Students must complete the requirements of both programs (MDP and MIDAS) in order to receive MIDAS Practicum credit.
- Students are responsible for identifying appropriate scope / content for individual work within the context of their MDP Project.
- Materials developed within group work may be utilized within the individual Practicum Report to provide context of the overall project.
- There must be sufficient individual work to justify the graduate level practicum.
- The scope/content of the proposal must be approved by the MDP Faculty Mentor / Faculty PI
- Students must submit their practicum proposal to MIDAS Director, Prof. Ivo Dinov, and obtain approval prior to the first day of class in the 2nd term of the MDP Project (Fall semester of the project).
- Student Practicum reports will be evaluated by Prof. Dinov on a Satisfactory/Unsatisfactory basis; Students must receive a grade of ENGR 599 with B- or better in order to receive a Satisfactory Report grade.
- Participation in “JumpStart” workshop (early January).
- Successful completion of all project assignments (Design Reviews, Peer Evaluations, Workshops, Poster Sessions, etc.).
- Consistent, successful, weekly team participation
- Average 8 hours effort / week
- Individual Practicum results may be included in the group work of the MDP Project Team.
|Term||Course Enrollment / Actions||Grade end of Winter Term||Grade end of Fall Term|
|Winter Semester||ENGR 599, 2 credit hours||Grade: “Y” – Placeholder Grade for Winter Term. This converts to a letter grade at the end of the Fall Term.||Letter Grade for ENGR 599, 2 credit placed in the transcript in Winter term|
|Summer||Submit proposal for practicum to MIDAS Director (currently Prof. Ivo Dinov)|
|Fall Semester||ENGR 599, 2 credit hours||Letter Grade for ENGR 599, 2 credits placed in the transcript in Fall Term.|
The following 2019 MDP projects were pre-approved by MIDAS to fulfill Practicum Credit:
- Bosch Path Planning: Robust Path Planning for Automated Vehicles
- GM Autonomous Vehicle: Determine Duty Cycle for Autonomous Vehicle with a Hybrid Drive Unit
- GM Waste Recovery: Engine Heat Waste Recovery
- Northrop Grumman Predictive Analytics: Using Predictive Analytics to develop better understanding of Opioid Use, Addiction and Treatment
- Parkwhiz: Dynamic Pricing for On-Demand Parking
- Proquest Machine Learning: Sentiment Analysis and Machine Learning for Measuring Ensemble Viewpoint Coverage
- Proquest Artificial Intelligence: Auto-Indexing Medical References using Artificial Intelligence
- Together Chicago: Chicago Social Asset Mapping Tool
- Union Pacific: Costing and Profitability Reporting
- UTC Aerospace Systems: Surface Navigation Aid for Commercial Aircraft