CRA-WP Announces Recipients of the Inaugural Skip Ellis Early Career Award and the 2020 Anita Borg Early Career Award

CRA-WP is honored to present the recipients of the inaugural Skip Ellis Early Career Award and the 2020 Anita Borg Early Career Award. Tawanna Dillahunt of the University of Michigan and Michel A. Kinsy of Boston University have been selected as the Skip Ellis Early Career Award recipients. Olga Russakovsky of Princeton University has been selected as the Anita Borg Early Career Award recipient.

The Skip Ellis Early Career Award honors the late Clarence “Skip” Ellis, who was the first African-American to both earn a Ph.D. in computer science and be elected a Fellow of the ACM. This award is given annually by CRA-WP to a person who identifies as a member of a group underrepresented in computing (African-American, Latinx, Native American/First Peoples, and/or People with Disabilities), who has made significant research contributions in computer science and/or engineering and has also contributed to the profession, especially in outreach to underrepresented demographics.

The Anita Borg Early Career Award honors the late Anita Borg, who was an early member of CRA-W (before it became CRA-WP), and is inspired by her commitment to increasing the participation of women in computing research. The annual award is given to a woman in computer science and/or engineering who has made significant research contributions and who has contributed to her profession, especially in the outreach to women.

This year, recognition was warranted beyond the award winners and two nominees are receiving the Distinction of Honorable Mention.

• Cindy Rubio González of the University of California Davis is recognized by both the Anita Borg Early Career Award and the Skip Ellis Early Career Award committees for a joint Honorable Mention.
• Carole-Jean Wu of Arizona State University is recognized by the Anita Borg Early Career Award committee.

CRA-WP is proud to celebrate the growing representation in computing research by highlighting both Rubio González and Wu for their significant contributions and outreach in the field. It is encouraging to see the growth in the excellent computing researchers from diverse backgrounds committed to scholarly excellence and equal opportunity. Thank you to everyone who took the time to submit a nomination for this year and we hope to see many more in the next cycle.

About the Awardees

Tawanna Dillahunt
Tawanna Dillahunt is an Associate Professor at the University of Michigan’s School of Information (UMSI) and holds a courtesy appointment with the Electrical Engineering and Computer Science Department. Working at the intersection of human-computer interaction; environmental, economic, and social sustainability; and equity, her research investigates and implements technologies to support the needs of marginalized people. She and her team have developed digital employment tools that address the needs of job seekers with limited digital literacy and education; assessed real-time ridesharing and online grocery delivery applications among lower-income and transportation-scarce groups, and proposed models for novice entrepreneurs to build their technical capacity.

Tawanna has received funding to support her research from the National Science Foundation, the Gates Foundation, UM Poverty Solutions, UM Ginsberg Center, and the UM Ford School. Her work appears in the most prestigious HCI conferences and journals and has won several best papers and honorable mentions. She holds a Ph.D. and M.S. in Human-Computer Interaction from Carnegie Mellon University, an M.S. in Computer Science from the Oregon Health and Science University, and a B.S. in Computer Engineering from North Carolina State University. She was also a software engineer at Intel Corporation for seven years.

Tawanna has demonstrated commitment to supporting underrepresented people and communities. She is a Digital Inclusion Policy fellow mentor for UM Poverty Solutions and is a member of the Advisory Committee for the University of Michigan Center for Academic Innovation. The nature of her research alone enables her to work with a diverse set of passionate students and community members who have been attracted to her research. She directs the Social Innovations Group and has mentored numerous master’s, undergraduate, and high school students, and postdocs, over half whom are women and underrepresented minorities. She actively participates in programs that benefit underrepresented groups and engages in community-based participatory research.

Michel A. Kinsy
Michel A. Kinsy is an Assistant Professor in the Department of Electrical and Computer Engineering at Boston University (BU), where he directs the Adaptive and Secure Computing Systems (ASCS) Laboratory. He focuses his research on computer architecture, hardware-level security, and efficient hardware design and implementation of post-quantum cryptography systems. He has published over 60 research articles, many in top-tier conferences and journals, including the International Symposium on Computer Architecture, International Symposium on High-Performance Computer Architecture, IEEE International Symposium on Hardware Oriented Security and Trust, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, and IEEE Transactions on Computers.

