Microsoft Research AI Frontiers
300 Lafayette St.
New York, NY 10012

Email: sidsen AT micro...

My CV (Updated: 10/2018)

I am a Principal Researcher Manager in the AI Frontiers lab of Microsoft Research, where I lead our work on Large Action Models (LAMs). Our goal is to build action-oriented, multimodal transformer (and beyond) models that can act like humans (and beyond) in domains such as web/OS interaction, car racing, and gaming. Previously I was part of the Microsoft Research NYC lab, who we share a building with and continue to work closely together; before that, I was a researcher in the MSR Silicon Valley lab. My research trajectory started with distributed systems and data structures, evolved to incorporate machine learning, and is currently most inspired by human behavior and improvement. The Maia project is an example of this perspective.

I received my PhD from the Department of Computer Science at Princeton University, where I worked with Robert Tarjan in the theory group and Michael Freedman in the systems group. I spent my final year as a junior research scientist at New York University working with Jinyang Li. Prior to my PhD, I worked for three years in the Network Load Balancing group of Windows Server at Microsoft. I received my S.B. and M.Eng. in Computer Science from MIT, where my M. Eng thesis advisor was Charles Leiserson.

Publications

2024

• Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
  with Karim Hamade, Reid McIlroy-Young, Jon Kleinberg, and Ashton Anderson
  In Proc. 12th International Conference on Learning Representations (ICLR), 2024
  
• Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification
  with A. Feder Cooper, Katherine Lee, Madiha Choksi, Solon Barocas, Christopher De Sa, James Grimmelmann, Jon Kleinberg, and Baobao Zhang
  In Proc. 38th Annual AAAI Conference on Artificial Intelligence (AAAI), 2024
  
• TraceUpscaler: Upscaling Traces to Evaluate Systems at High Load
  with Sultan Mahmud Sajal, Timothy Zhu, and Bhuvan Urgaonkar
  In Proc. 19th European Conference on Computer Systems (EuroSys), 2024
  Best Runner-up Paper Award

2023

• Splice: Efficiently Removing a User's Data from In-memory Application State
  with Xueyuan Han and James Mickens
  In Proc. 2023 ACM Conference on Computer and Communications Security (CCS), 2023
  
• CodaMOSA: Escaping Coverage Plateaus in Test Generation with Pre-trained Large Language Models
  with Caroline Lemieux, Jeevana Priya Inala, and Shuvendu K. Lahiri
  In Proc. 45th International Conference on Software Engineering (ICSE), 2023
  
• NCC: Natural Concurrency Control for Strictly Serializable Datastores by Avoiding the Timestamp-Inversion Pitfall
  with Haonan Lu, Shuai Mu, and Wyatt Lloyd
  In Proc. 17th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2023
  
• A new reduced mechanism for gas-phase isoprene oxidation
  with Forwood Wiser, Bryan K. Place, Siddhartha Sen, Havala O. T. Pye, Benjamin Yang, Daniel M. Westervelt, Daven K. Henze, Arlene M. Fiore, and V. Faye McNeill
  In Geoscientific Model Development (GMD), 2023
  

2022

• Learning Models of Individual Behavior in Chess
  with Reid McIlroy-Young, Russell Wang, Jon Kleinberg, and Ashton Anderson
  In Proc. 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022
  
• Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments
  with Jinkun Lin, Anqi Zhang, Mathias Lecuyer, Jinyang Li, and Aurojit Panda
  In Proc. 39th International Conference on Machine Learning (ICML), 2022
  
• Mimetic Models: Ethical Implications of AI that Acts Like You
  with Reid McIlroy-Young, Jon Kleinberg, Solon Barocas, and Ashton Anderson
  In Proc. 5th AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES), 2022
  
• How Reinforcement Learning Systems Fail and What to do About It
  with Pouya Hamadanian, Malte Schwarzkopf, and Mohammad Alizadeh
  In Proc. 2nd Workshop on Machine Learning and Systems (EuroMLSys), 2022
  
• Rolis: A software approach to efficiently replicating multi-core transactions
  with Weihai Shen, Ansh Khanna, Sebastian Angel, and Shuai Mu
  In Proc. 17th European Conference on Computer Systems (EuroSys), 2022
  

