2019 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 Tuesday May 28th and end with the final presentation on Friday, August 16th.

 

To apply for the 2019 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 2019 or later and complete the following five steps:

 

  1. Complete the application form.
  2. Obtain a copy of your transcript.  If you are a Rutgers student, an unofficial copy is sufficient.
  3. 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 since the WINLAB faculty will be asked for input regarding any student who lists them as a reference.
  4. 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.
  5. Prepare a CV/resume.
  6. Submit the application electronically as an email with the above transcript, essay and CV attachments to: internship (AT) winlab (DOT) rutgers (DOT) edu no later than March 22nd.  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 7th.

2019 Research Projects

Project
Pre-Requisites
Remote multi-robot extension to ORBIT: This project involves building a localization and mapping system for roomba robots to perform autonomous navigation.
OS: Linux
Software: Python, C/C++
Multi-agent 3D mapping: This project involves using intel realsense depth sensors and roomba robots to perform 3D mapping of a room by combining the maps of multiple robots.
OS: Linux
Software: Python, C/C++
AR information system: use an overlay to display information about the radio environment (IoT, ORBIT, ...)
OS: Linux, Windows
Software:C#, C/C++, Java
Educational Virtual Reality Escape Rooms: A game based on a set of virtual rooms in which players will have to solve a STEM related problem before being able to move to the next one – similar to the popular “escape rooms” experience. OS: Linux, Windows
Software:C#, C/C++, Java
Automatic air quality conditioning based on occupancy and weather:: implement open source air filter using 3D printer and program it with smart control algorithms that filter the air and improve indoor air quality, proactively. OS: Linux
Software:Python, C/C++
Activity classification in an office environment using suite of sensors used together:: Can we infer how many people are in the office, where they are, and what kind of activity they are engaged in (office work, eating, talking, standing, sitting). OS: Linux
Software:Python, C/C++
Intelligent 5G Cellular Environment: As the users are becoming more aware of the cellular technology he/she will look for advanced features to support 5th Generation mobile technology. Hence, our aim will to be provide state-of-the-art software and services for any type of network to help communication service providers and large enterprises deliver on the promise of 5G. The intensive project will give valuable practical experience and illustrate implementation of these technologies for enhanced user experience. OS: Linux
Software: C/C++, Python
Tools: ns3 (optional)
Self-Driving Vehicular Environment: Self-driving, autonomous vehicles is understanding when to hand off control to driver. This project will investigate autonomous vehicles control system changing from a safe autonomous mode to a manual mode, and back again. Students will develop a deep neural network (DNN) and use computer vision techniques to autonomously drive a model car around a simple track. They will also incorporate a slew of range-finding sensors, intersection infrastructure, and develop spatial models to reason about vehicular safely. Finally, the group will incorporate a fusion model to merge the DNN driving control with the safety model to hand control to the driver before a collision occurs. OS: Linux
Software:Python, C/C++
Investigating the Biological Impacts of Radio Spectrum Transmissions: This project will investigate how the recent explosion of Radio Frequency (RF) signals in the environment can have biological impacts. Recent work has shown bird navigation is impacted by megahertz frequencies, the the investigation of the impacts of possible RF pollution is a concern. Honeybees are one of the few species which have been shown to have electromagnetic detection mechanisms sensitive enough to navigate using the Earth's magnetic field, so this project will program software radios and develop an apparatus to investigate if honeybees can detect a range of frequencies, from the megahertz used by AM radios to 5 GHz used WiFi. OS: Linux, Embedded programming
Software: C/C++, Python
Deep Learning Deployment in Embedded Systems: Deep learning has delivered its powerfulness in many application domains. However, the deployment of deep neural networks (DNNs) on mobile devices or embedded platforms has been largely constrained due to the requirements of intensive computation and storage. This project will study how to revise DNN architecture to make it suitable for mobile/embedded platforms with reduced asymptotic complexity of both computation and storage. OS:
Software:
High-throughput Inaudible Acoustic Communication: This project will develop an acoustic communication system that can achieve inaudibility and high throughput simultaneously by using the non-linearity of microphones and OFDM multiplexing technique. OS:
Software:
mmWave based Gesture Recognition: mmWave is an extremely valuable sensing technology for detection of objects and providing the range, velocity and angle of these objects. This project will develop algorithms to detect and classify a set of human hand gestures to enrich the way of human-computer interaction. OS:
Software:
Dangerous Object Detection Using mmWave: mmWave has a short wavelength and high directionality. Such wireless signals are good for detecting material and shape of the objects. This project will develop a system to detect the existence of suspicious objects inside baggage by utilizing the mmWave. OS:
Software:
Radio Spectrum Characterization: The past 20 years has seen an explosion of radio communications, from cell-phones, to WiFi and bluetooth. Characterizing who is sending and receiving in a given space, e.g. a building, is a challenging task, and has many applications, ranging from security to building energy management. In this project, the students will program a set of software defined radios to list all the transmitter types in a given building, including their frequencies, protocols, packet destinations, as well as the likely locations of the transmitters OS: Linux
Software: C/C++, Python