Michel is an MIT Presidential Fellow. He earned his Ph.D. in Electrical Engineering and Computer Science in 2013 from the Massachusetts Institute of Technology (MIT). In his doctoral work, he introduced some of the first algorithms and innovative hardware techniques to emulate and control large-scale power systems at the microsecond resolution. The work inspired further research by the MIT spin-off Typhoon HIL, Inc. Before joining the BU faculty, Michel was an assistant professor in the Department of Computer and Information Systems at the University of Oregon, where he directed the Computer Architecture and Embedded Systems (CAES) Laboratory. From 2013 to 2014, he was a Member of the Technical Staff at the MIT Lincoln Laboratory, where he led the Advanced Computer Architecture Concepts sub-group tasked with exploring future secure computing architectures in critical DoD systems.

Michel is a mentor who inculcates a culture of embracing diversity, intellectual honesty, excellence in research, social responsibility, and personal integrity among the mentees in his research laboratory – three of them are underrepresented doctoral students. His outreach efforts include creating the University of the Virgin Islands Summer Cybersecurity Program; organizing ACM Richard Tapia Celebration of Diversity in Computing Conference workshops on open-source computer architecture design space exploration and post-quantum cryptosystem design; introducing a computer science module into the Oregon Young Scholars Program for preparing historically underserved students for college, and the University of Oregon African-American Rites of Passage Program.

Olga Russakovsky
Olga Russakovsky is an Assistant Professor of Computer Science at Princeton University where she is also affiliated with the Center for Statistics and Machine Learning and the Center for Information Technology Policy. Her research is in computer vision, closely integrated with machine learning, human-computer interaction and fairness, accountability and transparency. Olga focuses on three primary areas of exploration. The first is developing the fundamental building blocks of visual recognition, such as object detection, image parsing or human activity recognition. The second is designing human-machine interaction paradigms to enable computer vision systems to effectively learn from and collaborate with humans. The third is ensuring the fairness of the vision systems with respect to people of all backgrounds by improving dataset design, algorithmic methodology and model interpretability.

One of her notable research contributions is leading the ImageNet Large Scale Visual Recognition Challenge. This research appeared in the International Journal of Computer Vision in December 2015 and amassed 13,422 citations as of December 1, 2019. Her team was awarded the prestigious PAMI Everingham Prize, and the work was featured in the New York Times and MIT Technology Review. Crowdsourcing contributions of this research also appeared in the premier human-computer interaction conference (ACM CHI) in 2014 and follow-up work on remove cultural stereotypes from the dataset will appear in the ACM Conference on Fairness, Accountability and Transparency (FAT*) in 2020.

Olga was awarded numerous awards for her research and outreach work in addition to the PAMI Everingham Prize, such as the MIT EECS Rising Star award and NSF Graduate Research Fellowship. She was named one of MIT Technology Review’s 35 Innovators Under 35 in 2017, Foreign Policy Magazine’s 100 Leading Global Thinkers in 2015 and Becominghuman.ai’s 100 Brilliant Women in AI Ethics in 2019. She has served as a Senior Program Committee member for WACV’16, CVPR’18, CVPR’19, NeurIPS’19 and CVPR’20, has organized 9 workshops and tutorials on large-scale recognition, and has given more than 50 invited talks at universities, companies, workshops and conferences.

She completed her Ph.D. in Computer Science at Stanford University in August 2015 and her postdoctoral fellowship at the Robotics Institute of Carnegie Mellon University in June 2017.

In addition to her research, Olga co-founded and serves on the Board of Directors of the AI4ALL foundation dedicated to educating diverse future Artificial Intelligence (AI) leaders. She was the co-founder and co-director of the Stanford AI4ALL summer camp for high school girls; the camp was featured in Wired and a study on its effectiveness was published in SIGCSE’16. Olga is the co-founder and co-director of the Princeton AI4ALL summer camp teaching AI technology and policy to underrepresented high school students. AI4ALL has partnered with 11 universities so far to introduce students from underrepresented groups to AI, and launched a free, project-based online AI education program. In addition, she is the co-founder of the annual Women in Computer Vision workshop at CVPR, the monthly Women in AI tea at Stanford, and the monthly Research Inclusion Social Event at Princeton.