Siebel School SRP Lunch and Learn: Presentation and Other Verbal Communication Skills - Nancy Amato, Ruby Tahboub, Gang Wang 07142026

This session will focus on building your oral communication skills. Topics include strategies for making high quality oral and poster presentations.

Speakers

Nancy Amato

Nancy M. Amato is Director of the Siebel School of Computing and Data Science and Abel Bliss Professor of Engineering at the University of Illinois Urbana-Champaign.  She received undergraduate degrees in Mathematical Sciences and Economics from Stanford, and M.S. and Ph.D. degrees in Computer Science from UC Berkeley and the University of Illinois, respectively.  Before returning to her alma mater in 2019, she was Regents Professor and Senior Director of Engineering Honors Programs at Texas A&M. She is known for algorithmic contributions to robotics task and motion planning, computational biology and geometry, and parallel computing.  She has graduated 30 PhD students, 30+ master's students, 200+ undergraduates, and 10+ high school students. Amato currently serves as the President of the IEEE Robotics and Automation Society (2026-2027) and was CRA Board Chair (2021-2025).  Her honors include the inaugural MassRobotics Robotics Medal, the IEEE Robotics and Automation Society Saridis Leadership Award, the inaugural NCWIT Harrold/Notkin Research and Graduate Mentoring. She is a Fellow of the AAAI, AAAS, ACM, and IEEE and a Member of the American Academy of Arts and Sciences.

Ruby Tahboub
I am a Teaching Assistant Professor at the Siebel School of Computing and Data Science at the University of Illinois at Urbana-Champaign. I am passionate about teaching and making the learning process more effective and equitable. As an educator, I aim to help students construct the link between abstract concepts and practice while minimizing the cognitive load. I teach introductory programming, data management, and knowledge discovery. 

Gang Wang
Gang Wang received his Ph.D. from UC Santa Barbara in 2016 (under the direction of Ben Y. Zhao and Heather Zheng), and a B.E. from Tsinghua University in 2010. After working as an Assistant Professor at Virginia Tech (2016 - 2019), he joined the University of Illinois at Urbana-Champaign in 2019. Currently, he is an Associate Professor in the Department of Computer Science and also has affiliate faculty appointments in the Department of Electrical and Computer Engineering (ECE) and the Informatics Program of the School of Information Sciences at the University of Illinois. He is a recipient of the NSF CAREER Award (2018), Amazon Research Award (2021), Google Faculty Research Award (2017), and Best Paper Awards from IMWUT 2019, ACM CCS 2018, and SIGMETRICS 2013. His projects have been covered by media outlets such as MIT Technology Review, The New York Times, Boston Globe, CNN, and ACM TechNews.

Gang Wang's research interests are Security and Privacy, Internet Measurement, and Data Mining. His work takes a data-driven approach to addressing emerging security threats in massive communication systems (social media, email services), crowdsourcing systems, mobile applications, and enterprise networks. His major contribution is a series of measurement methodologies that have revealed previously overlooked security threats, including crowdturfing activities in online social networks, security certification failures in the payment card industry, email spoofing vulnerabilities in major email providers, and the deep link usage in mobile app ecosystems. Another key contribution is his work on applying machine learning in security applications (e.g., bot detection, malware classification) to handle adversarial behaviors and concept drift.

Gang Wang's current focus is on developing robust data-driven methods (e.g., machine learning models, graph models) to enable accurate, scalable, and user-friendly security applications for malware analysis and online abuse mitigation. The key challenge Wang is tackling is to effectively engineer human-machine collaboration pipelines to improve the efficacy and efficiency of both parties against adaptive attackers in the respective fields. Wang is currently collaborating with industry partners and researchers from related fields such as HCI and AI to address these problems.