MIT Undergraduate Research Technology Conference
October 8 - 10, 2021

2021 Dates

Early Paper Submission Deadline July 11, 2021
Early Notification of Acceptance July 31, 2021
Regular Paper Submission Deadline July 31, 2021
Regular Notification of Acceptance August 21, 2021
Poster and Lighting Talk Submission Deadline August 29, 2021
Poster and Lightning Talk Acceptance Notification September 5, 2021
Conference Dates October 8, 2021 - October 10, 2021


Over the past 6 years, URTC has grown its influence, reaching students internationally and receiving 234 submissions last year. Not only will sponsors receive significant exposure to talented individuals from MIT and other top universities, but sponsors also have the opportunity to present a lightning talk, have a booth, and gain additional exposure through the distribution of t-shirts and swag. If interested, please email us at!

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2020 Schedule
All times in EDT

Tech Talk Descriptions Conference Schedule
Paper Presentation Schedule Poster Presentation Schedule Lightning Talks Schedule

Paper Abstracts

AM Track 1 AM Track 2 AM Track 3 PM Track 1 PM Track 2 PM Track 3

Poster Abstracts

Session #1: Room A Session #1: Room B Session #2: Room A Session #2: Room B

Lightning Talks Abstracts

Lightning Talks





All times in EDT. Click each event to view details.

Friday, October 9

Computing at the edge (near the sensor) is preferred over the cloud due to privacy and/or latency concerns for a wide range of applications including robotics/drones, self-driving cars, smart Internet of Things, and portable/wearable electronics. However, at the edge, there are often stringent constraints on energy consumption and cost in addition to the throughput and the accuracy requirements of the application. In this talk, we will describe how the joint design of algorithms and hardware can be used to reduce energy consumption while delivering real-time and robust performance for applications including deep learning, computer vision, autonomous navigation/exploration and video/image processing.

Pandemics spread before innocent people infect other innocent people. This required a bottom up solution that can capture, analyze and act on the graph of social activities. Can today’s youth use open source open standard solutions to address these challenges? PathCheck Foundation has brought together talented young innovators from all around the world. This is a story about those changemakers.

From machine learning and computer vision to robotics and natural language processing, the application of data science and artificial intelligence is expected to transform healthcare. At present, a key evaluation metric for machine learning in healthcare applications is accuracy. But just because an algorithm is deemed accurate does not mean it will support fairness in healthcare applications. In an ideal world, only individual patient health and disease factors would determine — and guide prediction of — clinical outcomes. However, studies have repeatedly demonstrated that this is far from the case. Data routinely collected in the process of care are heavily influenced by long-standing social, cultural, and institutional biases. Unless the underlying inequities in our communities are addressed, algorithms will perpetuate, if not magnify, existing health disparities.

As we are leveraging data for making significant decisions that affect individual lives in domains such as health care, justice, finance, education, marketing, and employment, it is important to ensure the safe, ethical, and responsible use of AI. Data scientists know that no longer accuracy is the only concern when developing machine learning models, interpretability and fairness must be considered as well. In order to make sure that machine learning solutions are fair and the value of their predictions easy to understand and explain, it is essential to build tools that developers and data scientists can use to assess their AI system’s fairness and mitigate any observed unfairness issues. This session will focus on Responsible Machine Learning, by explaining the following aspects and tools: - Fairlearn: an open-source Python package to assess AI system’s fairness and mitigate any observed unfairness issues in your machine learning models. - InterpretML: an open-source Python package that helps you understand your model's global behavior, or understand the reasons behind individual predictions.

I started LocoRobo in 2015 with a simple mission -- bring educational robots to every classroom in the US by 2020. It is 2020 and we are nowhere close to achieving that naive mission. But we have survived and by all metrics, we have thrived. In this talk, I will share some secrets that have guided us through the ups and downs of the US ed-tech market for over 5 years now. I will also share the best and the worst entrepreneurial decisions that we made during this rewarding journey.

Before graduating from X as Waymo, Google’s self-driving car project had been using custom sensors such as lidars, radars, and cameras for several years. In their 5th generation, the sensors are designed to meet the challenging requirements of moving people and goods safely and efficiently in dense cities and on highways. Our goal is to make them affordable while meeting the performance needed for driverless operation in various applications and weather conditions. This talk will review some history of the project and describe a few use-cases for sensors and machine learning on Waymo vehicles.

