MS Students:

N/A

Prospective Students:

We are always on the lookout for highly motivated graduate students. The WiN-ML group is interested in the holistic design of distributed ML algorithms in wireless networks and developing physics-aided learning solutions for next-generation wireless networks. The team usually looks for students who will, ideally, work in one of the following two thrusts:

• Thrust-1: fundamental research problems of privacy-preserving distributed machine learning in wireless networks

• Thrust-2: fundamental research problems of 6G wireless networks using ML and optimization

Note: If you are interested in working with us, please feel free to send an e-mail with "Prospective Student: Program Name, Starting Semester" in the subject line and with your CV, transcripts, and up to 3 representative publications at 📧 ferdous.pervej@usu.edu, clearly indicating your research interest(s) and whether you are looking for funding (in terms of graduate assistantship) from the group/USU. While I usually try to read e-mails from prospective students, I may not be able to reply to all of them due to time constraints: my apologies in advance. Before writing me, please check the following requirements:

Minimum Requirements:

• A bachelor’s degree in electrical/communication/telecommunication/computer engineering or any closely related fields 

• Willingness to learn and grow

• Solid foundations in linear algebra and stochastic process

• Basic understanding of wireless communication and willingness to dive deeper   

• Basic understanding of optimization and willingness to dive deeper

• Basic understanding of different classical machine learning algorithms and willingness to dive deeper

• Good at Python programming and have experience with deep learning libraries like PyTorch and/or Tensorflow  

• Proven track record: no prior publication is necessary as long as your transcripts and CV speak for yourself

Preferred Qualifications:

• A prior MS degree in electrical /communication/telecommunication/computer engineering or any closely related fields  

• Good knowledge of wireless communication 

• Good knowledge of optimization

• Good knowledge of machine learning 

• Prior experience with developer kits (e.g., NVIDIA Jetson developer kits)