TL;DR:
- Schmidt Futures sponsored a conference at the University of Toronto.
- The conference focused on AI’s impact on scientific research and attracted 120 top minds.
- It marked the launch of the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowships program.
- The program aims to create a global network of AI-equipped researchers.
- U of T plays a vital role in the program.
- Schmidt Fellows showcased projects from AI-guided chemistry to cancer research.
- The program revolutionizes data collection for ecology.
- Climate modeling benefits from AI through the program.
Main AI News:
In the realm of scientific innovation, a seismic shift is underway, one that promises to redefine the very essence of research itself. The catalyst for this transformation? Remarkable strides are being made in the field of machine learning. As the world stands at the precipice of a new era in scientific exploration, where medical breakthroughs and climate change solutions beckon on the horizon, a pressing need arises—a need for visionary leaders who can harness the power of artificial intelligence to shape a future where science knows no bounds.
Midway through the month of August, Toronto played host to an assembly of 120 brilliant minds, luminaries on a mission to advance this audacious goal. Sponsored and co-hosted by Schmidt Futures, the conference served as a nexus for the exchange of ideas, the forging of bonds, and the sharing of progress in projects that leverage the potent capabilities of machine learning across a diverse spectrum of disciplines and challenges.
This momentous gathering marked the inauguration of the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowships program—a prestigious initiative offering over a hundred fellows, including nine from the University of Toronto, a gateway to cutting-edge machine learning training and mentorship. The program’s objective is nothing short of creating a global network of researchers poised to catapult science into the age of AI. In Toronto, this endeavor is helmed by the esteemed Professor Lisa Strug, Director of the Data Sciences Institute, and Professor Alán Aspuru-Guzik, Director of the Acceleration Consortium, with support from the Vector Institute.
Professor Alán Aspuru-Guzik emphasized the significance of the conference, stating, “The Schmidt AI in Science Conference has been a remarkable opportunity for postdocs, faculty leads, and program managers to gather and discuss their research and the future growth of this program. To have the first iteration of this event in Toronto and at U of T demonstrates that the Greater Toronto Area is the place to be in the field of AI for science.”
U of T’s invitation to join the program in fall 2022, alongside eight other esteemed institutions in Singapore, the United Kingdom, and the United States, signified a great honor. As the sole Canadian university participating, U of T proudly co-hosted the program’s inaugural conference, helping to foster a global community that champions and emboldens its initial cohort of fellows.
Leah Cowen, Vice-President, Research and Innovation, and Strategic Initiatives, commended U of T’s role in advancing the program, stating, “The Eric and Wendy Schmidt AI in Science Postdoctoral Fellowships program is accelerating the creative use of machine learning in science and building a global community of young leaders in this field. U of T’s participation in the program is helping to cement Toronto’s status as a global center of AI excellence.“
The third day of the conference placed a spotlight squarely on U of T’s Schmidt Fellows and the myriad ways in which U of T is adapting AI to propel scientific and medical breakthroughs. U of T staff led conference attendees on a tour of the St. George campus, where four U of T Schmidt Fellows delivered concise presentations on the projects they’ve been empowered to pursue through the program.
The first stop on this journey led to the Lash Miller building, home to Acceleration Consortium director Aspuru-Guzik’s “self-driving” organic chemistry lab. Here, Schmidt Fellow Felix Strieth-Kalthoff showcased a meticulously designed AI-guided system that tirelessly executes the laborious tasks inherent in organic chemistry research. This automation has not only eliminated significant manual labor but has also accelerated research efforts. Strieth-Kalthoff envisions further enhancing the system’s efficiency by automating the purification of solutions—a testament to the transformative potential of Schmidt Futures projects.
In the Myhal Centre for Engineering Innovation & Entrepreneurship, attendees gained insight into Fatema Tuz Zohora’s groundbreaking work in computational biology. As a U of T Schmidt Fellow and postdoctoral researcher at the Princess Margaret Cancer Center’s Schwartz lab, Zohora is unraveling the mysteries of anti-cancer drug resistance, a menace responsible for nearly 90 percent of cancer-related fatalities. Her innovative approach combines computer vision, natural language processing, and other machine learning techniques to analyze data from various molecular layers of cell-to-cell communication, potentially revolutionizing cancer therapy.
Adjacent to Zohora’s presentation, Jessica Leivesley, a postdoctoral researcher in the Department of Statistical Sciences, unveiled a novel technique aimed at revolutionizing ecological data collection. Her research, as a Schmidt Fellow, merges machine learning techniques to automate the monitoring of fish species populations, a vital aspect of managing freshwater ecosystems. By leveraging non-invasive methods that analyze sound wave interactions in lakes, Leivesley’s approach promises to redefine how ecologists gather critical data, enhancing their ability to monitor environmental changes.
The tour’s final destination was the new home of U of T’s Data Sciences Institute at College St. and University Avenue. Here, Soukayna Mouatadid, a U of T Schmidt Fellow and postdoctoral researcher in U of T’s Department of Computer Science, elucidated her pioneering work in integrating machine learning tools into climate modeling. Her research exemplifies the potential to develop a new breed of meteorological models, offering more accurate predictions even in the face of escalating climate change-induced weather extremes such as heatwaves, droughts, and floods.
Mouatadid’s focus on sub-seasonal forecasting, a critical window of two to six weeks ahead, where current prediction accuracy falls short, has garnered recognition and awards. By harnessing historical data and applying machine learning to decipher concealed patterns in decades of meteorological variables, her work promises to yield even more granular and precise forecasting models.
The Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship program has not only championed the remarkable endeavors of these exceptional researchers at U of T but has also woven them into a global tapestry of like-minded scholars shaping the future of scientific inquiry. As this Schmidt Futures program beckons new cohorts of gifted researchers, it propels forward the AI revolution in science, ever closer to a future where the boundaries of human knowledge are pushed beyond the imaginable.
Conclusion:
The collaboration between Schmidt Futures and the University of Toronto, as well as the global expansion of the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowships program, signifies a significant investment in the intersection of AI and scientific research. This commitment to nurturing young leaders and fostering a global network of researchers holds immense promise for the market, as it will likely accelerate advancements in various scientific domains, potentially leading to groundbreaking innovations and new market opportunities in the AI-driven scientific landscape.
