Talk 1: Great Ideas in Computer Science
Dr. Dan Garcia
Dan Garcia (UC Berkeley MS 1995, PhD 2000) is a Teaching Professor in the Electrical Engineering and Computer Science department at UC Berkeley. Selected as an ACM Distinguished Educator in 2012 and ACM Distinguished Speaker in 2019, he has won all four of the department's computer science teaching awards, and holds the record for the highest teaching effectiveness ratings in the history of several of the department's courses.
He is a national leader in the "CSforALL" movement, bringing engaging computer science to students normally underrepresented in the field. Locally, he serves as the CSforCA higher education co-chair. Thanks to four National Science Foundation grants, the "Beauty and Joy of Computing (BJC)" non-majors course he co-developed has been shared with over 500 high school teachers. He is delighted to regularly have more than 50% female enrollment in BJC, with a high mark of 65% in the Spring of 2018, shattering the record at UC Berkeley for an intro computing course, and is among the highest in the nation! He is humbled by the national exposure he and the course have received in the New York Times, PBS NewsHour, NPR's All Things Considered, USA Today, and the front pages of the San Jose Mercury News and San Francisco Chronicle.
He has won the NCWIT Undergraduate Research Mentoring award, the UC Berkeley Unsung Hero award, the LPFI Lux award, the SAP Visionary Member award, and was chosen as a Google CS4HS Ambassador for his work to support teachers and diversify computing. He has served on the ACM Education Board, the College Board Computer Science Principles Development Committee, was the ACM SIGCSE Program co-chair in 2017, and the ACM SIGCSE Symposium co-chair in 2018. He was recently elected ACM SIGCSE Vice-Chair for the 2019-2022 term. In 2019 it was announced he was the most frequent SIGCSE author in their 50-year history, with *61* submissions of all kinds: papers, panels, workshops, posters, etc.; second place had 42.
Talk 2: Mentoring and Networking Together
Effective mentoring allows for mentees to develop skills for personal and professional growth over time, through psychosocial and career support. According to the National Academies' 2019 Consensus Study Report: The Science of Effective Mentoring in Science, Technology, Engineering, Mathematics, and Medicine, if engaged in positive mentoring experiences, graduate students are more likely to persist in their academic decisions (McGee and Keller, 2007; Williams et al., 2016). Networking is a best practice in mentoring relationships. Done well, it can provide the ability for you to gain visibility and access to opportunities within your discipline and beyond. Mentoring and networking can and should work together to enhance your research experience. Join Dr. Jeremy Waisome as she illuminates successful strategies for both mentoring and networking to help you grow as a researcher.
Dr. Jeremy Waisome
Dr. Waisome is a Lecturer in the Department of Engineering Education at the University of Florida where she conducts research on broadening participation in science, technology, engineering, mathematics, and computing. She is particularly interested in understanding how formalized mentoring programs impact student trajectories and self-efficacy. In 2018, she was appointed to serve as Special Assistant to the UF Dean of the Graduate School in the Division of Graduate Student Affairs where she manages the UF Chapter of the Edward A. Bouchet Graduate Honor Society, of which she is a founding member/inductee (2017).
She is passionate about science-communication and participates in several activities to bridge the gap between the general public and the STEM+C disciplines. Along with her colleague, Dr. Kyla McMullen, Dr. Waisome is co-creator and host of the conversational style podcast, Modern Figures Podcast, which exists to elevate the voices of Black women in computing, to inspire the next generation of the advanced technology workforce.
Talk 3: Semantic Robot Programming... and Maybe Making the World a Better Place
The visions of interconnected heterogeneous autonomous robots in widespread use are a coming reality that will reshape our world. Similar to "app stores" for modern computing, people at varying levels of technical background will contribute to "robot app stores" as designers and developers. However, current paradigms to program robots beyond simple cases remain inaccessible to all but the most sophisticated of developers and researchers. In order for people to fluently program autonomous robots, a robot must be able to interpret user instructions that accord with that user’s model of the world. The challenge is that many aspects of such a model are difficult or impossible for the robot to sense directly. We posit a critical missing component is the grounding of semantic symbols in a manner that addresses both uncertainty in low-level robot perception and intentionality in high-level reasoning. Such a grounding will enable robots to fluidly work with human collaborators to perform tasks that require extended goal-directed autonomy.
