UD Graduate students look to the future at Delaware NextGen Data Science Symposium

Data science will drive innovation across an astounding variety of disciplines, from ecology to political science, attendees were told at the Delaware NextGen Data Science Symposium, organized and hosted by UD’s Data Science Institute (DSI) Student Association and the DSI Student Fellows.  

Speaking to an audience that included UD students and faculty, industry leaders and students from regional colleges and universities, DSI Fellows predicted where data science would take their fields by 2050. The increased availability of data together with fast-evolving technologies like machine learning and natural language artificial intelligence (AI) interfaces are expected to usher in changes that will be truly revolutionary.

James Korman, chair of the symposium planning committee and vice president of the DSI Student Association, is a doctoral candidate in political science and international relations. In a field that he sees as already transformed by big data and machine learning, Korman predicted a future in international relations defined by data-driven diplomacy and global collaborative governance.

"Envisioning the year 2050, we anticipate harnessing the power of data to foster deeper understanding, strengthen diplomatic ties and navigate the complexities of our interconnected world,” Korman said. “It's an exciting era where data science becomes not just a tool but an indispensable force shaping the trajectory of international relations."  

Hassan Baker, DSI Student Association president and a doctoral candidate in electrical and computer engineering, discussed the promise that machine learning holds for tumor segmentation and the detection of abnormal tissues.

“With the progress of machine learning, leveraging non-invasive methods for interpreting brain signals is now more viable than ever,” Baker explained. “Additionally, artificial intelligence is expected to enhance the identification of abnormal tissues, particularly in underserved areas lacking consistent expertise. The advent of unsupervised learning further proves advantageous by reducing the dependency on expert-labeled data."

Matt Walter, a doctoral candidate in geography and spatial science, pointed out the opportunities that remote sensing creates, with more than 6,718 active satellites orbiting the Earth able to generate more than 100 terabytes of data every day. GeoAI, the automation of information extraction from this data, could be used to address vital sustainability issues, from tracking wildlife to measuring pollution.  

“With increasing global populations and accelerating climate change impacting every ecosystem on our planet, there is a growing need to understand how Earth is being affected,” Walter explained. “Remote sensing satellites give us the ability to monitor physical, chemical and biological systems anywhere on Earth. Using data science tools like AI and cloud computing along with interdisciplinary collaboration will be essential in obtaining useful and actionable information from large quantities of satellite images."

Idowu Kunlere, a doctoral candidate in energy and public policy, outlined the potential impact of data science on energy and environmental policy and the benefits of AI to a wide range of societal challenges, from monitoring carbon emissions to smart grid management and energy demand forecasting.

"Many energy and environmental decisions are often made in silos, owing to massive amounts of data and the difficulty in making sense of such data,” Kunlere explained. “However, data science offers various tools for processing large datasets from different sources, revealing hidden relationships that could aid us in making smarter and holistic decisions. It also offers new analytical lenses and perspectives that could help increase productivity and profitability while cutting overall costs and minimizing adverse environmental impacts.”

Chara Angelidou, a doctoral candidate in mechanical engineering, described the benefits of equipping robots with advanced AI capabilities that would allow them to identify objects in complex environments, make real-time decisions and predict future states of environments.

"As we stand on the brink of a transformative era in data science and robotics, the possibilities are boundless,” Angelidou said. “Through real-time decision-making and predictive capabilities, intelligent machines are poised to revolutionize industries, offering unparalleled efficiency and adaptability. The transformative potential of merging engineering with cutting-edge AI paves the way for a new era of innovation and problem-solving, which will include enhanced robot perception for navigation in intricate and dynamic environments, personalized solutions in the realm of medical interventions, and seamless collaboration between humans and robots."

In addition to talks by DSI Fellows, the day’s events included graduate student panel discussions moderated by John Gizis, professor of physics and astronomy and associate director of DSI, and Benjamin Bagozzi, associate professor of political science, associate director of DSI and associate director of the Graduate College’s Master of Science in data science program. A panel discussion with industry leaders included Michael Blaustein, DSI industry liaison, as moderator and Jennifer Koester (State of Delaware), Joseph Davis (FMC), Ian Moloney (American Fintech Council) and Matthew Saponaro (A.I. Whoo) as panelists. Austin Brockmeier, assistant professor of electrical and computer engineering at UD, and Saleem Ali, Blue and Gold Distinguished Professor of Energy and Environment, gave keynote addresses.

The Delaware NextGen Data Science Symposium, an event tailored for the next generation of data science leaders, is part of the DSI Student Association's mission to represent a community of aspiring data scientists passionate about exploring the vast world of data. The association promotes collaborative learning where students can enhance their data analysis skills, engage in hands-on projects and stay updated with the latest data science and technology trends to develop the knowledge and expertise necessary to tackle real-world challenges.

DSI fellows are nominated by faculty within the data science community at UD as outstanding graduate students who are using data science techniques and tools to advance their research.

“The DSI fellows offer a diverse range of perspectives on cutting-edge data science methods and applications,” said Bagozzi. “Above and beyond this research expertise, they also provide key leadership to the DSI and to data science at UD on the whole. This recent success of the NextGen Data Science Symposium is but one example of these leadership efforts, which also include successful community hours, research competitions, and related community-building efforts.”

For more information about the DSI Student Association, contact Matt Walter at mswalter@udel.edu.