Markos Markakis

I am interested in enabling the efficient management of big data by designing novel high performance data systems. To that end, I am currently wrapping up a PhD at the intersection of data systems and machine learning as a member of the Data Systems Group at the Computer Science and Artificial Intelligence Lab (CSAIL) of the Massachusetts Institute of Technology. During my time at MIT, I have worked on projects with Prof. Tim Kraska, Prof. Michael Cafarella and Prof. Samuel Madden. I have also interned at Intel as a Graduate Research intern in the summer of 2021, and at Amazon Web Services as an Applied Scientist intern in the summers of 2023 and 2025.

I am currently looking for an industry position starting June 2026.

Before joining MIT, I earned my Bachelor's of Science in Engineering (B.S.E.) in Electrical Engineering from Princeton University, alongside a certificate (minor) in Applications of Computing. For my undergraduate thesis, I had the honor of working with Prof. Margaret Martonosi on efficient memory consistency testing, as well as on formal verification for the DECADES project.

Publications

	12. KramaBench: A Benchmark for AI Systems on Data-to-Insight Pipelines over Data Lakes Eugenie Lai, Gerardo Vitagliano, Ziyu Zhang, Sivaprasad Sudhir, Om Chabra, Anna Zeng, Anton A. Zabreyko, Chenning Li, Ferdi Kossmann, Jialin Ding, Jun Chen, Markos Markakis, Matthew Russo, Weiyang Wang, Ziniu Wu, Michael J. Cafarella, Lei Cao, Samuel Madden, and Tim Kraska arXiv Preprint, Under Review for ICLR 2026
	11. Improving DBMS Scheduling Decisions with Fine-grained Performance Prediction on Concurrent Queries Ziniu Wu, Markos Markakis, Chunwei Liu, Peter Baile Chen, Balakrishnan (Murali) Narayanaswamy, Tim Kraska, and Samuel Madden Proceedings of the VLDB Endowment 18 (11), 4185 - 4198 (VLDB 2025)
	10. Causal DAG Summarization Anna Zeng, Michael Cafarella, Batya Kenig, Markos Markakis, Brit Youngmann, and Babak Salimi Proceedings of the VLDB Endowment 18 (6), 1933 - 1947 (VLDB 2025)
	9. From Logs to Causal Inference: Diagnosing Large Systems Markos Markakis, Brit Youngmann, Trinity Gao, Ziyu Zhang, Rana Shahout, Peter Baile Chen, Chunwei Liu, Ibrahim Sabek, and Michael Cafarella Proceedings of the VLDB Endowment 18 (2), 158 - 172 (VLDB 2025)
	8. Virtualizing Cloud Data Infrastructures with BRAD [Demo] Geoffrey X. Yu, Ziniu Wu, Ferdi Kossmann, Tianyu Li, Markos Markakis, Amadou Ngom, Sophie Zhang, Samuel Madden, and Tim Kraska 2025 International Conference on Management of Data (SIGMOD 2025)
	7. CausaLens: A System for Summarizing Causal DAGs [Demo] Noam Chen, Anna Zeng, Michael Cafarella, Batya Kenig, Markos Markakis, Oren Mishali, Brit Youngmann, and Babak Salimi 2025 International Conference on Management of Data (SIGMOD 2025)
	6. Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD Geoffrey X. Yu, Ziniu Wu, Ferdi Kossmann, Tianyu Li, Markos Markakis, Amadou Ngom, Samuel Madden, and Tim Kraska Proceedings of the VLDB Endowment 17 (11), 3629 - 3643 (VLDB 2024)
🎉 Best Paper	5. Press ECCS to Doubt (Your Causal Graph) Markos Markakis, Ziyu Zhang, Rana Shahout, Trinity Gao, Chunwei Liu, Ibrahim Sabek, and Michael Cafarella 2024 Workshop on Governance, Understanding and Integration of Data for Effective and Responsible AI (GUIDE-AI 2024)
	4. Sawmill: From Logs to Causal Diagnosis of Large Systems [Demo] Markos Markakis, An Bo Chen, Brit Youngmann, Trinity Gao, Ziyu Zhang, Rana Shahout, Peter Baile Chen, Chunwei Liu, Ibrahim Sabek, and Michael Cafarella 2024 International Conference on Management of Data (SIGMOD 2024)
	3. Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes [Vision] Tim Kraska, Tianyu Li, Samuel Madden, Markos Markakis, Amadou Ngom, Ziniu Wu, and Geoffrey X. Yu* Proceedings of the VLDB Endowment 16 (11), 3293-3301 (VLDB 2023)
	2. TreeLine: An Update-In-Place Key-Value Store for Modern Storage Geoffrey X. Yu, Markos Markakis, Andreas Kipf, Per-Ake Larson, Umar Farooq Minhas, and Tim Kraska Proceedings of the VLDB Endowment 16 (1), 99-112 (VLDB 2023)*
	1. PerpLE: Improving the Speed and Effectiveness of Memory Consistency Testing Themis Melissaris, Markos Markakis, Kelly Shaw, and Margaret Martonosi 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO 2020)
	0. The use of Indocyanine green in endocrine surgery of the neck: A systematic review Nina Maria Fanaropoulou, Angeliki Chorti, Markos Markakis, Maria Papaioannou, Antonios Michalopoulos, and Theodosios Papavramidis Medicine 98 (10) (Medicine 2019)