2021

• Detecting Individual Decision-Making Style: Exploring Behavioral Stylometry in Chess
  with Reid McIlroy-Young, Russell Wang, Jon Kleinberg, and Ashton Anderson
  In Proc. 35th Conference on Neural Information Processing Systems (NeurIPS), 2021
  
• Sayer: Using Implicit Feedback to Optimize System Policies
  with Mathias Lecuyer, Sang Hoon Kim, Mihir Nanavati, Junchen Jiang, Aleksandrs Slivkins, and Amit Sharma
  In Proc. 12th ACM Symposium on Cloud Computing (SoCC), 2021
  
• SmartHarvest: Harvesting Idle CPUs Safely and Efficiently in the Cloud
  with Yawen Wang, Kapil Arya, Marios Kogias, Manohar Vanga, Aditya Bhandari, Neeraja J. Yadwadkar, Sameh Elnikety, Christos Kozyrakis, and Ricardo Bianchini
  In Proc. 16th European Conference on Computer Systems (EuroSys), 2021
  
• TraceSplitter: A New Paradigm for Downscaling Traces
  with Sultan Mahmud Sajal, Rubaba Hasan, Timothy Zhu, and Bhuvan Urgaonkar
  In Proc. 16th European Conference on Computer Systems (EuroSys), 2021
  
• SENSEI: Aligning Video Streaming Quality with Dynamic User Sensitivity
  with Xu Zhang, Yiyang Ou, and Junchen Jiang
  In Proc. 18th USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2021
  

2020

• Performance-Optimal Read-Only Transactions
  with Haonan Lu and Wyatt Lloyd
  In Proc. 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2020
  
• Tolerating Slowdowns in Replicated State Machines using Copilots
  with Khiem Ngo and Wyatt Lloyd
  In Proc. 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2020
  
• Aligning Superhuman AI with Human Behavior: Chess as a Model System
  with Reid McIlroy-Young, Jon Kleinberg, and Ashton Anderson
  In Proc. 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020
  
• Disaggregation and the Application
  with Sebastian Angel and Mihir Nanavati
  In Proc. 12th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud), 2020
  
• Expanding the Scope of Reproducibility Research Through Data Analysis Replications
  with Jake M. Hofman, Daniel G. Goldstein, and Forough Poursabzi-Sangdeh
  In Proc. The Web Conference Workshop on Innovative Ideas in Data Science (IID), 2020
  Best Paper Award

2019

• E2E: Embracing User Heterogeneity to Improve Quality of Experience on the Web
  with Xu Zhang, Daniar Kurniawan, Haryadi Gunawi, and Junchen Jiang
  To appear in Proc. ACM Special Interest Group on Data Communication (SIGCOMM), 2019
  

2018

• RobinHood: Tail Latency-Aware Caching -- Dynamically Reallocating from Cache-Rich to Cache-Poor
  with Daniel Berger, Benjamin Berg, Timothy Zhu, and Mor Harchol-Balter
  In Proc. 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2018
  
• The FuzzyLog: A Partially Ordered Shared Log
  with Joshua Lockerman, Jose Faleiro, Juno Kim, Soham Sankaran, Daniel J. Abadi, James Aspnes, and Mahesh Balakrishnan
  In Proc. 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI), 2018
  
• Chameleon: Scalable Adaptation of Video Analytics
  with Junchen Jiang, Ganesh Ananthanarayanan, Peter Bodik, and Ion Stoica
  In Proc. ACM Special Interest Group on Data Communication (SIGCOMM), 2018
  

2017

• Harvesting Randomness to Optimize Distributed Systems
  with Mathias Lecuyer, Joshua Lockerman, Lamont Nelson, Amit Sharma, and Aleksandrs Slivkins
  In Proc. 16th ACM Workshop on Hot Topics in Networks (HotNets), 2017
  
• Hyperbolic Caching: Flexible Caching for Web Applications
  with Aaron Blankstein and Michael J. Freedman
  In Proc. USENIX Annual Technical Conference (ATC), 2017
  
• Pyramid: Enhancing Selectivity in Big Data Protection with Count Featurization
  with Mathias Lecuyer, Riley Spahn, Roxana Geambasu, and Tzu-Kuo Huang
  In Proc. 38th IEEE Security and Privacy Symposium (IEEE S&P), 2017
  
