IBM announces the winners of the 2024 Pat Goldberg competition

IBM Research has recently concluded the annual Pat Goldberg Memorial Best Paper Award competition. This annual competition recognizes a small number of outstanding papers spanning the broad breadth of IBM Research including computer science and AI, mathematical sciences, physical sciences and quantum. These papers also reflect strong collaborations with leading research universities.

Papers published in the previous year (2023) were eligible, and this year, three papers were selected as winners and four as honorable mention. These seven papers were published in leading scientific publications: Nature, Nature Communications, Nature Electronics, Nature Machine Intelligence, Physical Review Letters, the IEEE Journal of Solid State Circuits, and NeurIPS. Topics covered in the papers include a paradigm using AI to discover fundamental scientific laws; advances in superconducting computers; and key advances enabling practical use of quantum computing before we have fully fault-tolerant systems.

These awards were established in the memory of Pat Goldberg, an IBM researcher who was instrumental in establishing systematic research disciplines in IBM Research. The competition was named in her honor when she passed away after retiring from IBM.

We salute the winners and encourage you to read the papers.

Winners

1. Combining data and theory for derivable scientific discovery with AI-Descartes. Nature Communications. Cristina Cornelio, Sanjeeb Dash, Vernon Austel, Tyler Josephson, Joao Goncalves, Ken Clarkson, Nimrod Megiddo, Bachir El-Kahdir, Lior Horesh

2. Ubiquitous superconducting diode effect in superconductor thin films. Physical Review Letters. Yasen Hou, Fabrizio Nichele, Hang Chi, Alessandro Lodesani, Yingying Wu, Markus F. Ritter, Daniel Z. Haxell, Margarita Davydova, Stefan Ili─ç, Ourania Glezakou-Elbert, Amith Varambally, F. Sebastian Bergeret, Akashdeep Kamra, Liang Fu, Patrick A. Lee, Jagadeesh S. Moodera

3. Evidence for the utility of quantum computing before fault tolerance. Nature. Youngseok Kim, Andrew Eddins, Sajant Anand, Ken Xuan Wei, Ewout van den Berg, Sami Rosenblatt, Hasan Nayfeh, Yantao Wu, Michael Zaletel, Kristan Temme, Abhinav Kandala

Honorable mention

1. A 72-GS/s, 8-Bit DAC-Based Wireline Transmitter in 4-nm FinFET CMOS for 200+ Gb/s Serial Links. IEEE Journal of Solid-State Circuits. Timothy Dickson, Zeynep Toprak Deniz, Martin Cochet, Troy Beukema, Marcel Kossel, Thomas Morf, Young-Ho Choi, Pier Andrea Francese, Matthias Brandli, Christian Baks, Jonathan Proesel, John Bulzacchelli, Michael Beakes, Byoung-Joo Yoo, Hyoungbae Ahn, Dong-Hyuk Lim, Gunil Kang, Sang-Hune Park, Mounir Meghelli, Hyo Gyuem Rhew, Daniel Friedman, Michael Choi, Mehmet Soyuer, Jongshin Shin

2. A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference. Nature Electronics. Manuel Le Gallo, Riduan Khaddam-Aljameh, Milos Stanisavljevic, Athanasios Vasilopoulos, Benedikt Kersting, Martino Dazzi, Geethan Karunaratne, Matthias Braendli, Abhairaj Singh, Silvia M. Mueller, Julian Buechel, Xavier Timoneda, Vinay Joshi, Malte J. Rasch, Urs Egger, Angelo Garofalo, Anastasios Petropoulos, Theodore Anthonakopoulos, Kevin Brew, Samuel Choi, Injo Ok, Timothy Phillip, Victor Chan, Claire Silvestre, Ishtiaq Ahsan, Nicole Saulnier, Vijay Narayanan, Pier Andrea Francese, Evangelos Eleftheriou, Abu Sebastian

3. A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization. NeurIPS: Advances in Neural Information Processing Systems. Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark S. Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong

4. Regression Transformer Enables Concurrent Sequence Regression and Generation for Molecular Language Modelling. Nature Machine Intelligence. Jannis Born, Matteo Manica