THE POWER OF

PENN ENGINEERING

Gig economy firms benefit from labor flexibility by hiring independent self-scheduling workers. This flexibility poses a great challenge to such firms in terms of planning and committing to a service capacity. Understanding the motivations that drive gig economy workers, therefore, is of great importance. In collaboration with a ride-hailing platform, we study how on-demand workers make labor decisions: specifically, when to work and for how long. We are interested not only in improving the prediction of the number of active workers but also in understanding how to design better incentives for them. Data-driven econometric analysis of historical work decisions and responses to incentives accounting for sample selection and endogeneity has revealed behavioral insights that can inform better incentive design.

In this talk, we explore Penn research in building (1) Safe Autonomous Vehicles: What is a driver’s license test for driverless vehicles? (2) Safe Medical Devices: How can we use computer models to speed up clinical trials with a reduced cost? and (3) Grid-responsive Energy Systems: How do we build AI for Smart Buildings?

For the first time since the early 1940s, humankind is at the cusp of a fundamentally new type of computing technology using the quantum mechanical properties of matter and energy. What this technology can enable, has the promise to take our civilization to a new level of advancement. The questions really are how do we get there and how far are we from real applications with commercial value? In this talk, Deep will provide a detailed introduction to current status and future prospects of quantum computing and related technologies.

Is education, like music, photos, and videos, infinitely and cheaply replicable? Do students actually learn online? Does online advanced education attract a diverse, non-traditional, student population? Sampath will answer these questions based on Penn Engineering’s experience in its forays into online education.

In 1987 Robert Solow quipped that "You can see the computer age
everywhere but in the productivity statistics".² Twenty years on, the quip
is still true. How does one reconcile this with the intuition that AI and
automation has changed and will change our lives in a profound way?

When will we have robots that will be able to drive cars, do our chores, and build other robots? When will AI exceed human intelligence? Will your job be automated? This talk will explore the answers to these existential questions and start a discussion on the future of our society.

What does it mean for machine learning to be privacy-preserving or fair, and how can we build algorithms that incorporate these basic social norms? We will explore how to innovate while respecting privacy concerns and without reflecting biases in algorithmic decision making, promoting transparency and trust.

Blockchain technology promises to revolutionize the way transactions are handled across many industries by allowing distributed, but synchronized, ledger system and the promise of secure transactions without a central point of failure. On the other hand, there are many important unresolved questions around protocols, security, and concurrency, particularly with the emergence of distributed embedded systems. We will discuss both the potential benefits and the challenges with these technologies.

The near-term impact of artificial intelligence has been exaggerated with claims that these technologies will automate half of all paid jobs in the world. However, the difficulties in integrating artificial intelligence into physical machines and having them interact with humans have been greatly underestimated. We will address the challenges in developing autonomous machines, particularly in creating software that is verifiably safe and trustworthy.

High school students who aspire to become engineers and computer scientists have an opportunity to engage with Penn faculty in discussions on the future of technology. This Penn-India Youth Forum will feature moderated interactive panels on the future of technology and its impact on society; and the Penn approach to engineering education and opportunities for students.

Executive Director, Reliance Industries

Tracking his journey from IITK, Penn and the GRASP Lab to the world of business and building on his learnings from building the Indian School of Business (ISB), the Young India Fellowship, Ashoka University, the Vedica Scholars Programme for Women and the Naropa Fellowship, Pramath will share a vision for the future of higher education in India and beyond.

This session will explore the investment opportunities AI opens up across India.

With new unicorns springing up constantly thanks to large investment rounds, the latest one being the 1 billion dollar investment in Swiggy, is India ready for the big game? Where do we see things going in the next 5-10 years.

Building technology businesses in India: India supports an academic and institutional environment that has produced world famous technology professionals in top management positions all over the world. This panel will talk about the opportunities and challenges of building technology businesses in India, and addresses areas such as market opportunity, global vs Indian target markets, talent acquisition and most importantly, creating and supporting a truly global innovation culture.

Today’s digital landscape is forcing traditional businesses to pivot in order to stay relevant and integrate into the everyday habits of both individuals and businesses. This is particularly evident in banking, where we are seeing a shift in the way we save, borrow, and invest, and even in the way we interact with currency. Consequently, more and more fintech startups are emerging to fill consumer needs, which is changing the financial industry and encouraging traditional banks to innovate. The panelists will discuss the rise of fintech, the integration of new and innovative technologies within financial services, and the future of digital finance.

Deep research into algorithms, complexity, and machine learning is underway at Penn. Advances in these areas promise to impact AI and Data Science technologies globally impacting every industry. This session will help us understand the opportunities and challenges of the new algorithm-centric world that increasingly envelopes us.

Building technology businesses in India: India supports an academic and institutional environment that has produced world famous technology professionals in top management positions all over the world. This panel will talk about the opportunities and challenges of building technology businesses in India, and addresses areas such as market opportunity, global vs Indian target markets, talent acquisition and most importantly, creating and supporting a truly global innovation culture.

