​Dr Megan Maas is an assistant professor in Human Development and Family Studies at Michigan State University. Her research investigates adolescent and emerging adult sexual and romantic experiences, and how parents, schools, and media can impact those experiences for better and for worse.

For over 13 years, Dr Maas has served as a keynote speaker, workshop facilitator, and expert contributor on issues revolving around adolescent sexuality, the sexualization of girls, pornography use, and parent-child communication about sexuality at universities and organizations across the country.

Dr. Maas has provided consulting on several media literacy programs, parenting programs, documentary series, sexuality education programs, and sexual misconduct policy development. She has also served as an expert witness on a revenge pornography case.

Alexander is assistant professor of Neuroscience and Computer Science at the University of Texas at Austin. His research uses computational methods to model how the brain processes language and represents meaning. Alexander is also interested in fMRI technology and data visualization.

In 2016, he authored a paper that explored the relationship between language meaning and brain activity. Through his research, Alex demonstrated that models based on the semantic properties of words can effectively predict functional magnetic resonance imaging (fMRI) responses to naturally spoken narrative stories. Additionally, he conducted a thorough analysis of these models to determine the specific semantic properties represented in various brain areas, resulting in detailed maps of semantic representation across the human cortex.

Alex discovered that these maps exhibit remarkable consistency across different individuals. To further enhance his findings, he developed a generative model of cortical maps to create a group atlas from the collected data, and created a web-based 3D viewer to facilitate the exploration of this dataset.

He completed his Ph.D. and postdoctoral studies at the University of California, Berkeley, working in Dr. Jack Gallant's laboratory within the Helen Wills Neuroscience Institute. Prior to this, he pursued both a bachelor's and master's degree in computation and neural systems (CNS) at the California Institute of Technology (Caltech).

Dr. Walid Saad is a distinguished academic and researcher in the field of electrical and computer engineering. He earned his Ph.D. degree from the University of Oslo in 2010 and currently holds the position of full Professor at the Department of Electrical and Computer Engineering at Virginia Tech.

Dr. Saad is the leader of the Network sciEnce, Wireless, and Security (NEWS@VT) laboratory, which is part of the esteemed Wireless@VT research group. He also serves as the Wireless NextG Faculty Lead for Virginia Tech's Innovation Campus, demonstrating his commitment to advancing wireless technologies.

His research interests encompass wireless networks (5G/6G/beyond), machine learning, game theory, security, UAVs, semantic communications, cyber-physical systems, and network science. Dr. Saad's contributions have been recognized through his election as a Fellow of the IEEE.

Throughout his career, Dr. Saad has received several notable awards, including the NSF CAREER award in 2013, the AFOSR summer faculty fellowship in 2014, and the Young Investigator Award from the Office of Naval Research (ONR) in 2015. He has also co-authored eleven conference best paper awards at prominent conferences such as IEEE WiOpt, ICIMP, IEEE WCNC, IEEE PIMRC, IEEE SmartGridComm, EuCNC, IEEE GLOBECOM, IFIP NTMS, and IEEE ICC.

The IEEE Communications Society has honored Dr. Saad with prestigious awards, including the Fred W. Ellersick Prize in 2015 and 2022, the IEEE ComSoc Best Young Professional in Academia award in 2017, the IEEE ComSoc Radio Communications Committee Early Achievement Award in 2018, and the IEEE ComSoc Communication Theory Technical Committee Early Achievement Award in 2019. He has also contributed as a co-author to the 2019 IEEE Communications Society Young Author Best Paper and the 2021 IEEE Communications Society Young Author Best Paper.

Dr. Saad actively contributes to the academic community through his editorial roles. He serves as an Area Editor for the IEEE Transactions on Network Science and Engineering and the IEEE Transactions on Communications. Additionally, he is the Editor-in-Chief for the IEEE Transactions on Machine Learning in Communications and Networking.