  • Invited article: Enhancing Selectivity in Big Data in IEEE S&P Magazine, 2018
• Black-box Concurrent Data Structures for NUMA Architectures
  with Irina Calciu, Mahesh Balakrishnan, and Marcos Aguilera
  In Proc. 22nd ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2017
  Best Paper Award
  • How to Implement Any Concurrent Data Structure in Communications of the ACM (CACM), 2017
  • Brief announcement in Proc. 31st International Symposium on Distributed Computing (DISC), 2017

2016

• Balancing CPU and Network in the Cell Distributed B-Tree Store
  with Christopher Mitchell, Kate Montgomery, Lamont Nelson, and Jinyang Li
  In Proc. USENIX Annual Technical Conference (ATC), 2016
  
• Deletion Without Rebalancing in Binary Search Trees
  with David H. K. Kim and Robert E. Tarjan
  In ACM Transactions on Algorithms (TALG), 2016
  • Conference version in Proc. 21st ACM-SIAM Symposium on Discrete Algorithms (SODA), 2010

2015

• Rank-Balanced Trees
  with Bernhard Haeupler and Robert E. Tarjan
  In ACM Transactions on Algorithms (TALG), 2015
  • Conference version in Proc. 11th International Symposium on Algorithms and Data Structures (WADS), 2009

2014

• Aggregation and Degradation in JetStream: Streaming analytics in the wide area
  with Ariel Rabkin, Matvey Arye, Vivek Pai, and Michael J. Freedman
  In Proc. 11th USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2014
  
  • Workshop paper in Proc. 14th Workshop on Hot Topics in Operating Systems (HotOS), 2013
  • Invited abstract in Proc. 6th Workshop on Large Scale Distributed Systems and Middleware (LADIS), 2012
• A Back-to-Basics Empirical Study of Priority Queues
  with Daniel H. Larkin and Robert E. Tarjan
  In Proc. 16th Workshop on Algorithm Engineering and Experiments (ALENEX), 2014
• Deletion Without Rebalancing in Multiway Search Trees
  with Robert E. Tarjan
  In ACM Transactions on Database Systems (TODS), 2014
  • Conference version in Proc. 20th International Symposium on Algorithms and Computation (ISAAC), 2009
    Invited to Special Issue for ISAAC 2009 of Theoretical Computer Science

2013

• Scalable, Optimal Flow Routing in Datacenters via Local Link Balancing
  with David Shue, Sunghwan Ihm, and Michael J. Freedman
  In Proc. 9th International Conference on emerging Networking EXperiments and Technologies (CoNEXT), 2013
  
  • Brief announcement in Proc. 25th International Symposium on Distributed Computing (DISC), 2011

2012

• On the Price of Equivocation in Byzantine Agreement
  with Alexander Jaffe and Thomas Moscibroda
  In Proc. 31st ACM Symposium on Principles of Distributed Computing (PODC), 2012
  Best Student Paper Award
  Invited to Journal of the ACM
  • My Review of PODC 2012 appears in Idit Keidar's SIGACT News Distributed Computing Column
• Don't Lose Sleep Over Availability: The GreenUp Decentralized Wakeup Service
  with Jacob R. Lorch, Richard Hughes, Carlos G. J. Suarez, Brian Zill, Weverton Cordeiro, and Jitendra Padhye
  In Proc. 9th USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2012
  
• Commensal Cuckoo: Secure Group Partitioning for Large-Scale Services
  with Michael J. Freedman
  In Best papers from LADIS 2011 issue of ACM SIGOPS Operating Systems Review (OSR), 2012
  
  • In Proc. 5th Workshop on Large Scale Distributed Systems and Middleware (LADIS), 2011
• Incremental Cycle Detection, Topological Ordering, and Strong Component Maintenance
  with Bernhard Haeupler, Telikepalli Kavitha, Rogers Mathew, and Robert E. Tarjan
  In ACM Transactions on Algorithms (TALG), 2012
  • Conference version in Proc. 35th International Colloquium on Automata, Languages, and Programming (ICALP), 2008

