January, 23

15.30

55.309

January, 30

15.30

55.003

PhD Research Seminar 

Getting your PhD but keeping your sanity. A workshop Format:

Abstract:

Recent studies suggest that PhD students suffer a mental health issues at alarminglevels—around six times the level of the general population—issues which impact not only productivity and program outcomes but also the long-term well-being of the developing researcher. Research centers have begun to address the issue, but it resists a simple policy solution. Indeed, the issue of mental health and well-being in PhD programs has the characteristics of a “wicked problem”. For example, it lacks a definitive solution, every problem is unique, it can be explained in a number of ways, and it tightly intertwined with a number of interconnected systems, also experiencing issues. In light of these challenges, this workshop takes a collaborative, action-oriented approachto generate awareness and empower PhD students. Based on methods developed in psychology, organizational studies, and design thinking, it provides a means of understanding and addressing the challenges PhD students face in a way that allows for the variety of forms these are likely to take. Participants will gain increased awareness of the complexity of the issue and propose their own solution in a hands-on, supportive setting.

January, 31

15.00

55.003

January, 31

16.10

55.003

This seminar offers a comprehensive survey of privacy dependencies—the many ways that our privacy depends on the decisions and disclosures of other people. What we do and what we say can reveal as much about others as it does about ourselves, even when we don’t realize it or when we think we’re sharing information about ourselves alone.

We identify three bases upon which our privacy can depend: our social ties, our similarities to others, and our differences from others. In a tie-based dependency, an observer learns about one person by virtue of her social relationships with others—family, friends, or other associates. In a similarity-based dependency, inferences about our unrevealed attributes are drawn from our similarities to others for whom that attribute is known. And in difference-based dependencies, revelations about ourselves demonstrate how we are different from others—by showing, for example, how we “break the mold” of normal behavior or establishing how we rank relative to others with respect to some desirable attribute. 

We elaborate how these dependencies operate, isolating the relevant mechanisms and providing concrete examples of each mechanism in practice, the values they implicate, and the legal and technical interventions that may be brought to bear on them. Our work adds to a growing chorus demonstrating that privacy is neither an individual choice nor an individual value—but it is the first to systematically demonstrate how different types of dependencies can raise very different normative concerns, implicate different areas of law, and create different challenges for regulation.

Reference: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3447384

Bio:

Solon Barocas is a Principal Researcher in the New York City lab of Microsoft Research and an Assistant Professor in the Department of Information Science at Cornell University. He is also a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard University.

His research explores ethical and policy issues in artificial intelligence, particularly fairness in machine learning, methods for bringing accountability to automated decision-making, and the privacy implications of inference.

He co-founded the annual workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) and later established the ACM conference on Fairness, Accountability, and Transparency (FAT*).

He was previously a Postdoctoral Researcher at Microsoft Research as well as a Postdoctoral Research Associate at the Center for Information Technology Policy at Princeton University. He completed his doctorate at New York University, where he remains a Visiting Scholar at the Center for Urban Science + Progress.

February, 6

15.30

TBA

PhD Research Seminar

Creating an elevator pitch

February, 13

15.30

55.309

PhD Research Seminar 

By Marianna Nadeu (CIREP) and Marc Vives (UPF Data Protection Officer)

Introduction to ethical issues in research

Abstract:

The Institutional Committee for Ethical Review of Projects wants to contribute to the improvement of ethics and personal data protection standards in research activities and academic practices related to human beings within the UPF community. Among other tasks, CIREP is in charge of evaluating research projects subject to ethics review and giving its approval by issuing binding reports. In this talk we will introduce basic research ethics principles that researchers need to take into account when designing and conducting their research projects. We will also review key concepts related to the European General Data Protection Regulation that regulates the processing of personal data. The ethical review process (from application to approval) will also be discussed.

February, 20

15.30

55.309

PhD Research Seminar

By Alastair Porter

Software development best practices for research reproduceability. 

Abstract:

In software development it is considered a best practice to test code, include documentation, use source code management tools, and make frequent backups. A lot of the time technical research tends to eschew these best practices, resulting in missing data, hard to reproduce results, and wasted time. For researchers who haven't worked in or studied software engineering roles, it can often be confusing to know where to start, or how these best practices improve code quality and save time. In this talk I will show some examples why software engineering best practices are a valuable part of technical research and how to start applying them if you do not know what tools and resources are available.