1:16:1
Shafi Goldwasser
https://womenintheory.wordpress.com/program/
Women in Theory
Visit talk page
https://womenintheory.wordpress.com/program/
Women in Theory
1:9:55
Laurie Weingart
https://womenintheory.wordpress.com/program/
Women in Theory
Abstract: In their recent book, Babcock, Peyser, Vesterlund, and Weingart share evidence that across industries, jobs, and levels of seniority, women carry a heavier load of tasks that support the organization but do not advance their careers. These non-promotable tasks range from taking notes at meetings and organizing team-building events to serving on organizational governance committees. When women are overloaded with NPTS they have less time to do the work that matters and end up having to work more hours to avoid falling behind their male colleagues. This is bad for women’s careers and bad for their organizations.
In this session, we’ll explore why this happens and what you can do to manage your NPT workload. The common thinking is that women just need to learn how to say no, and this will solve the problem. But it’s not that simple. We will discuss tried and true strategies that you can use to identify NPTs in your work portfolio and begin the process of bringing your workload into balance, as well as what managers can do to change the distribution of NPTs in the first place.
Bio: Laurie R. Weingart is the Richard M. and Margaret S. Cyert Professor of Organizational Behavior and Theory at the Tepper School of Business, Carnegie Mellon University. She served as CMU’s Interim Provost and Chief Academic Officer, and as Senior Associate Dean – Education and Director of the Accelerate Leadership Center within the Tepper School.
Coauthor of The No Club: Putting a Stop to Women’s Dead-End Work(©Simon & Schuster, 2022), her research examines collaboration, conflict, and negotiation, with a focus on how differences across people both help and hinder effective problem solving and innovation. Prof. Weingart has published over 70 articles and book chapters in the fields of management, social psychology, industrial psychology, cognitive psychology, and economics. An elected Fellow of the Academy of Management and recipient of the Joseph E. McGrath Award for Lifetime Achievement in the Study of Groups, Dr. Weingart served as President of the International Association for Conflict Management, founding President of the Interdisciplinary Network for Group Research, and as co-editor of the Academy of Management Annals.
Dr. Weingart earned her Ph.D. in Organizational Behavior from the Kellogg School of Management at Northwestern University.
Visit talk page
https://womenintheory.wordpress.com/program/
Women in Theory
Abstract: In their recent book, Babcock, Peyser, Vesterlund, and Weingart share evidence that across industries, jobs, and levels of seniority, women carry a heavier load of tasks that support the organization but do not advance their careers. These non-promotable tasks range from taking notes at meetings and organizing team-building events to serving on organizational governance committees. When women are overloaded with NPTS they have less time to do the work that matters and end up having to work more hours to avoid falling behind their male colleagues. This is bad for women’s careers and bad for their organizations.
In this session, we’ll explore why this happens and what you can do to manage your NPT workload. The common thinking is that women just need to learn how to say no, and this will solve the problem. But it’s not that simple. We will discuss tried and true strategies that you can use to identify NPTs in your work portfolio and begin the process of bringing your workload into balance, as well as what managers can do to change the distribution of NPTs in the first place.
Bio: Laurie R. Weingart is the Richard M. and Margaret S. Cyert Professor of Organizational Behavior and Theory at the Tepper School of Business, Carnegie Mellon University. She served as CMU’s Interim Provost and Chief Academic Officer, and as Senior Associate Dean – Education and Director of the Accelerate Leadership Center within the Tepper School.
Coauthor of The No Club: Putting a Stop to Women’s Dead-End Work(©Simon & Schuster, 2022), her research examines collaboration, conflict, and negotiation, with a focus on how differences across people both help and hinder effective problem solving and innovation. Prof. Weingart has published over 70 articles and book chapters in the fields of management, social psychology, industrial psychology, cognitive psychology, and economics. An elected Fellow of the Academy of Management and recipient of the Joseph E. McGrath Award for Lifetime Achievement in the Study of Groups, Dr. Weingart served as President of the International Association for Conflict Management, founding President of the Interdisciplinary Network for Group Research, and as co-editor of the Academy of Management Annals.
