I am interested in enabling the efficient management of big data by designing novel high performance data systems. To that end, I am currently working towards 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 summer of 2023.
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.
From Logs to Causal Inference: Diagnosing Large Systems Paper
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)
Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD Paper Extended Version
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)
Press ECCS to Doubt (Your Causal Graph) Paper 🎉 Best Paper Award
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)
Sawmill: From Logs to Causal Diagnosis of Large Systems [Demo] Paper
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)
Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes [Vision] Paper
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)
TreeLine: An Update-In-Place Key-Value Store for Modern Storage Paper
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)
PerpLE: Improving the Speed and Effectiveness of Memory Consistency
Testing Paper
Themis Melissaris, Markos Markakis, Kelly Shaw, and Margaret
Martonosi
53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO
2020)
The use of Indocyanine green in endocrine surgery of the neck: A systematic
review Paper
Nina Maria Fanaropoulou, Angeliki Chorti, Markos Markakis, Maria
Papaioannou, Antonios Michalopoulos, and Theodosios Papavramidis
Medicine 98 (10) (Medicine 2019)
Summer 2023: Amazon Web Services, Applied Scientist Intern - Boston, MA
Summer 2021: Intel Corporation, Graduate Research Intern - Munich, Germany
Summer 2019: McKinsey & Company, Summer Business Analyst - Athens, Greece
Summer 2018: EY (Ernst & Young), Performance Improvement Intern - Athens, Greece
BRAD
Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures
ECCS Documentation
Interactive Causal Graph Verification
LOGos Documentation
From Logs to Causal Diagnosis of Large Systems (formerly "Sawmill")
TreeLine
An Update-In-Place Key-Value Store for Modern Storage
Press ECCS to Doubt (Your Causal Graph) Slides
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 - June 14, 2024
Sawmill: From Logs to Causal Diagnosis of Large Systems Poster
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 - June 9-14, 2024
Sawmill: From Logs to Causal Diagnosis of Large Systems Slides Poster
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 - May 23, 2024
Virtualizing Cloud Data Infrastructures with BRAD Poster
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 - May 23, 2024
Press ECCS to Doubt (Your Causal Graph) Poster
Markos Markakis, Ziyu Zhang, Rana Shahout, Trinity Gao, Chunwei Liu, Ibrahim Sabek, Michael Cafarella
North East Database (NEDB) Day 2024, Boston, MA - May 23, 2024
Sawmill: Extracting Log Data for Causal Diagnosis of Large Systems Poster
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 - April 3, 2024
Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes Poster
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 - August 28-September 1, 2023
TreeLine: An Update-In-Place Key-Value Store for Modern Storage Slides Poster
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 - August 28-September 1, 2023
Learning-Based Creation of Data Mesh Architectures Poster
Tim Kraska*, Tianyu Li*, Samuel Madden*, Markos Markakis*, Amadou
Ngom*, Ziniu Wu*, and Geoffrey X. Yu*
North East Database
(NEDB) Day 2023, Boston, MA - March 10, 2023
Automatically Extracting and Annotating Models From Scientific Publications and
Code Poster
Markos Markakis, Chunwei Liu, Peter Baile Chen, Michael Cafarella
North East Database
(NEDB) Day 2023, Boston, MA - March 10, 2023
TreeLine: An Update-In-Place Key-Value Store for Modern Storage Slides Poster
Geoffrey X. Yu*, Markos Markakis*, Andreas Kipf*, Per-Ake Larson, Umar
Farooq Minhas, and Tim Kraska
North East Database
(NEDB) Day 2023, Boston, MA - March 10, 2023
TreeLine: An Update-In-Place Key-Value Store for Modern Storage Slides Poster
Geoffrey X. Yu*, Markos Markakis*, Andreas Kipf*, Per-Ake Larson, Umar
Farooq Minhas, and Tim Kraska
Fall 2022 DSAIL Retreat, Cambridge, MA -
October 20, 2022
IAP 2024: Programming with Data Workshop Co-instructor
Spring 2022: 6.S079 - Software Systems for Data Science (Prof. Tim Kraska, Prof. Samuel Madden) Teaching Assistant
Fall 2019: ELE 308 - Electronic and Photonic Devices (Prof. Nathalie de Leon) Teaching Assistant
Fall 2019: ELE 206/COS 306 - Contemporary Logic Design (Prof. Sharad Malik) Teaching Assistant
Spring 2019: Undergraduate Computer Science Lab Teaching Assistant for Introductory Courses
Fall 2018: ELE 206/COS 306 - Contemporary Logic Design (Prof. Sharad Malik, Prof. Christopher Brinton) Teaching Assistant
Fall 2018: COS 217 - Introduction to Programming Systems (Prof. Szymon Rusinkiewicz) Piazza Teaching Assistant
Spring 2018: COS 226 - Algorithms and Data Structures (Prof. Mark Braverman) Undergraduate Grader