TechLab at Mcity is an incubator for early-stage mobility companies in the connected and autonomous vehicle industry. The incubator places a heavy emphasis on student learning by matching emerging transportation startups with students interested in applying classroom learning to practical technology development. 

TechLab is managed by U-M Center for Entrepreneurship, in partnership with Mcity.



ENTR 390. 013 | Tues. 4-6PM, 1690 Beyster

TechLab students experience entrepreneurship while working in the emerging industry of connected and automated mobility. We are looking for the most driven, passionate and talented students to join this program. 



  • Participate in a 1-year fellowship program (Must be able to enroll Winter-Fall 2019) 
  • Complete a sponsor company project and receive 3-credits per semester
  • Gain experience developing new technologies at an early-stage startup
  • Work with industry experts and U-M faculty across multiple disciplines  





This incubator is for startups who are developing technologies for connected and automated vehicles, and passionate about educating the future technical leaders of tomorrow. 



  • Work on your proposed year-long project with a team of 3-4 student interns
  • Receive access to the Mcity Test Facilty–the nation’s leading mobility research and urban test facility on U-M’s North Campus
  • Gain access to U-M faculty and industry experts
  • Leverage the close proximity to Detroit, the birthplace of mobility 


I am not a CoE student, can I apply?
TechLab is open to all undergraduate students.

Due to the highly competitive nature of the program, if you are not accepted, we recommend reapplying the following year. Depending on the technical experience that a student has, an incoming freshman could be selected to participate.

I am a Masters student, can I apply?
At this time, TechLab is only open to undergraduate students. We are looking to expand the program to Master students.
What is the time commitment?
In order to participate, you must be able to commit to two semesters – Winter & Fall.

Students are required to attend a lecture class every week. Class serves two purposes (1) Receive lectures from faculty on topics like business model and project management (2) Present weekly updates and ask for guidance relating to project roadblocks

To fit with U-M guidelines of 2-3 hours of work per credit hour, this course will require 8-10 hours outside of class.

How will I know if I am selected?
Only selected students will be contacted via email.
How will students interface with the companies?
Student teams have an hour-long weekly Skype or Google Hangout call with the company they are matched with. At different points during the year company leads may travel to Ann Arbor to work with students.
How many & what type of credits do I earn?
3 general elective credits per semester. You must be eligible to receive all 3 credits.


*Note: EECS students can use this course as a flexible technical credit. We are working to get this approved among other CoE departments. 

What do companies receive access to?
Upon being accepted into the incubator program, companies are paired with a team of 3-4 U-M students. As a part of TechLab, you also receive access to Mcity’s Open CAV program, the Mcity Test Facility– the nation’s leading mobility research and urban test facility on U-M’s North Campus, and additional resources as needed. 
What type of companies are you looking for?
We are looking for early-stage technology companies in the autonomous and connected vehicle industry. The typical TechLab company is one that has already raised > $5M dollars and has more than 15 employees. This guarantees that we are working with globally leading companies that are well on their way and have the management capability to oversee and contribute to projects in a substantial way.
How does our company apply?
All companies are required to submit a proposal. If you are interested in being considered for this incubator program, please email
Who owns any IP that is developed?
Existing intellectual property of technology startups, and any IP developed using the U-M facilities, will be strictly protected and remain with your company. All students are required to sign a NDA.


New York City, NY

Provides real-time 3D maps and navigation-critical data for autonomous vehicles. | More info:

Looking for. experience in..

  • Computer vision
  • Machine learning
  • Artificial intelligence
  • Software development either from hands on internships/projects or advanced level courses in programming, preferred
  • In-vehicle integration skills

Desired Coursework : EECS 442, EECS 445, EECS 447, EECS 492, EECS 402, EECS 481



San Jose, CA

Exposes self-driving cars to the harshest conditions on earth through simulation testing. | More info:

Looking for experience in…

  • Autonomous vehicle sensing suite
  • Data management
  • ROS/Python/C++, MatLAB and/or Octave
  • Machine learning techniques – classification, clustering, regression – and framework


Trillium Secure

Trillium Secure

Sunnyvale, CA

Developing machine learning techniques to advance vehicle cybersecurity measures. | More info:

Looking for experience in…

  • Machine learning
  • Artificial intelligence 
  • Experience with CAN bus data
  • Knowledge of data formats and/or databases

Desired coursework (or their prerequisites): EECS 445, EECS 453, EECS 545




Portland, OR

Builds a framework for building, testing and deploying safe driverless vehicle applications quickly. | More info:

Looking for experience in…

  • Software development, including items such as configuration management
  • Systems design and integration experience – getting the system up and running, assisting with the debugging of operational problems
  • C/C++/Python programming
  • R/MATLAB for data analysis and scripting





Detroit, MI

Operates in the Internet of Things technology space. As part of TechLab, Tome will focus on safe bicycle-to-vehicle (B2V) communication. | More info:

Looking for experience in…

  • Basic knowledge of power and control systems for prototyping RF communication modules, ultrasonic, magnetic, or RF-beacon sensor systems
  • Firmware development for embedded sensor systems
  • Development of mobile applications processing real-time RF data and system-level applications for single board computers.
  • Data analysis using AI methodologies
  • C/C++/Python programming

Desired Coursework: EECS 216, EECS 250, EECS 270, EECS 280, EECS 281, EECS 282, EECS 381, EECS 382, EECS 453, EECS 492



Civil Maps

Civil Maps

San Francisco, CA
Fall 2016-Winter 2017


Villeurbanne, France
Fall 2016-Winter 2017


San Francisco, CA
Fall 2017-Winter 2018


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