Dr. Weingart earned her Ph.D. in Organizational Behavior from the Kellogg School of Management at Northwestern University.
1:45:30
Gagan Aggarwal: Autobidding and Auctions
Abstract: Over the past few years, more and more Internet advertisers have started using automated bidding for optimizing their advertising campaigns. Advertisers using automated bidding have an optimization goal (e.g. to maximize conversions), and some constraints (e.g. a budget or an upper bound on average cost per conversion), and the automated bidding system optimizes their auction bids on their behalf. In this talk, we discuss several fundamental questions around autobidding and auctions. How should an autobidder bid to optimize their goals? Do optimal bidding algorithms depend on the underlying auction? What happens when all advertisers adopt optimal autobidding? Does an equilibrium exist, and is it efficient? How do we define efficiency in the presence of autobidding? What happens to the equilibrium when the auctioneer uses reserve prices to optimize its revenue? We will attempt to answer some of these questions in this talk. In particular, we will present a practical algorithm for autobidding that is optimal if and only if the underlying auction is truthful. We will show that an equilibrium always exists under certain smoothness conditions and that the price of anarchy is no more than 2. We will also show that the use of reserve prices can increase the price of anarchy, and bound the resulting increase.
This is based on joint work with Ashwinkumar Badanidiyuru, Aranyak Mehta, Andres Perlroth and Junyao Zhao.
Bio: Gagan Aggarwal is a Research Scientist at Google, where she co-leads the Market Algorithms research team. Her research interests are in Algorithmic Game Theory and Approximation Algorithms, as well as their application to online marketplaces. She received her PhD in Computer Science in 2005 from Stanford University, and her BTech in Computer Science in 2000 from IIT Delhi.
Naama Ben-David: Fast and Fair Lock-Free Locks
Abstract: Locks are frequently used in concurrent systems to simplify code and ensure safe access to contended parts of memory. However, they are also known to cause bottlenecks in concurrent code, leading practitioners and theoreticians to sometimes opt for more intricate lock-free implementations. In this talk, I’ll show that, despite the seeming contradiction, it is possible to design practically and theoretically efficient lock-free locks. I’ll discuss how we model and reason about concurrent systems theoretically, and present a lock-free lock algorithm with good bounds on running time and fairness.
Bio: Naama Ben-David is a postdoctoral researcher at VMware. Her primary research interests are in the intersection of theory and practice in distributed and concurrent computing. More specifically, Naama strives to theoretically explain phenomena seen in modern machines, and to use obtained insights to design and analyze practical algorithms for multiprocessor settings. Naama’s work has been recognized with several awards, including an honorable mention for the CMU School of Computer Science Dissertation Award, a PPoPP 2022 best paper award, an NSERC postgraduate scholarship and a Microsoft Research PhD Fellowship. After her postdoc at VMware, she will be joining the Technion as an Assistant Professor.
Kshipra Bhawalkar: Simple Mechanisms for Rich Advertising Auctions
Abstract: The study of internet advertising auctions has fueled a lot of growth in the area of Algorithmic Game Theory. The traditional model of sponsored Search Auctions is well studied, but more recently we face a more challenging problem of Rich Advertising Auctions, where advertisers provide multiple ads of different sizes and a bid per click. This gives rise to a challenging computational problem of finding the optimal set of ads to fit within a fixed amount of space and a more challenging auction design problem of soliciting true preferences from the advertisers. In this talk, I will describe our recent result that provides a truthful auction that obtains a 3-approximation to the optimal allocation. I will also discuss an extension where with a non-truthful mechanism we prove a 6-approximation in the worst Nash equilibrium.