We have spent the greater part of the day talking about trending technology topics such as blockchain, robotics, automation, drones, and AI. However, India could still have some way to go before adopting some of the leading innovations. This panel will discuss the adoption of futuristic technology in India, and what do they see coming up in the medium term that would be interesting from an investment perspective.

Brain Computer Interfaces (BCIs) are enabled by neurotechnology, which allows getting data out of brains. Progress in neurotechnology has been exponential for decades and now, with the increased involvement of industry participants, it is growing even faster. My research aims to facilitate such progress and, above all, to build algorithms that make sense of the coming deluge of data. I will highlight how modern decoding techniques can be used to decode brain activities and how such approaches are starting to be a central driver in the study of brains.

Many recent mainstream media articles and popular books have raised alarms over anti-social algorithmic behavior, especially regarding machine learning and artificial intelligence. The concerns include leaks of sensitive personal data by predictive models, algorithmic discrimination as a side-effect of machine learning, and inscrutable decisions made by complex models. While standard and legitimate responses to these phenomena include calls for stronger and better laws and regulations, researchers in machine learning, statistics, and related areas are also working on designing better-behaved algorithms. An explosion of recent research in areas such as differential privacy, algorithmic fairness, and algorithmic game theory is forging a new science of socially aware algorithm design. I will survey these developments and attempt to place them in a broader societal context. This talk is based on the book The Ethical Algorithm, co-authored with Aaron Roth (Oxford University Press).

Natural Language Processing has been flourishing in the last few years due, to a large extent, to the success of deep neural networks models. However, most of this success has pushed the boundaries of well-defined classification tasks, where we have a lot of annotated data to train large models. And, most of it is in English. We would like to broaden the scope of our current natural language understanding programs to better deal with more complex, realistic tasks, and to expand it to other languages. I will describe some of our efforts in the direction of improving natural language processing and, specifically, some key information extraction tasks, in low-resource languages.

Data science is transforming all aspects of our society, from how we conduct healthcare and develop treatments, to how we make new discoveries, to how we formulate policies or understand history. Contrary to the popular view, data science consists of more than applying algorithms to data: it must also incorporate existing human expertise, supply any missing context, and provide insights while respecting data's privacy and integrity. I will discuss recent research at Penn focused on effective data reuse and data sharing within collaborative data science -- and the broader goal of developing an AI for facilitating data science and discovery.

By 2050, the US population is estimated to grow to 400 million and the world population to 9.7 billion. Current agricultural practices account for 70% of global water use, energy use is one of the largest costs on a farm, and inefficient use of agrochemicals is altering Earth’s ecosystems. With finite arable land, water, and energy resources, ensuring food, energy, and water security will require new technologies to improve the efficiency of food production, create sustainable approaches to supply energy, and prevent water scarcity.

The National Science Foundation granted the University of Pennsylvania and its partners, Purdue University, the University of California at Merced, and the University of Florida an award to establish the Engineering Research Center for the Internet of Things for Precision Agriculture (IoT4Ag) in September 2020. IoT4Ag’s mission is to create and translate to practice Internet of Things (IoT) technologies for precision agriculture and to train and educate a diverse workforce that will address the societal grand challenge of food, energy, and water security for decades to come. IoT4Ag will develop novel, integrated systems that capture the microclimate and spatially, temporally, and compositionally map heterogeneous stresses for early detection and intervention to better outcomes in agricultural crop production.

The Center will create internet of things (IoT) technologies to optimize practices for every plant; from sensors, robotics, and energy and communication devices to data-driven models constrained by plant physiology, soil, weather, management practices, and socio-economics. Diverse participant groups will be well-prepared through IoT4Ag educational and inclusion programs to have a strong science and engineering knowledge and to establish a workforce able to discover, innovate, translate, and practice precision agriculture solutions. The Center will form an innovation ecosystem and network with academic, industry, investment, and government partners to collaboratively build the future of precision agriculture.

The impact of the COVID-19 pandemic has challenged each of us to change our social behavior and practices while maintaining a sense of social cohesion and public health. Time and again over the course of the pandemic, technology has emerged to enable solutions to achieve normalcy during a uniquely abnormal time. Whether it was to improve the clinical course of COVID-19, to provide accessible technologies for public health, to provide enriched classroom learning experiences, or to invent entirely new technical platforms for testing, treating, and altering the course of the pandemic, faculty in Penn Engineering quickly engaged to contribute solutions in fighting the pandemic. At the same time, our school expanded our use of technology to achieve an engaged remote learning experience for Penn students throughout the world.

This talk will highlight some of the activities occurring in Penn Engineering over the past several months, a period of time where we witnessed dozens of inventions by necessity. Beginning with clinical technologies that filled phasic inventory challenges in medical supplies, we will also discuss inventions that will inevitably contribute biomedical solutions beyond the current pandemic and shape the course of educational practice well into the next decade.

As the atmospheric concentration of carbon dioxide (CO₂) continues to rise, it is imperative that we develop technologies that not only mitigate CO₂ emissions but also remove CO₂ directly from the atmosphere. There are a variety of approaches that are being developed to do just this, and many approaches will be required to achieve a meaningful scale to mitigate climate change. In our work, we have been developing a novel, land-based magnesium oxide looping process to capture CO₂ from the air.