Chemistry Meets Glassblowing (at a Special Venue: S-429 Chemistry Building); Learning from Societal Data; The SuperAgers Study


For 19 October 2022    

Hi WN@TL Fans,

I admire the look and feel of a hefty ceramic mortar and pestle, but as a kid nothing said “chemistry” quite like a Pyrex beaker & an Erlenmeyer flask arrayed with a rack of test tubes next to a long-necked vol flask.  O, the possibilities!

In college one of the (few) joys of organic chemistry lab was the meticulous assembling of the crystalline distillation apparatus, with sintered fittings and water-jacketed condensation columns and rotary evaporation vessels spinning under vacuum.

Laboratory glass shares with diamonds the appeal of clarity and durability, but only glass can be like putty in our hands; only glass can be shaped by our lungs; only glass can meld into our most labyrinthine apparatus or into our most elegantly-sublime device.

This week we get to peer into the extraordinary interplay between chemistry and glass.  Aptly, we have a Special Venue—Room S-429 in the splendid new addition to Chemistry at 1101 University Avenue.




Credit: Andy Warwick                        Credit: Bryce Richter


On October 19  historian Catherine Jackson of Oxford University returns to UW-Madison and joins with the Department of Chemistry’s master glassblower Tracy Drier.  The title of their presentation is “Microheterotopias:  Chemistry Meets Glassblowing.”

Note 1:  The Madison chapter of the American Chemical Society will have a reception featuring pizza starting at 6:30. 

Note 2:  Did someone say pizza? 

Description:  The American Chemical Society’s logo includes a triangular graphic representing an item of scientific glassware.  This is the Kaliapparat (potash bulbs).  Desperate to solve one of the most pressing scientific problems of his day, the young Justus Liebig made the first Kaliapparat in the fall of 1830.  Using the Kaliapparat, he became one of the nineteenth century’s greatest chemists.  

But the Kaliapparat altered much more than the course of Liebig’s career.  His decision to make the Kaliapparat by bending and blowing glass tubing changed how chemists worked and were trained, with important consequences for the developing science of chemistry and its relationship to glassblowing.

Managing other worlds in glass – the Microheterotopias of my title – is vital in chemists’ ability to control and manipulate matter.  But making Microheterotopias relies on the skill of the scientific glassblower.  This talk explains what happened when chemistry met glassblowing – and why that connection remains vital today.

Bios:  Chemist, historian, and educator, Catherine Jackson has a passion for using history to understand chemistry’s present and future, as well as its past.

                Jackson’s work reshapes our view of nineteenth-century chemistry. Built around practice-based breakthroughs including chemistry’s glassware revolution and turn to synthesis, her forthcoming book Molecular World: Making Modern Chemistry (MIT Press, July 2023) explains a critical period in chemistry’s quest to understand and manipulate organic nature. A sequel volume Molecular Puzzles: Re-thinking the Ring will show that practical utility – rather than theoretical correctness – lay behind the success of Kekulé’s benzene ring.

Catherine M. Jackson is Associate Professor of the History of Science in the University of Oxford, Peck Fellow in History at Harris Manchester College, and Director of the Oxford Centre for the History of Science, Medicine, and Technology.

Tracy Drier has been exploring glassblowing since he was a child. A graduate of Western Michigan University and the scientific glassblowing program at Salem Community College in New Jersey, he is currently the Master Glassblower for the University of Wisconsin-Madison where he works closely with scientists designing, building, and refining chemical glassware to meet their research needs.

Tracy educates people of all ages about glass and teaches glassblowing in institutions and conferences around the country including the American Scientific Glassblowers Society, the Studio of Corning Museum of Glass and Pilchuck Glass School.

Explore More:

Catherine Jackson’s forthcoming book: Molecular World: Making Modern Chemistry

Note: For guidance on parking options, please see and click on the Public Parking box that will give you real-time information on available parking spaces.  You may want to consider parking under Grainger Hall, since it’s closer to Chemistry than Lot 20 is.


On October 26 we will return to our regular homebase in Room 1111 Genetics Biotech Center as Ramya Vinayak of the Department of Electrical and Computer Engineering tunes us in to a defining attribute of our times:  “Learning from Societal Data.”

Description:  Machine learning algorithms learn to make predictions and inferences using large quantities of data. More than half a century of advances in this field have led us to build very good systems that identify spam emails, make our phone cameras detect where to focus when taking pictures, and recommend relevant items or movies on e-commerce platforms. We are now using machine learning algorithms to many critical societal applications in health care, finance, criminal justice systems, and governance to aid in decision making which have far reaching consequences on our lives in the present and the future. However, the nature of the data that we learn from and the consequences of making wrong inferences in these applications are very different.

In many societal applications, the data comprises people from diverse backgrounds. The inferences we can draw from such societal-scale datasets are often severely limited not by the number of people in the data but rather by limited observations available for each individual. Therefore, addressing these challenges due to diversity among the population and the limited observations per individual are critical. My research focuses on tackling these limitations both from theoretical and practical perspectives. In this talk, I will provide a high-level overview of how machine learning algorithms learn from data, what are the key challenges to learning from data from diverse people, and some of the approaches being developed in my research group and from other researchers in the field to tackle them.

Bio:  Ramya Vinayak is an assistant professor in the Department of Electrical and Computer Engineering and affiliate faculty in the Department of Computer Science at UW-Madison. Her research focuses on machine learning, statistical inference and crowdsourcing. Prior to joining UW-Madison she was a postdoctoral researcher at the University of Washington in Seattle. She obtained her Ph.D. and masters degrees in Electrical Engineering at Caltech in Pasadena, California. She grew up in the southern part of India and obtained her undergraduate degree in Electrical Engineering at Indian Institute of Technology Madras before starting her academic research journey. In her spare time, she enjoys hiking, cooking and painting.

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Machine learning and Optimization Group at UW-Madison: