Summer Internship

2022 WINLAB Summer Internship

The WINLAB Summer Internship Program offers full and part-time summer internships in a university research setting to highly talented undergraduate and graduate students.  The main goal of the program is to provide students with a real-world, team-based research experience in various topics related to wireless technologies.  Each intern joins an active research group consisting of a mix of graduate and undergraduate students with at least one mentor who is a faculty member.  All projects are designed to be completed within the duration of the program, but can also be extended for eligible students to the following academic year.  Each week students are expected to report on the progress of their work in a summer research group meeting.  At the conclusion of the program, interns submit a report and are required to give a final presentation on the research results.  A limited number of full-time internship students receive a monthly stipend plus an on-campus room in designated Rutgers dormitories (available for non-Rutgers, full-time interns ONLY!).  Additional students will be offered part-time (hourly) summer employment. The opportunity for non-paid participation may also exist once the paid positions are distributed. Should you be interested in one of those positions if not chosen for a paid position, please make sure to indicate that on your application. The program will begin with an introductory meeting on Friday May 27th and end with the final presentation on Thursday, August 4th.

To apply for the 2022 WINLAB Summer Internship Program, students must be currently enrolled full time in a college or university, be eligible to work in the US and have an anticipated graduation date of 2023 or later and complete the following five steps:

  1. Obtain a copy of your transcript.  If you are a Rutgers student, an unofficial copy is sufficient.
  2. Please obtain two letters of reference.  Letters of reference should be submitted to internship (AT) winlab (DOT) rutgers (DOT) edu by faculty at your home institution or past job supervisors who can assess the quality of your academic performance and research potential. If you are a Rutgers student and will be using a WINLAB professor(s) as your reference(s), you do not need a letter of reference from them.  Simply list the name of the professor(s) in the reference section of the application form since the WINLAB faculty will be asked for input regarding any student who lists them as a reference.
  3. Write a brief essay (no more than one page) on why you would like to join the program, what strengths you will bring to the program and what you hope to achieve by being included in the program.  Please also see the list of research topics at the bottom of this page and advise which projects peak your interest.  While we cannot promise that you will be assigned to the project you ask for, we will make an effort to put accepted students in their areas of interest.
  4. Prepare a CV/resume.
  5. Complete the application form. with the above transcript, essay and CV uploaded no later than April 3rd.  Incomplete applications or those received after the deadline will be considered only after the on-time complete applications have been processed.The selection of interns will be determined by the WINLAB faculty members.  All accepted students will be notified by email of their acceptance into the program by April 15th.

2022 Summer Internship Dates

Applications Due: April 3
Notifications: April 15 (postponed to April 19 due to holidays)
Internship Starts: May 31
Internship Ends: Aug 5

Project Pages

Past Research Topics

2022 Research Projects

Project Pre-Requisites
Distributed Spectrum Sensing and Channel Assignment: use a collection of software defined radios (SDRs) to detect spectrum occupancy and perform channel usage coordination among number of radio systems.
OS: Linux Software: C/C++, Python
Smart Intersection Situational Awareness: Use inputs from lidars, 2d and 3d cameras and other sensors to create a 3D point-cloud of the intersection area.
OS: Linux Software: C/C++, Phyton
Self-Driving Vehicular Project: Assemble and train miniature autonomous vehicles to run in the miniature smart city environment. Low latency networks for vehicular control. This project will use specialized low latency cameras and radios to operate remote model cars. Design and implement self-driving algorithms using machine learning libraries in python. Design behavior that will allow the vehicles to react realistically to other cars and props in the smart city environment, and work with the testbed infrastructure to use external data from the intersection to improve performance. OS: Linux Software:Python, C/C++
Smart City Traffic Simulator: Work on virtual reality smart city environment using Unity. Connect VR environment to traffic simulation software to generate realistic car behavior in the smart city. Work with physical smart city environment to use real car behavior as input to the simulator. OS: Linux Software: C/C++, Python
Adversarial Machine Learning Against Voice Assistant Systems: This project aims to study the security of voice assistant systems under adversarial machine learning. Adversarial learning algorithms can generate adversarial audio samples to serve as the input of voice assistant systems, so as to fool the machine learning models in the system. In this project, students will focus on the white-box attack in the digital domain by generating adversarial samples using adversarial machine learning algorithms to attack a speaker recognition system based on X-Vector. The students will learn Python with Tensorflow Library. OS: Linux Software: Python
AR Mural: Develop augmented reality based art allowing users to contribute paintings, photos, videos or notes and leave them for other visitors to the set of locations.
OS: Windows Software: Unity, C#
Mobile mmWave Platform: Develop an indoor robotic platform for conducting mobile mmWave experimentation. The ROS based platform has to follow user-specified paths.
OS: Linux Software: C/C++, Python
Channel Measurement Campaign: Develop an SDR based platform for channel measurements on COSMOS/ORBIT testbeds and perform a series of measurement campaigns at various locations.
OS: Linux Software: VHDL/Verilog, C/C++, Phyton
Agricultural Sensing and Monitoring: Wireless sensing has the potential to reshape agriculture. This project will attach a camera and microphone to a honeybee hive. The system will be engineered to use little energy so it can be solar powered. The system will use an AI to count honeybees and measure hive activity via sound. A neural network will send a compressed representation back to Winlab via a LoRA radio connection and then reconstruct the number of bees and hive activity.
OS: Linux Software: Python, C++
Agricultural Sensing and Monitoring: Wireless sensing has the potential to reshape agriculture. This project will attach a camera and microphone to a honeybee hive. The system will be engineered to use little energy so it can be solar powered. The system will use an AI to count honeybees and measure hive activity via sound. A neural network will send a compressed representation back to Winlab via a LoRA radio connection and then reconstruct the number of bees and hive activity.
OS: Linux Software: Python
Real-time Motion Planning for Robotics: .
OS: Linux Software: Python
Security vulnerabilities study on indoor wireless systems:This project aims to study the vulnerability of wireless localization systems under interference signals. In this project, students will learn and implement a wireless localization system. They will utilize USRP devices to interfere with the localization system in real time to study the system vulnerability. The students will learn Python with Tensorflow Library; GNU Radio(for programming USRP to generate attack signals).
OS: Linux Software: Python
Low-power object detection on FPGAs: .
OS: Linux Software: Verilog,VHDL