2011

• Rank-Pairing Heaps
  with Bernhard Haeupler and Robert E. Tarjan
  In SIAM Journal on Computing (SICOMP), 2011
  • Conference version in Proc. 17th European Symposium on Algorithms (ESA), 2009
    Invited to Special Issue for ESA 2009 of Algorithmica

2010 and earlier

• Prophecy: Using History for High-Throughput Fault Tolerance
  with Wyatt Lloyd and Michael J. Freedman
  In Proc. 7th USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2010
• Virtual Ring Routing Trends
  with Dahlia Malkhi, Kunal Talwar, Renato F. Werneck, and Udi Wieder
  In Proc. 23rd International Symposium on Distributed Computing (DISC), 2009
  

Patents

• Client affinity in distributed load balancing systems
  with Vladimir Petter and Andrea D'Amato.
  United States Patent #8176495. Issued May 8, 2012.
  
• Maintaining client affinity in network load balancing systems
  with Vladimir Petter, Andrea D'Amato, and Jimmy C. Yu.
  United States Patent #8046467. Issued Oct. 25, 2011.
  
• Software testing techniques for stack-based environments
  with Amit Date.
  United States Patent #7827531. Issued Nov. 2, 2010.
  
• Diagnosing problems in distributed systems
  with Joseph M. Joy, Nikolai Tillman, Colin L. Campbell, and Margus Veanes.
  United States Patent #7548911. Issued June 16, 2009.
  
  

Service

• Conference/Workshop organizer: Cloud Intelligence Workshop, SysML '20, SysML '19, AI Systems (SOSP '19, SOSP '17), Systems for ML/ML Systems (NeurIPS '19, NIPS '18, NIPS '17, NIPS '16),
• Program committees: SOSP '24, AAAI '24, MLSys '23, NSDI '21, SIGMETRICS '21, MLSys '21, ATC '20, SysML '20, SoCC '19, SysML '19, ATC '18, SoCC '17, CoNEXT '16, NSDI '16, SOCC '15, P2P '15, SSS '13, SIROCCO '13
• External reviews: DISC '20, ITCS '19, SODA '18, FOCS '17, ICALP '15, ESA '14, FOCS '13, NSDI '13, SODA '13, NSDI '12, CATS '12, SODA '12, SODA '11, ICALP '10, LATIN '10, STACS '10, Inf. Proc. Letters (IPL)
• Journal reviews: Algorithmica, Theoretical Computer Science (TCS), Transactions on Knowledge and Data Engineering (TKDE), Software: Practice and Experienc (SPE), Information Processing Letters (IPL)
  
  

Teaching

• Data Science Summer School (DS3), Instructor, Summer 2016-2018
• Modeling Social Data (APAM E4990), Guest Lecturer, Spring 2018
• Theory of Algorithms (COS 423), Teaching Assistant/Guest Lecturer, Spring 2009, 2011
• General Computer Science (COS 126), Teaching Assistant, Fall 2008
  
  

Students

I've had the privilege of working with these talented students/postdocs, many of whom have moved on to doing greater things!

• Xueyuan (Michael) Han (PhD, Harvard)
• Joana M. F. da Trindade (PhD, MIT)
• Sebastian Angel (PhD, NYU)
• Xu Zhang (PhD, U. Chicago)
• Haonan Lu (PhD, Princeton)
• Mathias Lecuyer (PhD, Columbia)
• Yawen Wang (PhD, Stanford)
• Ana Stoica (PhD, Columbia)
• Daniel Berger (postdoc, CMU)
• Mihir Nanavati (PhD, UBC)
• Benjamin Berg (PhD, CMU)
• Khiem Ngo (PhD, Princeton)
• Lloyd Brown (undergraduate, Cornell)
• Lamont Nelson (PhD, NYU)
• Amy Tai (PhD, Princeton)
• Joshua Lockerman (PhD, Yale)
• Riley Spahn (PhD, Columbia)
• Aaron Blankstein (PhD, Princeton)
• Matvey Arye (PhD, Princeton)
• Christopher Mitchell (PhD, NYU)
• Daniel Larkin (PhD, Princeton)
• Jarett Schwartz (undergraduate, Princeton)
• Kay Ousterhout (undergraduate, Princeton)
• David Hong Kyun Kim (undergraduate, Princeton)