Work Experience

	05/2025 - 08/2025	Amazon Web Services Applied Scientist Intern - Boston, MA Interned with the Learned Systems Group within Amazon Redshift. Developed ML models for workload tail latency prediction on Redshift Serverless, enabling improved cost-efficient scaling under production workloads.
	05/2023 - 08/2023	Amazon Web Services Applied Scientist Intern - Boston, MA Interned with the Learned Systems Group within Amazon Redshift. Designed and evaluated techniques to accelerate recurring Redshift workloads and improve latency for enterprise data warehousing customers.
	06/2021 - 08/2021	Intel Corporation Graduate Research Intern - Munich, Germany Interned remotely with the US-based Intel Cloud Enterprise Solutions Group. Explored solutions for leveraging persistent memory technology for key-value stores.
	06/2019 - 08/2019	McKinsey & Company Summer Business Analyst Intern - Athens, Greece Helped a prominent organization of over 7000 employees redefine its strategic vision after a major leadership change and shifts in market conditions. Contributed to corporate governance restructuring recommendations presented directly to the CEO of the client company. Joined an international team as the domestic expert to help an organization rethink the staffing and work allocation paradigm in one of its most business-critical units.
	06/2018 - 08/2018	EY (Ernst & Young) Performance Improvement Intern - Athens, Greece Contributed to a software suite which analyzed the product data of an international retail client to provide actionable business insights. Designed and developed a machine learning tool that facilitates sentiment analysis of intra-organizational feedback comments.

Education

06/2022 - Present
Expected 05/2026

Massachusetts Institute of Technology
PhD Candidate in Electrical Engineering and Computer Science

Advisor: Prof. Tim Kraska (Data Systems Group)
Research: Workload-aware, ML-driven optimization for data systems.
Collaborations: Microsoft Research, Intel, and Amazon via MIT's DSAIL

09/2020 - 05/2022

Massachusetts Institute of Technology
Master of Science in Electrical Engineering and Computer Science

Advisor: Prof. Tim Kraska (Data Systems Group)
Thesis: Rethinking Update-in-Place Key-Value Stores for Modern Storage

09/2016 - 06/2020

Princeton University — Princeton, NJ
BSE in Electrical Engineering, Summa Cum Laude

Advisor: Prof. Margaret Martonosi (MRM Research Group)
Thesis: Challenges and Opportunities in Heterogeneous Parallelism

Open-Source Code

	LOGos From Logs to Causal Diagnosis of Large Systems (formerly "Sawmill")
	ECCS Interactive Causal Graph Verification
	BRAD Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures
	TreeLine An Update-In-Place Key-Value Store for Modern Storage

