Artificial Intelligence (AI) is everywhere and you may not even know it. It is even applied in the most obvious to the most bizarre of fields: from natural language processing in Alexa to electronic dream generation in Dreamscape. With AI improving and gaining prominence at an exponential rate, students should gain early access to explore this technology. Our mission is to empower students to explore AI and its intersection with a diverse range of applications. We provide experiential learning opportunities through interactive lectures, monthly guest presenters, and workshops to students beyond our school.
Aditya Sirohi
Niru Vijayakrishnan
Saj Agarwal
Rhea Malik
Speaker: Polina Golland, MIT
Topic: Learning to Read X-Ray via Machine Learning
About the Speaker: Dr. Polina Golland is a Henry Ellis Warren Professor of Electrical Engineering and
Computer Science at principal investigator in the CSAIL at MIT. In this talk, Dr. Golland discusses her lab's
current work to detect and characterize pathology in chest x-ray images using machine learning. She discusses
methods and clinical applications, as well as possible future directions for this project.
Speaker: Dr. Jason Moore — Perelman School of Medicine, University of Pennsylvania
Topic: Accessible Artificial Intelligence for Data Science
About the Speaker: Dr. Moore is an Edward Rose Professor and Senior Associate Dean for Informatics and
Director, Institute for Biomedical Informatics. His research focuses on developing, evaluating, and applying
AI and machine learning to understand and improve human health. His lab is interested in enhancing the
prediction, diagnosis, prevention, and treatment of common human diseases.
Speaker: Dr. Avi Ma’ayan — Icahn School of Medicine at Mount Sinai, New York
Topic: Data Integration for Machine Learning in Drug and Target Discovery
About the Speaker: Dr. Avi Ma’ayan is Mount Sinai Endowed Professor in Bioinformatics, Professor in the
Department of Pharmacological Sciences, and Director of the Mount Sinai Center for Bioinformatics. He
utilizes statistical mining and machine learning to better understand how intracellular regulations affect
different functions. Dr. Ma’ayan’s research team has developed several software systems to help experimental
biologists. Recently he developed a shared database to aid scientists in finding a cure for COVID-19.
Speaker: Dr. Daniel Rock — Wharton, University of Pennsylvania
Topic: Job2Vec: Learning a Representation of Jobs
About the Speaker: Professor Daniel Rocke is an assistant professor of Operations, Information, and
Decision at Wharton. He researches the impact of AI and other digital technologies on economics. He recently
studied the occupations that are most exposed to machine learning and measured the value of AI skill sets.
His research has been featured in the New York Times, Wall Street Journal, Bloomberg, and more!
Speaker: Alex Miller — Ph.D. Student at Wharton, University of Pennsylvania
Topic: Personalization in e-commerce with causal machine learning
About the Speaker: Alex Miller is a Ph.D. Student in The Wharton School, University of Pennsylvania. In
his talk, Alex discussed how he uses machine learning to study techniques in online personalization. Alex
also discussed how to utilize machine learning to create effective e-commerce marketing campaigns. To top it
all off, he described how he got involved in this field and offered advice on how you can apply AI to your
area of interest.
Speaker: Lindsley Medlin — Chief Operating Officer, Pitlane Strategies LLC
Topic: Artificial Intelligence: Opportunities and Challenges
About the Speaker: Lindsley Medlin serves as an advisor for small and mid-sized companies to help them
grow. Mr. Medlin is a certified Blockchain and Ethereum expert. His talk addressed new and upcoming
opportunities within the field of AI. Moreover, we also discussed current and potential challenges faced
with the developments of artificial intelligence.
Speaker: Dr. Eunsu Kang — Carnegie Mellon University, Pittsburg
Topic: Welcome our New Neighbor, Creative Machines
About the Speaker: Eunsu Kang is an artist, a researcher, and an educator who explores the intersection
of art and machine learning as well as the possibility of creative AI. After more than 100 art exhibitions
around the world, her works have transformed into interactive and interdisciplinary art projects. All ten of
her past solo shows, consisting of individual or collaborative projects, were invited or awarded. She has
won the Korean National Grant for Arts three times. A few years ago she left her tenured art professor
position to design and teach new courses at the Machine Learning Department of Carnegie Mellon University.
Data shows 40% of the USA is digitally literate. Even in the Philadelphia area, 80% of schools lack classes on basic computational skills, let alone coding. This invaluable skill is vital for students to develop at an early age as it is critical for our near digital future. Further, without diverse involvement of low-income and underrepresented communities, technology (like AI) will not become inclusive. This youth-led project aims to increase digital literacy and combat learning loss in the Philadelphia region through workshops, peer tutoring, and guest lectures. Our mission is to help underserved youth gain a standing within the growing digital world.
Our Project is supported by two major grants:
Global Youth Mobilization Local Solutions Grant:
The TDL project is supported by an international grant provided by Global Youth Mobilization (partners
include WHO, UN Foundation, and Big 6 Youth Organizations) to address a global problem with a local solution.
Center for Schools and Communities Grant:
This is a state grant provided by the Center for Schools and Communities for this service project. This
group will assist us in initiating contact with sponsors and local communities.