# Min Shen

> Leading data platform @ Kumo.ai

Location: Sunnyvale, California, United States
Profile: https://flows.cv/minshen

I hold my Ph.D. degree in computer science where my research interest lies in distributed systems. 
I'm currently a software engineer at LinkedIn and I work in the Hadoop Infrastructure team.

Interested areas:
- Distributed System Algorithms
- Big data systems

## Work Experience
### Software Engineer @ Kumo.AI
Jan 2022 – Present

### Sr. Staff Software Engineer @ LinkedIn
Jan 2021 – Jan 2022

### Staff Software Engineer @ LinkedIn
Jan 2017 – Jan 2021 | San Francisco Bay Area
Tech lead of Spark at LinkedIn. The team is focused on building and scaling LinkedIn's general purpose batch compute engine based on Apache Spark to empower the multiple use cases at LinkedIn ranging from data analytics, data engineering, to ML feature engineering and model training.

### Senior Software Engineer @ LinkedIn
Jan 2015 – Jan 2017 | San Francisco Bay Area
Tech lead of Hadoop YARN at LinkedIn. Improve YARN CapacityScheduler to handle the fast increasing compute needs and the diversified demands from different internal orgs.
- Lead the design and implementation of the OrgQueue project, which aims to decentralize the management of compute resources across the various internal orgs. OrgQueue feature was contributed back to Apache Hadoop YARN.
- Lead the design and implementation of project ElasticityTuner, which automates the OrgQueue management (tuning queue elastic capacity) based on real-time feedbacks of resource demands and allocation fairness among queues. This project converted the YARN cluster queue capacity management at LinkedIn entirely into an autonomous process, significantly freeing up dev and SRE team efforts.

### Software Engineer @ LinkedIn
Jan 2014 – Jan 2015 | San Francisco Bay Area

### MTS intern @ VMware
Jan 2013 – Jan 2013
Work on a project which explores the benefit of virtualizing Hadoop YARN (Hadoop MapReduce nextGen) on top of VMware vSphere. I implemented the virtualization architecture based on hadoop 2.0.4. To further optimize the system for a better support of the multi-tenancy environment, I designed and implemented a tenant-aware scheduling algorithm. The experiment result shows improvement in job completion time.

### SDE Intern @ Amazon
Jan 2012 – Jan 2012
Work on a host monitoring project. To enable this project to monitor a larger scale of hosts (tens of thousands of hosts), I designed and implemented a three-level comparison model. The results shows significant reduction in both storage consumption and average processing time.

### Research Assistant @ University of Illinois at Chicago
Jan 2011 – Jan 2012
Cross layer interaction is a going-on research in wireless sensor network field. We proposed a new paradigm for cross layer interaction, and to cooperate the new paradigm, I implemented an extension to the existing SIDNet-SWANS simulator. This extension enables cross layer interaction in the traditional OSI model simulator. This work is later published in IWCMC 2012.

### Teaching Assistant @ University of Illinois at Chicago
Jan 2009 – Jan 2011
TA for 2 graduate level courses, Theory of Computation and Software Design.
The first deals with the theoretical part of computer science, while the second involves C++ together with other software design principals.

### Research Assistant @ University of Illinois at Chicago
Jan 2009 – Jan 2010
Focusing on the Kshemkalyani-Singhal vector time optimization technique in distributed system area, a simulation system is built to experimentally test how much message overhead is reduced. This work is later published in ISPDC 2011.


## Education
### Doctor of Philosophy (Ph.D.) in Computer Science
University of Illinois Chicago

### BE in Software Engineering
Nanjing University


## Contact & Social
- LinkedIn: https://linkedin.com/in/min-shen

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Source: https://flows.cv/minshen
JSON Resume: https://flows.cv/minshen/resume.json
Last updated: 2026-04-10