News

	2025/06/23	Building brain bridges to the Greek diaspora [Opinion] Kathimerini, Athens, Greece
	2025/06/10	Press coverage of the first Hellenic American Meeting of Early-Career Researchers [in Greek] iefimerida, Athens, Greece
	2024/12/10	CSAIL Alliances Student Spotlights: Markos Markakis MIT CSAIL, Cambridge, MA, USA
	2021/12/10	University Survival Guide: Markos Markakis '16 [in Greek] Anatolia College Alumni News, Thessaloniki, Greece
	2020/06/02	Graduates recognized for innovation, service and perseverance Princeton University, Princeton, NJ, USA
	2019/04/10	Student Profile by the Princeton Center for Statistics and Machine Learning by Sharon Adarlo Princeton University, Princeton, NJ, USA
	2018/09/10	Markakis, a junior, honored at Opening Exercises by Jamie Saxon Princeton University, Princeton, NJ, USA
	2016/12/15	Architectural ethics is focus of freshman seminar by Laurie Zazenski Princeton University, Princeton, NJ, USA
	2016/06/17	Anatolia College students achieve excellent international college admission results [in Greek] Anatolia College Press Release, Thessaloniki, Greece

Presentations

	2025/09/04	From Logs to Causal Inference: Diagnosing Large Systems Markos Markakis, Brit Youngmann, Trinity Gao, Ziyu Zhang, Rana Shahout, Peter Baile Chen, Chunwei Liu, Ibrahim Sabek, and Michael Cafarella 51st International Conference on Very Large Data Bases (VLDB 2025), London, UK
	2025/09/03	Improving DBMS Scheduling Decisions with Fine-grained Performance Prediction on Concurrent Queries Ziniu Wu, Markos Markakis, Chunwei Liu, Peter Baile Chen, Balakrishnan (Murali) Narayanaswamy, Tim Kraska, and Samuel Madden 51st International Conference on Very Large Data Bases (VLDB 2025), London, UK
	2025/05/10	Cloud Data Processing with Cost-Efficient Latency SLOs using Probabilistic Query Performance Prediction Markos Markakis, Ziniu Wu, Tim Kraska 1st Hellenic American Meeting of Early-Career Researchers (HAMER 2025), Cambridge, MA
	2024/06/14	Press ECCS to Doubt (Your Causal Graph) Markos Markakis, Ziyu Zhang, Rana Shahout, Trinity Gao, Chunwei Liu, Ibrahim Sabek, Michael Cafarella 1st Workshop on Governance, Understanding and Integration of Data for Effective and Responsible AI (GUIDE-AI 2024), Santiago, Chile
	2024/06/11	Sawmill: From Logs to Causal Diagnosis of Large Systems Markos Markakis, An Bo Chen, Brit Youngmann, Trinity Gao, Ziyu Zhang, Rana Shahout, Peter Baile Chen, Chunwei Liu, Ibrahim Sabek, Michael Cafarella 2024 ACM SIGMOD/PODS International Conference on Management of Data (SIGMOD 2024), Santiago, Chile
	2024/05/23	Sawmill: From Logs to Causal Diagnosis of Large Systems Markos Markakis, An Bo Chen, Brit Youngmann, Trinity Gao, Ziyu Zhang, Rana Shahout, Peter Baile Chen, Chunwei Liu, Ibrahim Sabek, Michael Cafarella North East Database (NEDB) Day 2024, Boston, MA
	2024/05/23	Virtualizing Cloud Data Infrastructures with BRAD Geoffrey X. Yu, Ziniu Wu, Ferdinand Kossmann, Tianyu Li, Markos Markakis, Amadou L Ngom, Tim Kraska, Samuel Madden North East Database (NEDB) Day 2024, Boston, MA
	2024/05/23	Press ECCS to Doubt (Your Causal Graph) Markos Markakis, Ziyu Zhang, Rana Shahout, Trinity Gao, Chunwei Liu, Ibrahim Sabek, Michael Cafarella North East Database (NEDB) Day 2024, Boston, MA
	2024/04/03	Sawmill: Extracting Log Data for Causal Diagnosis of Large Systems Markos Markakis, Brit Youngmann, Trinity Gao, Ziyu Zhang, Rana Shahout, Peter Baile Chen, Chunwei Liu, Ibrahim Sabek, Michael Cafarella CSAIL Alliances Annual Meeting 2024, Cambridge, MA
	2023/08/31	TreeLine: An Update-In-Place Key-Value Store for Modern Storage Geoffrey X. Yu, Markos Markakis, Andreas Kipf, Per-Ake Larson, Umar Farooq Minhas, and Tim Kraska 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada*
	2023/08/29	Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes Tim Kraska, Tianyu Li, Samuel Madden, Markos Markakis, Amadou Ngom, Ziniu Wu, and Geoffrey X. Yu* 49th International Conference on Very Large Data Bases (VLDB 2023), Vancouver, Canada
	2023/03/10	Learning-Based Creation of Data Mesh Architectures Tim Kraska, Tianyu Li, Samuel Madden, Markos Markakis, Amadou Ngom, Ziniu Wu, and Geoffrey X. Yu* North East Database (NEDB) Day 2023, Boston, MA
	2023/03/10	Automatically Extracting and Annotating Models From Scientific Publications and Code Markos Markakis, Chunwei Liu, Peter Baile Chen, Michael Cafarella North East Database (NEDB) Day 2023, Boston, MA
	2023/03/10	TreeLine: An Update-In-Place Key-Value Store for Modern Storage Geoffrey X. Yu, Markos Markakis, Andreas Kipf, Per-Ake Larson, Umar Farooq Minhas, and Tim Kraska North East Database (NEDB) Day 2023, Boston, MA*
	2022/10/20	TreeLine: An Update-In-Place Key-Value Store for Modern Storage Geoffrey X. Yu, Markos Markakis, Andreas Kipf, Per-Ake Larson, Umar Farooq Minhas, and Tim Kraska DSAIL Retreat, Cambridge, MA*

