2023 Summer Research Program Virtual Open House

The 2023 WINLAB Summer Internship Open House took place on Thursday August 10th, 2023, offering a platform for students to present the results of their dedicated efforts over the past 10 weeks.

A total of 79 students participated in the program, comprising 8 graduate students, 52 undergraduate students, and 19 high school students. These aspiring researchers showcased a diverse range of projects, providing insights into the program's extensive reach and impact.

The event was not only an opportunity for the students to exhibit their hard work but also a chance for attendees to engage in meaningful discussions about the projects. The open dialogue fostered a constructive exchange of ideas and perspectives.

The success of the Summer Internship Program wouldn't have been possible without the generous support of the ​NSF REU program and a donation from ​nVerses Capital. Their contributions played a crucial role in empowering these young minds to explore, innovate, and develop valuable skills.

Presentations and Posters

Distributed Data Infrastructure
Evaluating 5G/6G Wireless
Security in Artificial Intelligence
Robotic Iot SmartSpace Testbed
Developing and Testing Vehicular AI Agents
Smart Intersection Situational Awareness
Resilient Edge-cloud Autonomous Learning with Timely Inferences
Correlations between Weather Patterns and NYCMesh Network State
mmWave Measurements for Joint Sensing and Communications
Self-Driving Vehicular Project
AR Mural
Hive Monitoring
Neural Networks for Feature Analysis
First Person View Self Driving Car
Low Latency Camera

Thursday, August 10th, 2023

Poster		Project Presentation
Distributed Data Infrastructure Anna KotelnikovUG, Keshav SubramaniyamUG, Jason Zhiyuan ZhangUG, Gyana Deepika DasaraGR, Samyak AgarwalGR
(PDF)		(PDF ) (​Presentation Recording )
Evaluating 5G/6G Wireless Aleksa SamardzijaUG, Jeff AcevedoUG, Nikhil SampathUG, Sreeram MandavaUG, Stanislav CemanUG, Sanskar Jagdish ShahGR, Ryan LinUG, Steve ShinUG, Xoua ThaoUG
(PDF)		(PDF ) (​Presentation Recording )
Security in Artificial Intelligence Damon LinUG, Jacob MorinUG, Rut MehtaUG, Ethan LungHS
(PDF)		(PDF ) (​Presentation Recording )
Robotic Iot SmartSpace Testbed Katrina CelarioUG, Matthew GrimalovskyUG, Jeremy HuiUG, Julia RodriguezUG, Michael CaiHS, Laura LiuHS, Jose RubioHS, Sonya Yuan SunGR, Hedaya WalterGR
(PDF)		(PDF ) (​Presentation Recording )
Developing and Testing Vehicular AI Agents Aditya Kaushik JonnavittulaGR, Eddie WardUG, Romany EbrhemUG, William ChingUG, Donald YubeatonUG, Vibodh SinghUG, Haejin SongUG
(PDF)		(PDF ) (​Presentation Recording )
Smart Intersection Situational Awareness Heneil PatelUG, Peter WilmotUG, Eleonore PichonUG
(PDF)		(PDF ) (​Presentation Recording )
Resilient Edge-cloud Autonomous Learning with Timely Inferences Haider AbdelrahmanUG, Yunhyuk ChangUG, Lakshya GourUG, Tanushree MehtaUG, Shreya VenugopalGR
(PDF)		(PDF ) (​Presentation Recording )
Identifying Correlations between Weather Patterns and NYCMesh Network State Zachary Hine, Dror Jacoby and Shuyue Yu
(PDF)		(PDF ) (​Presentation Recording )
mmWave Measurements for Joint Sensing and Communications David ChenHS and Timothy WangUG
(PDF)		(PDF ) (​Presentation Recording )
Self-Driving Vehicular Project Adarsh NarayananUG, Brandon ChengUG, Christopher SawickiUG, Joshua MenezesUG, Ruben AliasUG, Tommy ChuUG, Aleicia ZhuHS, Ranvith AdullaHS, Arya ChhabraHS, Suhani SenguptaHS
(PDF)	(PDF)	(PDF ) (​Presentation Recording )
AR Mural Alexander ClarkeUG, Arya ShettyUG, Nicholas ClarkeUG, Pavan datta Vedire ReddyUG, Ana ObradovicHS
(PDF)		(PDF ) (​Presentation Recording )
Hive Monitoring Sarah BenedictoUG, Tate SparksUG, Evan KohutUG, Shrinidhi KesavanUG, Sonia MalhotraHS, Ben YuHS, Andrew MartinHS
(PDF)		(PDF ) (​Presentation Recording )
Neural Networks for Feature Analysis Mayank BaradUG, Daksh KhetarpaulUG, Katherine LewUG
(PDF)		(PDF ) (​Presentation Recording )
First Person View Self Driving Car Adam StrubHS, Divya KrishnaHS, Elliot LiHS, Mei Mei CastranovaHS
(PDF)		(PDF ) (​Presentation Recording )
Low Latency Camera Brayden CasarenUG, Sebastian Bradley ClarkeUG, Rohit KarthickeyanHS, Ayush IyerHS
(PDF)		(PDF ) (​Presentation Recording )

Notes

• GR - Graduate student
• UG - Undergraduate student
• HS - High School student