Jenkins will present our efforts towards accessible and general methods of robot programming from the demonstrations of human users. Our recent work has focused on Semantic Robot Programming (SRP), a declarative paradigm for robot programming by demonstration that builds on semantic mapping. In contrast to procedural methods for motion imitation in configuration space, SRP is suited to generalize user demonstrations of goal scenes in workspace, such as for manipulation in cluttered environments. SRP extends our efforts to crowdsource robot learning from demonstration at scale through messaging protocols suited to web/cloud robotics. With such scaling of robotics in mind, prospects for cultivating both equal opportunity and technological excellence will be discussed in the context of broadening and strengthening Title IX and Title VI.
Odest Chadwicke Jenkins, Ph.D.
Odest Chadwicke Jenkins, Ph.D., is a Professor of Computer Science and Engineering and Associate Director of the Robotics Institute at the University of Michigan. Prof. Jenkins earned his B.S. in Computer Science and Mathematics at Alma College (1996), M.S. in Computer Science at Georgia Tech (1998), and Ph.D. in Computer Science at the University of Southern California (2003). He previously served on the faculty of Brown University in Computer Science (2004-15). His research addresses problems in interactive robotics and human-robot interaction, primarily focused on mobile manipulation, robot perception, and robot learning from demonstration. His research often intersects topics in computer vision, machine learning, and computer animation. Prof. Jenkins has been recognized as a Sloan Research Fellow and is a recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE). His work has also been supported by Young Investigator awards from the Office of Naval Research (ONR), the Air Force Office of Scientific Research (AFOSR) and the National Science Foundation (NSF). Prof. Jenkins is currently serving as Editor-in-Chief for the ACM Transactions on Human-Robot Interaction. He is a Fellow of the American Association for the Advancement of Science, and Senior Member of the Association for Computing Machinery and the Institute of Electrical and Electronics Engineers. He is an alumnus of the Defense Science Study Group (2018-19).
Talk 4: Graduate Studies and the Academic Journey
Dr. Manuel Pérez-Quiñones
Dr. Manuel A. Pérez Quiñones is Professor of Software and Information Systems at UNC at Charlotte. His research interests include HCI, CS education, and diversity in computing. He was Chair of the Coalition to Diversify Computing, Program Chair for the 2014 Tapia Conference, and Co-Chair for SIGCSE 2018 (program) and 2019 (symposium). He serves on the SIGCSE Board, Advisory Board for CMD-IT, Steering Committee for BPCNet.org and Technical Consultant for the Center for Inclusive Computing at Northeastern. His service to diversify computing has been recognized with ACM Distinguished Member status, the CRA's A. Nico Habermann award, and the Richard A. Tapia Achievement Award. He is originally from San Juan, Puerto Rico.
Talk 5: Developing Confidence and INterest
Dean Carla E. Brodley
Dean Carla E. Brodley leads the Khoury College of Computer Sciences at Northeastern University. Prior to joining Northeastern, she was a professor of the Department of Computer Science and the Clinical and Translational Science Institute at Tufts University (2004-2014). Before joining Tufts, she was on the faculty of the School of Electrical Engineering at Purdue University (1994-2004).
A fellow of the Association for Computing Machinery and the Association for the Advancement of Artificial Intelligence (AAAI), Brodley’s interdisciplinary machine learning research led to advances not only in computer and information science, but in areas including remote sensing, neuroscience, digital libraries, astrophysics, content-based image retrieval of medical images, computational biology, chemistry, evidence-based medicine, and predictive medicine.
Brodley’s numerous leadership positions include serving as program co-chair of the International Conference on Machine Learning, co-chair of AAAI, and associate editor of the Journal of AI Research and the Journal of Machine Learning Research. She previously served on the Defense Science Study Group, the board of the International Machine Learning Society, the AAAI Council, the executive committee of the Northeast Big Data Hub, and DARPA’s Information Science and Technology Board.
Carla is on the Board of Trustees of the Jackson Laboratory (JAX). Additionally, she serves on the Computing Research Association Board of Directors, and is a member of Mass Technology Leadership Council and Mass Tech.