Service

Reviewing

	2025/04 - Present	Proceedings of the VLDB Endowment (PVLDB), Volume 19 (For VLDB 2026)
	2025	ACM Computing Surveys (CSUR), Volume 57 (2025)

Mentoring

	2025/05 - Present	EECS Communication Lab Fellow Massachusetts Institute of Technology
	2024/09 - 2024/12	EECS Graduate Application Assistance Program (GAAP) Mentor Massachusetts Institute of Technology
	2023/09 - 2023/12	EECS Graduate Application Assistance Program (GAAP) Mentor Massachusetts Institute of Technology
	2022/09 - 2022/12	EECS Graduate Application Assistance Program (GAAP) Mentor Massachusetts Institute of Technology

Teaching

	2025/01	Programming with Data Workshop Co-instructor Massachusetts Institute of Technology
	2024/01	Programming with Data Workshop Co-instructor Massachusetts Institute of Technology
	2022/02 - 2022/05	6.S079 - Software Systems for Data Science Teaching Assistant Massachusetts Institute of Technology
	2019/09 - 2019/12	ELE 308 - Electronic and Photonic Devices Teaching Assistant Princeton University
	2019/09 - 2019/12	ELE 206/COS 306 - Contemporary Logic Design Teaching Assistant Princeton University
	2019/02 - 2019/05	Undergraduate Computer Science Lab Teaching Assistant for Introductory Courses Princeton University
	2018/09 - 2018/12	ELE 206/COS 306 - Contemporary Logic Design Teaching Assistant Princeton University
	2018/09 - 2018/12	COS 217 - Introduction to Programming Systems Piazza Teaching Assistant Princeton University
	2018/02 - 2018/05	COS 226 - Algorithms and Data Structures Undergraduate Grader Princeton University

Fun

	2022/06 - 2025/05	MIT Hellenic Students' Association (HSA) The HSA promotes fellowship among members of the Greek/Cypriot student community at MIT and beyond. I served as the HSA president in 2024-25, after having served as the HSA treasurer in 2023-24 and as the HSA publicity chair in 2022-23.
	2014/04 - 2018/01	Pantzouroi I played lead guitar for a local rock band in high school. We recorded 5 original songs and performed, among other venues, at Schoolwave Festival 2016.