 2024, 2025, 2026).
• RTAS (IEEE Real-Time and Embedded Technology and Applications Symposium): PC member (2025), publicity chair (2025).
• VALUETOOLS (International Conference on Performance Evaluation Methodologies and Tools): PC chair (2023), PC member (2024, 2025, 2026), publicity chair (2015), external reviewer (2013, 2014, 2015).
• ICPE (International Conference on Performance Engineering): publicity chair (2024), tools and demonstrations chair (2018).
• SIGMETRICS: publicity chair (2018, 2024).
• IFIP Performance: publicity chair (2020, 2021), external reviewer (2016).
• ASMTA (International Conference on Analytical and Statistical Modelling Techniques and Applications): publicity chair (2024).
• MASCOTS (Modeling, Analysis and Simulation of Computer and Telecommunication Systems): external reviewer (2016, 2017).
• FORMATS (International conference on Formal Modeling and Analysis of Timed Systems): external reviewer (2013, 2015, 2016).

I have been a reviewer for Performance Evaluation, ACM ToMPECS, Journal of Systems and Software, Reliability Engineering & System Safety, Journal of Internet Services and Applications.

Publications

• L. Carnevali, A. Horváth, M. Paolieri, E. Vicario, Differentiable fit of empirical distributions by Bernstein phase types, Proceedings of EPEW 2026, pp. 115-130, Springer, 20262026
  Stochastic ProcessesPerformance ModelsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• Z. Li, M. Paolieri, L. Golubchik, Accelerating mobile inference through fine-grained CPU-GPU co-execution, Selected papers of EPEW 2025, pp. 41-55, Springer, 20262026
  Performance ModelsML SystemsEdge AIApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• B. Picano, M. Paolieri, L. Carnevali, E. Vicario, Joint offloading and service selection via matching and auction theory for multi-task dependent computation-intensive applications, Perform. Evaluation, 172:102556:1-102556:16, 20262026
  Performance ModelsGame TheoryStochastic WorkflowsEdge AITheory
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• Z. Li, M. Paolieri, L. Golubchik, A study on inference latency for vision transformers on mobile devices, Proceedings of VALUETOOLS 2024, pp. 229-251, Springer, 20262026
  Performance ModelsML SystemsMobile AIApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• A. Horváth, M. Paolieri, E. Vicario, Approximation of first passage time distributions of compositions of independent Markov chains, Selected papers of EPEW 2024, pp. 75-90, Springer, 20252025
  Stochastic ProcessesTheory🏆 Best Paper
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• A. Horváth, M. Paolieri, B. Picano, E. Vicario, Analytical characterization and efficient simulation of batched arrivals in the Kafka broker, Proceedings of MASCOTS, pp. 1-8, IEEE Computer Society, 20252025
  Stochastic ProcessesPerformance ModelsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• A. Horváth, I. Horváth, M. Paolieri, M. Telek, E. Vicario, Approximation of cumulative distribution functions by Bernstein phase-type distributions, Perform. Evaluation, 168:102480:1-102480:24, 20252025
  Stochastic ProcessesTheory
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• B. Song, M. Paolieri, H. Stewart, L. Golubchik, J. L. McNitt-Gray, V. Misra, D. Shah, Estimating ground reaction forces from inertial sensors, IEEE Trans. Biomed. Eng., 72(2):595-608, 20252025
  AI HealthcareApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, R. Reali, L. Scommegna, E. Vicario, Cost-effective software rejuvenation combining time-based and inspection-based policies, IEEE Trans. Emerg. Top. Comput., 13(2):354-369, 20252025
  Stochastic ProcessesReliability ModelsSoftware RejuvenationApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• E. Ábrahám, M. Paolieri, Introduction to the special issue on QEST 2022, part 2, ACM Trans. Model. Comput. Simul., 35(2):9:1-9:2, 20252025
  Editor
  (copy bib | save bib | go to publisher)
  