Saturday, October 10

We, as robot engineers, have to think hard about our role in the design of robots and how it interacts with learning, both in "the factory" (that is, at engineering time) and in "the wild" (that is, when the robot is delivered to a customer). I will share some general thoughts about the strategies for robot design and then talk in detail about some work I have been involved in, both in the design of an overall architecture for an intelligent robot and in strategies for learning to integrate new skills into the repertoire of an already competent robot.

Ideas come from everywhere, the trick is getting them into the world. One idea leads to another. This session will follow the origin story of Microsoft’s Project 15 Open Platform for Conservation and Ecological Sustainability. Internet of Things (IoT) drives sustainability as sensors are at the center of gathering data to generate advanced insights. The opportunity that IoT and Machine Learning (ML) bring us to re-invent existing processes and innovate on new ideas is immense. Join us to learn more about Project 15 and leveraging IoT and ML for good.

Internet of Things (IoT) solutions have known patterns of development. Come learn how the different components of a holistic IoT solution incorporating machine learning fit together leveraging Azure IoT. Daisuke will move from learning the basic patterns into real live examples and demo the Project 15 Open Platform for Conservation and Ecological Sustainability. Bring your questions as Daisuke brings his 23 years of experience to the session to share how to turn ideas into innovation.

Cloud Computing has spread like a marketing virus. But what is cloud computing and How does it work? What are different service models and where do they fit the most? You will also learn why CXO considering Cloud Computing and how does it help them. What new skill sets are required to meet the job? market. When you are done with this webinar you will much clear understanding of Cloud Computing which will help you develop you career with right skill sets.

Graduate School Admissions Session: Come learn about the graduate school admissions process at MIT and beyond. Noelle Wakefield, PhD, Assistant Director of Diversity Initiatives & MSRP at the Office of Graduate Education at MIT and Katherine Mizrahi (4th-year materials science Ph.D. candidate and MIT course 3 alumna) will be giving a talk covering all topics regarding graduate school admission!

Sunday, October 11

Join us for a panel discussion with inspiring women leaders in the tech field hailing from OpenTable, Waymo, Morgan Stanley, and MIT! Listen as they share their experiences, and learn how they entered and navigated the tech space, as well as how they overcame challenges and paved their way to successes. You’ll leave feeling energized and with some practical advice and thoughts on the future of tech to help guide your own career decisions. This event is open to all!

Join us for a panel discussion with inspiring tech leaders as they share about their experiences transitioning into life after college and beyond! There’ll be a breadth of experiences, from life as a White House Presidential Innovation Fellow to working at Amazon, Google Brain, and BAE Systems. Learn about how our panelists shaped their career paths, including any changes that came their way. You’ll leave with insights that can help with your own transition to the “real world”!

1. Biological and Biomedical Engineering (BioEECS)
2. Circuits, Materials, and Nanotechnologies
3. Computer Systems, Theoretical Computer Science and Mathematics
4. Machine Learning / Artificial Intelligence (AI)
5. Robotics and Controls
6. Security and Communications
7. Space Application and Technologies
8. Innovation Research


The 2021 IEEE MIT Undergraduate Research Technology Conference (URTC) brings together undergraduates from around the world to present, discuss, and develop solutions to advance technology for humanity. Students may publish papers of their school projects, research, innovations, or case studies. Conference attendees will attend a rich program with keynote speeches and technical talks featuring renowned speakers, a student design competition, and networking events. The 2021 URTC conference will be hosted in a hybrid format.

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2021 Organizing Committee

Ritik Patnaik '23

Conference Co-Chair

Meenu Singh '23

Conference Co-Chair

Cathy Yung '24

Logistics Co-Chair

Dewei Feng '24

Logistics Co-Chair

Chelsea Chen '23

Publicity Chair

Jenny Zhao '23

Sponsorship Chair

Robert Chen '23

Technology Chair

Neil Deshmukh '24

Logistics Team

Penny Zipei Tan '24

Logistics Team

Lucas Chu '23

Logistics Team

Qiong Zhou Huang '24

Logistics Team

Gianna Torpey '23

Publicity Team

Shayda Moezzi '24

Sponsorship Team

Tammy Chen '24

Sponsorship Team

Karen Liberman '24

Technology Team

Ivy Wang '22

Conference Advisor

Fiona Cai '23

Conference Advisor

Shulammite Lim '22

Conference Advisor