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Pengsheng Ji

Associate Professor and Associate Head, Department of Statistics
Education:
  • PhD, Statistics, Cornell University
  • MS, Statistics, Nankai University
  • BS, Mathematics, Nankai University
Of note:

Research Interests

  • Network Data Analysis
  • Machine Learning
  • Variable/Feature Selection
  • Nonparametric Testing
  • Rare and Weak Signals in Big Data
  • Scientometrics and Bibliometrics
  • Bioinformatics

Jeremy Davis

Assistant Professor, Department of Philosophy

Dr. Davis's research is broadly in applied ethics, with a current focus on ethical issues surrounding the use of big data technologies by institutions that are typically thought to have justified claims to the use of force—in particular, the criminal justice system, police departments, and the military. His research explores a range of moral challenges posed by the increasing use of algorithms by these institutions, such as the impact on trust and institutional legitimacy, whether specific actors are morally justified in relying on these systems within these institutional structures, and what factors can and should be incorporated into these predictive systems.

Education:
  • Ph.D, Philosophy, University of Toronto
  • B.A. (Honors), Philosophy, University of Missouri

Anna Abraham

E. Paul Torrance Professor, Department of Educational Psychology
Director, Torrance Center for Creativity & Talent Development

Anna Abraham, Ph.D. is the E. Paul Torrance Professor at the Department of Educational Psychology and the Director of the Torrance Center for Creativity and Talent Development at UGA’s Mary Frances Early College of Education. She is the Program Coordinator for the Interdisciplinary Certificate in Creativity and Innovation (ICCI). She also serves as a Neuroscience faculty member of the Integrated Life Sciences Program (ILS) and is an affiliate of the Owens Institute for Behavioral Research (OIBR). She leads the Creativity and Imagination Lab at UGA.

Dr. Abraham’s educational and professional training has been within the disciplines of psychology and neuroscience. She has worked across a diverse range of academic institutions and departments the world over, all of which have informed her multidisciplinary focus. She investigates the psychological and neurophysiological mechanisms underlying creativity and other aspects of the human imagination, including the reality-fiction distinction, mental time travel, social and self-referential cognition, and mental state reasoning. She has penned numerous publications including the book, The Neuroscience of Creativity (2018, Cambridge University Press), and the multidisciplinary edited volume, The Cambridge Handbook of the Imagination (2020). She is the Founding Editor of an innovative short book series, the Cambridge Elements in Creativity and Imagination.

Education:
  • PhD in Neuroscience, Ruhr University Bochum, Germany
  • MSc in Psychology, University of Essex, UK
  • BA (Hons) in Psychology, Lady Shri Ram College, University of Delhi, India

     

Jooyoung Kim

Professor, Department of Advertising & Public Relations, Grady College of Journalism & Mass Communication
Dan Magill Georgia Athletic Association Professor

Dr. Jooyoung Kim is a Professor of Advertising in Grady College of Journalism and Mass Communication at the University of Georgia. He is also the Executive Director of the Business and Public Communication Fellows Program in cooperation with Cox International Center for Mass Communication Training and Research. Dr. Kim’s research seeks to advance the scientific knowledge on understanding the interactions between advertising and consumers across the media platforms, including emerging digital media such as the metaverse. His research activities include numerous conference presentations, invited speeches at academic and business venues, and many publications in leading advertising journals such as the Journal of Advertising and the International Journal of Advertising. He was the Secretary of the American Academy of Advertising in 2021-2022 and is the Editor-in-Chief of the Journal of Interactive Advertising.

Education:

Ph.D., Mass Communication, University of Florida, Gainesville

M.A., Integrated Marketing Communications, University of Colorado at Boulder

B.A., Economics, Hongik University, Seoul

Personal Website:

Yuri V. Balashov

Professor, Department of Philosophy
Education:
  • Ph.D. Philosophy, 1998 University of Notre Dame (Notre Dame, Indiana)
  • Candidate of Philosophy, 1986 Institute of Philosophy, Russian Academy of Sciences
  • M.S. Physics, 1983 Moscow Institute of Physics and Technology
Research Interests:

Philosophy of Science

Metaphysics

Philosophy of Language/Linguistics

Logic

Translation Studies

Of note:

Dr. Balashov's new interdisciplinary project is to explore the uneasy, complicated relationship between human and machine translation. In form, the project is a case study of the history and current state of both fields conducted from the complementary perspectives of three theoretical disciplines. The project includes: (i) a theoretical component focused on the representation of linguistic meaning in various human, machine, and hybrid human-machine translation systems; and (ii) a practical component focused on the different forms of human-machine symbiosis in technical (non-literary) translation areas and ways of improving them.
The two aspects of the project are interrelated: a better understanding of the theoretical (cognitive, linguistic, philosophical) foundations of human and machine translation may suggest new ways of leveraging their strengths and overcoming their weaknesses; on the other hand, a close look at how human and machine translation interact in real life may offer new insights into how physical systems represent linguistic meaning and, more ambitiously, what linguistic meaning consists in.
Philosophers have approached the problem of meaning from many angles, but never in the context of recent developments in translation technologies.

Personal Website:

Exploring the Limits of Large Scale Pre-training

Hanie_pic
Dr. Hanié Sedghi
Google Brain
Google
Online

Registration Required

Recent developments in large-scale machine learning suggest that by scaling up data, model size, and training time properly, one might observe that improvements in pre-training would transfer favorably to most downstream tasks. In this work, we systematically study this phenomenon and establish that, as we increase the upstream accuracy, the performance of downstream tasks saturates.

In particular, we investigate more than 4800 experiments on Vision Transformers, MLP-Mixers, and ResNets with a number of parameters ranging from ten million to ten billion, trained on the largest scale of available image data (JFT, ImageNet21K) and evaluated on more than 20 downstream image recognition tasks. We propose a model for downstream performance that reflects the saturation phenomena and captures the nonlinear relationship in the performance of upstream and downstream tasks. Delving deeper to understand the reasons that give rise to these phenomena, we show that the saturation behavior we observe is closely related to the way that representations evolve through the layers of the models. We showcase an even more extreme scenario where performance on upstream and downstream are at odds with each other. That is, to have a better downstream performance, we need to hurt upstream accuracy.

Dr. Hanié Sedghi is a senior research scientist at Google Brain, where she leads the "Deep Phenomena" research group. Her approach is to bond theory and practice in large-scale machine learning. Her primary research interest is understanding and improving deep learning.

Prior to Google, she was a research scientist at Allen Institute for Artificial Intelligence and before that, a postdoctoral fellow at the University of California, Irvine. Hanié received her Ph.D. from the University of Southern California with a minor in mathematics and her MSc and BSc from the School of Electrical and Electronic Engineering at Sharif University of Technology, Iran.

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