• L. Carnevali, M. Paolieri, R. Reali, L. Scommegna, E. Vicario, Compositional coordinated resource provisioning in workflows with stochastic durations, IEEE Trans. Parallel Distributed Syst., 36(9):1937-1954, 20252025
  Stochastic ProcessesPerformance ModelsStochastic WorkflowsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• Z. Li, M. Paolieri, L. Golubchik, A benchmark for ML inference latency on mobile devices, Proceedings of EdgeSys, pp. 31-36, ACM, 20242024
  Performance ModelsML SystemsEdge AIApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• Z. Li, M. Paolieri, L. Golubchik, Inference latency prediction for CNNs on heterogeneous mobile devices and ML frameworks, Perform. Evaluation, 165:102429:1-102429:26, 20242024
  Performance ModelsML SystemsEdge AIApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• A. Horváth, I. Horváth, M. Paolieri, M. Telek, E. Vicario, Approximation of cumulative distribution functions by Bernstein phase-type distributions, Proceedings of QEST+FORMATS, pp. 90-106, Springer, 20242024
  Stochastic ProcessesTheory🏆 Best Paper
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• E. Ábrahám, M. Paolieri, Introduction to the special issue on QEST 2022, part 1, ACM Trans. Model. Comput. Simul., 34(3):16:1-16:1, 20242024
  Editor
  (copy bib | save bib | go to publisher)
  
• E. Kalyvianaki, M. Paolieri, Proceedings of VALUETOOLS 2023, Lecture notes of the institute for computer sciences, social informatics and telecommunications engineering, vol. 539, Springer, 20242024
  Editor
  (copy bib | save bib | go to publisher)
  
• L. Carnevali, M. Paolieri, R. Reali, L. Scommegna, F. Tammaro, E. Vicario, Using the ORIS tool and the SIRIO library for model-driven engineering of quantitative analytics, Proceedings of EPEW 2022, pp. 200-215, Springer, 20232023
  Stochastic ProcessesTools
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, B. Picano, R. Reali, L. Scommegna, E. Vicario, A quantitative approach to coordinated scaling of resources in complex cloud computing workflows, Proceedings of EPEW, pp. 309-324, Springer, 20232023
  Stochastic ProcessesPerformance ModelsStochastic WorkflowsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• Z. Li, M. Paolieri, L. Golubchik, Predicting inference latency of neural architectures on mobile devices, Proceedings of ICPE, pp. 99-112, ACM, 20232023
  Performance ModelsML SystemsEdge AIApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• A. Horváth, M. Paolieri, E. Vicario, Equilibrium analysis of Markov regenerative processes, Proceedings of QEST, pp. 172-187, Springer, 20232023
  Stochastic ProcessesTheory🏆 Best Paper
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, R. Reali, E. Vicario, Compositional safe approximation of response time probability density function of complex workflows, ACM Trans. Model. Comput. Simul., 33(4):16:1-16:26, 20232023
  Stochastic ProcessesPerformance ModelsStochastic WorkflowsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• B. Song, M. Paolieri, L. Golubchik, Performance and revenue analysis of hybrid cloud federations with QoS requirements, Proceedings of IEEE CLOUD, pp. 321-330, IEEE, 20222022
  Stochastic ProcessesPerformance ModelsCloud SystemsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, E. Vicario, The ORIS tool: App, library, and toolkit for quantitative evaluation of non-Markovian systems, SIGMETRICS Perform. Eval. Rev., 49(4):81-86, 20222022
  Stochastic ProcessesTools
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• Y. Yao, M. Paolieri, L. Golubchik, Sojourn time minimization of successful jobs, SIGMETRICS Perform. Eval. Rev., 50(2):24-26, 20222022
  Stochastic ProcessesTheory
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• E. Ábrahám, M. Paolieri, Proceedings of QEST, Lecture notes in computer science, vol. 13479, Springer, 20222022
  Editor
  (copy bib | save bib | go to publisher)
  
