Industrial Engineering

Students may apply to one or more of the below projects, indicating this in their statement of interest, or they may apply for "ABE: General," indicating in their statement of interest their skills and background and some faculty with whom they would be interested in working.  ABE Faculty List

Title Name Email Project Name Project Description Requirements
Asst. Prof. Vaneet Aggarwal vaneet@purdue.edu Straggler Mitigation in Cloud Computing Cloud computing involves running large jobs on the distributed servers. The processing time of the jobs are uncertain and so is the speed on the servers. Due to these, some jobs may be stragglers, where they take unexpectedly large amount of time to complete. In our group, we work on both efficient redundancy strategies (in form of erasure codes) as well as the queueing aspects to decide when and how many redundant copies to start. We also work on non-convex optimization algorithms where the convergence guarantees are important for different applications.  Strong mathematical and coding background, with a preferred major in EE/CS/Math/Stats. 
Asst. Prof. Vaneet Aggarwal vaneet@purdue.edu Machine Learning In our group, we work on theoretical as well as applied aspects of machine learning. In terms of theory, we work on finding guarantees for algorithm convergence and the gaps to the optimality. In terms of applications, we work on video streaming, cloud computing, vehicle ridesharing etc. The research in this area is timely since this forms the basis of the innovations in the next decade, where autonomous vehicles impact the mechanisms for autonomy in computation and ridesharing. The summer intern can choose either the theoretical or the applied side to do the project. CS/EE/Math/Stats backgrounds are preferred.
Assoc. Prof. Juan Wachs jpwachs@purdue.edu Autonomous robotic surgery using Deep Learning This research focuses on the “Medical Robotics Research” topic area. Within this area we will address the following objectives: 1) extend to full automation when deemed necessary; 2) develop semi-autonomous robotic assistant protocols; and 4) develop models for knowledge representation of semi-autonomous medical behaviors.
The student contribution will be data collection using the robot while performing a simulated procedure and training Deep Neural Networks architectures.
* Good programming skills Python
* Experience in machine learning
* Experience in computer vision is a plus
* Experience in robotics is a plus.

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