Bio: Kshipra Bhawalkar is a Research Scientist at Google Research in Mountain View, CA. Her research interest is in Algorithmic Game Theory with applications to online ad auctions and related optimization questions. Kshipra obtained her PhD from Stanford University in 2013 and obtained her bachelors from Duke University.
https://womenintheory.wordpress.com/program/
Women in Theory
Visit talk page
Abstract: Over the past few years, more and more Internet advertisers have started using automated bidding for optimizing their advertising campaigns. Advertisers using automated bidding have an optimization goal (e.g. to maximize conversions), and some constraints (e.g. a budget or an upper bound on average cost per conversion), and the automated bidding system optimizes their auction bids on their behalf. In this talk, we discuss several fundamental questions around autobidding and auctions. How should an autobidder bid to optimize their goals? Do optimal bidding algorithms depend on the underlying auction? What happens when all advertisers adopt optimal autobidding? Does an equilibrium exist, and is it efficient? How do we define efficiency in the presence of autobidding? What happens to the equilibrium when the auctioneer uses reserve prices to optimize its revenue? We will attempt to answer some of these questions in this talk. In particular, we will present a practical algorithm for autobidding that is optimal if and only if the underlying auction is truthful. We will show that an equilibrium always exists under certain smoothness conditions and that the price of anarchy is no more than 2. We will also show that the use of reserve prices can increase the price of anarchy, and bound the resulting increase.
This is based on joint work with Ashwinkumar Badanidiyuru, Aranyak Mehta, Andres Perlroth and Junyao Zhao.
Bio: Gagan Aggarwal is a Research Scientist at Google, where she co-leads the Market Algorithms research team. Her research interests are in Algorithmic Game Theory and Approximation Algorithms, as well as their application to online marketplaces. She received her PhD in Computer Science in 2005 from Stanford University, and her BTech in Computer Science in 2000 from IIT Delhi.
Naama Ben-David: Fast and Fair Lock-Free Locks
Abstract: Locks are frequently used in concurrent systems to simplify code and ensure safe access to contended parts of memory. However, they are also known to cause bottlenecks in concurrent code, leading practitioners and theoreticians to sometimes opt for more intricate lock-free implementations. In this talk, I’ll show that, despite the seeming contradiction, it is possible to design practically and theoretically efficient lock-free locks. I’ll discuss how we model and reason about concurrent systems theoretically, and present a lock-free lock algorithm with good bounds on running time and fairness.
Bio: Naama Ben-David is a postdoctoral researcher at VMware. Her primary research interests are in the intersection of theory and practice in distributed and concurrent computing. More specifically, Naama strives to theoretically explain phenomena seen in modern machines, and to use obtained insights to design and analyze practical algorithms for multiprocessor settings. Naama’s work has been recognized with several awards, including an honorable mention for the CMU School of Computer Science Dissertation Award, a PPoPP 2022 best paper award, an NSERC postgraduate scholarship and a Microsoft Research PhD Fellowship. After her postdoc at VMware, she will be joining the Technion as an Assistant Professor.
Kshipra Bhawalkar: Simple Mechanisms for Rich Advertising Auctions
Abstract: The study of internet advertising auctions has fueled a lot of growth in the area of Algorithmic Game Theory. The traditional model of sponsored Search Auctions is well studied, but more recently we face a more challenging problem of Rich Advertising Auctions, where advertisers provide multiple ads of different sizes and a bid per click. This gives rise to a challenging computational problem of finding the optimal set of ads to fit within a fixed amount of space and a more challenging auction design problem of soliciting true preferences from the advertisers. In this talk, I will describe our recent result that provides a truthful auction that obtains a 3-approximation to the optimal allocation. I will also discuss an extension where with a non-truthful mechanism we prove a 6-approximation in the worst Nash equilibrium.
Bio: Kshipra Bhawalkar is a Research Scientist at Google Research in Mountain View, CA. Her research interest is in Algorithmic Game Theory with applications to online ad auctions and related optimization questions. Kshipra obtained her PhD from Stanford University in 2013 and obtained her bachelors from Duke University.
https://womenintheory.wordpress.com/program/
Women in Theory