• C. Chen, S. Babakniya, M. Paolieri, L. Golubchik, Defending against poisoning backdoor attacks on federated meta-learning, ACM Trans. Intell. Syst. Technol., 13(5):76:1-76:25, 20222022
  AI SafetyApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• Z. Li, M. Paolieri, L. Golubchik, S. Lin, W. Yan, Predicting throughput of distributed stochastic gradient descent, IEEE Trans. Parallel Distributed Syst., 33(11):2900-2912, 20222022
  Performance ModelsML SystemsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, R. Reali, L. Scommegna, E. Vicario, A Markov regenerative model of software rejuvenation beyond the enabling restriction, Proceedings of IEEE ISSRE workshops (WOSAR), pp. 138-145, IEEE, 20222022
  Stochastic ProcessesReliability ModelsSoftware RejuvenationApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, R. Reali, E. Vicario, Compositional safe approximation of response time distribution of complex workflows, Proceedings of QEST, pp. 83-104, Springer, 20212021
  Stochastic ProcessesPerformance ModelsStochastic WorkflowsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• S. Dey, S. Babakniya, S. C. Kanala, M. Paolieri, L. Golubchik, P. A. Beerel, K. M. Chugg, Deep-n-cheap: An automated efficient and extensible search framework for cost-effective deep learning, SN Comput. Sci., 2(4):265:1-265:15, 20212021
  Performance ModelsML SystemsEdge AIApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• M. Paolieri, M. Biagi, L. Carnevali, E. Vicario, The ORIS tool: Quantitative evaluation of non-Markovian systems, IEEE Trans. Software Eng., 47(6):1211-1225, 20212021
  Stochastic ProcessesTools
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• Z. Li, W. Yan, M. Paolieri, L. Golubchik, Throughput prediction of asynchronous SGD in TensorFlow, Proceedings of ICPE, pp. 76-87, ACM, 20202020
  Performance ModelsML SystemsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• M. French, M. Paolieri, V. V. Menon, A. G. Schmidt, Emulating and verifying sensing, computation, and communication in distributed remote sensing systems, Proceedings of IEEE IGARSS, pp. 3849-3852, IEEE, 20202020
  SpaceTools
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• A. G. Schmidt, V. Venugopalan, M. Paolieri, M. French, Constellations in the cloud: Virtualizing remote sensing systems, Proceedings of IEEE IGARSS, pp. 5351-5354, IEEE, 20192019
  SpaceTools
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• M. Biagi, L. Carnevali, M. Paolieri, F. Patara, E. Vicario, A continuous-time model-based approach for activity recognition in pervasive environments, IEEE Trans. Hum. Mach. Syst., 49(4):293-303, 20192019
  Stochastic ProcessesAmbient Assisted LivingApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• S. Lin, M. Paolieri, C. Chou, L. Golubchik, A model-based approach to streamlining distributed training for asynchronous SGD, Proceedings of MASCOTS, pp. 306-318, IEEE Computer Society, 20182018
  Performance ModelsML SystemsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• S. Lin, R. Pal, M. Paolieri, L. Golubchik, Performance driven resource sharing markets for the small cloud, Proceedings of ICDCS, pp. 241-251, IEEE Computer Society, 20172017
  Stochastic ProcessesPerformance ModelsCloud SystemsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• M. Biagi, L. Carnevali, M. Paolieri, T. Papini, E. Vicario, Exploiting non-deterministic analysis in the integration of transient solution techniques for Markov regenerative processes, Proceedings of QEST, pp. 20-35, Springer, 20172017
  Stochastic ProcessesTheory
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• M. Paolieri, S. Sankaranarayanan, E. Vicario, Guest editorial: Special issue on formal modeling and analysis of timed systems, Real Time Syst., 53(3):289-290, 20172017
  Editor
  (copy bib | save bib | go to publisher)
  
