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Yulun Tian

 
Ph.D. candidate at MIT AeroAstro

Email:

yulun [at] mit [dot] edu

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Hi There! I'm Yulun.

 

I am a Ph.D. candidate in the Department of Aeronautics and Astronautics at MIT, advised by Professor Jonathan How. I am passionate about developing provably correct algorithms and real-world systems to enable future multi-agent perception and navigation. Beyond that, I am also broadly interested in robot autonomy and machine learning. 

For a complete list of my publications, please visit my Google Scholar page.

 

 
EXPERIENCE
Fall 2017 - Present

Research Assistant

Aerospace Controls Lab, MIT

I currently work as a research assistant at MIT's Aerospace Controls Lab (ACL). My research focuses on developing new algorithms, theoretical guarantees, and real-world systems for collaborative simultaneous localization and mapping (SLAM).

June 2020 - Aug 2020

Research Intern

Reality Labs, Meta

I interned at Facebook Reality Labs during the summer of 2020. My research project investigates robust translation averaging methods for large-scale structure-from-motion (SfM) applications.

Spring 2017

Teaching Assistant

UC Berkeley

I served as an undergraduate student instructor for EE 122 - Communication Networks. My main duties include holding regular office hours,  designing exam questions, and helping with class logistics.

Spring 2016 - Spring 2017

Undergraduate Researcher

UC Berkeley

I worked as an undergraduate research assistant with Ming Jin and Professor Costas Spanos. Our projects aim to use agile robots to accomplish tasks in the emerging field of smart buildings. 

Summer 2016

Software Engineering Intern

Oracle

I joined Oracle's Solaris Platform QE group as a software engineering intern. 

 
RESEARCH
Distributed Pose Graph Optimization
  • Distributed Certifiably Correct Pose-Graph Optimization
    [Paper] [Video Presentation][Code]
    Y. Tian, K. Khosoussi, D.M. Rosen, J.P. How
    IEEE Transactions on Robotics (T-RO), 2021
    2021 Honorable Mention for the King-Sun Fu Memorial Best Paper Award

  • Asynchronous and Parallel Distributed Pose Graph Optimization [Paper
    Y. Tian, A. Koppel, A.S. Bedi, J.P. How
    IEEE Robotics and Automation Letters (RA-L), 2020
    2020 Honorable Mention for the IEEE RA-L Best Paper Award

Distributed Metric-Semantic SLAM
  • Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems [Paper] [Demo]
    Y. Tian, Y. Chang, F. Herrera Arias, C. Nieto-Granda,
    J. P. How, L. Carlone
    IEEE Transactions on Robotics (T-RO), 2022

Forest Search and Rescue using multiple UAVs
  • Search and Rescue under the Forest Canopy using Multiple UAVs
    [Paper] [MIT News]
    Y. Tian, K. Liu, K. Ok, L. Tran, D. Allen, N. Roy, J.P. How
    International Journal of Robotics Research (IJRR), 2020
    Invited to special issue of IJRR

RSS18
Resource-Aware Collaborative SLAM 
  • Near-Optimal Budgeted Data Exchange for Distributed Loop Closure Detection [Paper]
    Y. Tian, K. Khosoussi, M. Giamou, J.P. How, J. Kelly
    Robotics: Science and Systems (RSS) 2018

  • Resource-Aware Algorithms for Distributed Loop Closure Detection with Provable Performance Guarantees [Paper]
    Y. Tian, K.Khosoussi, J.P. How
    Int. Workshop on the Algorithmic Foundations of Robotics (WAFR) 2018
    Invited to special issue of IJRR

 
SKILLS

C/C++

Python

SQL

MATLAB

OpenCV

Spark

Robot Operating System (ROS)

PyTorch/TensorFlow

Google Web Toolkit (GWT)

 
Fall 2019-Present

Ph.D

Aeronautics & Astronautics, MIT

Courses: Nonlinear Optimization, Optimization Algorithms for Machine Learning, Advances in Computer Vision, Semidefinite Optimization

2017-2019

M.S.

Aeronautics & Astronautics, MIT

Courses: Principles of Autonomy and Decision Making, Optimal Control and Estimation, Machine Learning, Algorithms for Inference, Real Analysis

2013-2017

B.A. High Distinction

Computer Science, UC Berkeley

Courses: Machine Learning, Artificial Intelligence, Algorithms, Optimization Models, Systems and Signals, Operating Systems, Communication Networks, Databases, Computer Security

 
EDUCATION