• M. Biagi, L. Carnevali, M. Paolieri, E. Vicario, Performability evaluation of the ERTMS/ETCS - level 3, Transportation Research Part C: Emerging Technologies, 82:314-336, 20172017
  Stochastic ProcessesReliability ModelsCritical InfrastructuresApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• M. Biagi, L. Carnevali, E. Vicario, M. Paolieri, An introduction to the ORIS tool, Proceedings of VALUETOOLS, pp. 9-11, ACM, 20172017
  Stochastic ProcessesTools
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• M. Biagi, L. Carnevali, M. Paolieri, F. Patara, E. Vicario, A stochastic model-based approach to online event prediction and response scheduling, Proceedings of EPEW, pp. 32-47, Springer, 20162016
  Stochastic ProcessesAmbient Assisted LivingApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• D. Fiems, M. Paolieri, A. N. Platis, Proceedings of EPEW, Lecture notes in computer science, vol. 9951, Springer, 20162016
  Editor
  (copy bib | save bib | go to publisher)
  
• S. Martina, M. Paolieri, T. Papini, E. Vicario, Performance evaluation of Fischer’s protocol through steady-state analysis of Markov regenerative processes, Proceedings of MASCOTS, pp. 355-360, IEEE Computer Society, 20162016
  Stochastic ProcessesPerformance ModelsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• M. Paolieri, A. Horváth, E. Vicario, Probabilistic model checking of regenerative concurrent systems, IEEE Trans. Software Eng., 42(2):153-169, 20162016
  Stochastic ProcessesModel CheckingTheory
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, F. Flammini, M. Paolieri, E. Vicario, Non-Markovian performability evaluation of ERTMS/ETCS level 3, Proceedings of EPEW, pp. 47-62, Springer, 20152015
  Stochastic ProcessesReliability ModelsCritical InfrastructuresApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• A. Avritzer, L. Carnevali, L. Happe, A. Koziolek, D. S. Menasché, M. Paolieri, S. Suresh, A scalable approach to the assessment of storm impact in distributed automation power grids, Proceedings of QEST, pp. 345-367, Springer, 20142014
  Stochastic ProcessesReliability ModelsCritical InfrastructuresApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, F. Tarani, E. Vicario, K. Tadano, Modeling and evaluation of maintenance procedures for gas distribution networks with time-dependent parameters, Proceedings of SAFECOMP workshops (ReSA4CI), pp. 304-315, Springer, 20142014
  Stochastic ProcessesReliability ModelsCritical InfrastructuresApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, K. Tadano, E. Vicario, Towards the quantitative evaluation of phased maintenance procedures using non-Markovian regenerative analysis, Proceedings of EPEW, pp. 176-190, Springer, 20132013
  Stochastic ProcessesReliability ModelsSoftware RejuvenationApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, A. Santoni, E. Vicario, Non-Markovian analysis for model driven engineering of real-time software, Proceedings of ICPE, pp. 113-124, ACM, 20132013
  Stochastic ProcessesPerformance ModelsApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• P. Ballarini, N. Bertrand, A. Horváth, M. Paolieri, E. Vicario, Transient analysis of networks of stochastic timed automata using stochastic state classes, Proceedings of QEST, pp. 355-371, Springer, 20132013
  Stochastic ProcessesTheory
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• L. Carnevali, M. Paolieri, F. Tarani, E. Vicario, Quantitative evaluation of availability measures of gas distribution networks, Proceedings of VALUETOOLS, pp. 145-154, ICST/ACM, 20132013
  Stochastic ProcessesReliability ModelsCritical InfrastructuresApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• S. Ballerini, L. Carnevali, M. Paolieri, K. Tadano, F. Machida, Software rejuvenation impacts on a phased-mission system for Mars exploration, Proceedings of IEEE ISSRE workshops (WOSAR), pp. 275-280, IEEE Computer Society, 20132013
  Stochastic ProcessesReliability ModelsSoftware RejuvenationApplications
  (copy bib | save bib | save pdf | abstract | go to publisher)
  
• A. Horváth, M. Paolieri, L. Ridi, E. Vicario, Transient analysis of non-Markovian models using stochastic state classes, Perform. Evaluation, 69(7-8):315-335, 20122012
  Stochastic ProcessesTheory
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• A. Horváth, M. Paolieri, L. Ridi, E. Vicario, Probabilistic model checking of non-Markovian models with concurrent generally distributed timers, Proceedings of QEST, pp. 131-140, IEEE Computer Society, 20112011
  Stochastic ProcessesModel CheckingTheory
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