ACM and IMS to hold first ever Data Science Conference


The Affiliation for Computing Equipment (ACM) along with the Institute of Mathematical Statistics (IMS) will maintain the first-ever ACM-IMS Foundations of Knowledge Science (FODS) Convention nearly on October 19-20.

This interdisciplinary occasion will convey collectively researchers and practitioners to handle foundational information science challenges in prediction, inference, equity, ethics, and the way forward for information science.

“Knowledge science is a brand new, rising subject, constructing its foundations from pc science, statistics, and lots of different quantitative disciplines,” mentioned FODS Normal Co-chair Jeannette Wing, Columbia College, and Fellow, Affiliation for Computing Equipment.

“Massive information shouldn’t be new: by way of giant, one-of-a-kind, costly devices, scientists have been gathering and producing huge quantities of knowledge for many years.

What has modified is that the web has turn out to be an instrument for anybody, not simply scientists, to gather and generate information and that that information is about folks.

We even have highly effective AI, machine studying, and statistical strategies that enable us to interpret and achieve worth from the info in new methods.

And since a lot information is about folks, we should tackle upfront questions of ethics and privateness. We’re witnessing a brand new period the place each sector, together with healthcare and finance, is being remodeled by information science.

We consider that our interdisciplinary method to organizing this convention will make it an vital analysis gathering for a few years to return.”

“FODS is a first-of-its-kind convention in that it’s a collaboration between the 2 main scientific societies in computing and statistics,” added FODS Normal Co-chair, David Madigan, Northeastern College, and Fellow, Institute for Mathematical Statistics.

“We consider this cross-collaboration between pc scientists and statisticians is the best approach to foster groundbreaking new analysis on this subject.

Constructing on the success of the preliminary summit ACM and IMS co-organized in 2019, we have now put collectively an thrilling program that includes the world’s high researchers and practitioners.

We additionally hope that the digital nature of this 12 months’s convention will encourage members from around the globe to interact with us.”

ACM-IMS FODS 2020 HIGHLIGHTS: Keynote Audio system

  1. “AutoML and Interpretability: Powering the Machine Studying Revolution in Healthcare”
  • Speaker: Michaela van der Schaar, The Alan Turing Institute

AutoML and interpretability are each elementary to the profitable uptake of machine studying by non-expert end-users.

This keynote presents state-of-the-art AutoML and interpretability strategies for healthcare developed in van der Schaar’s lab and the way they’ve been utilized in numerous medical settings (together with most cancers, heart problems, cystic fibrosis, and lately Covid-19).

It then explains how these approaches type a part of a broader imaginative and prescient for the way forward for machine studying in healthcare.

2.“Semantic Scholar, NLP, and the Struggle Towards COVID-19”

  • Oren Etzioni, Allen Institute for AI (AI2)

Etzioni’s speak will describe the dramatic creation of the COVID-19 Open Analysis Dataset (CORD-19) on the Allen Institute for AI and the broad vary of efforts, each inside and outdoors of the Semantic Scholar challenge.

That is to garner insights into COVID-19 and its remedy primarily based on this information. The speak will spotlight the tough issues going through the rising subject of Scientific Language Processing.

FODS 2020 Papers (Partial Checklist)

  • For a listing of all accepted papers, go to right here.

3. “Incentives Wanted for Low-Price Honest Knowledge Reuse”

  • Roland Maio, Augustin Chaintreau, Columbia College

One of many central targets in algorithmic equity is to construct methods with equity properties that compose gracefully.

Though the significance of this objective was acknowledged early, restricted progress has been made. On this work, Maio and Chaintreau suggest a contemporary method to constructing pretty composable data-science pipelines by incorporating details about events’ incentives into equity interventions.

Their outcomes open a number of new instructions for analysis on honest data-science pipelines, honest machine studying, and algorithmic equity extra broadly.

4.“Making use of Algorithmic Accountability Rules and Frameworks to Ecosystem Forecasting: A Case Research in Forecasting Shellfish Toxicity within the Gulf of Maine”

  • Isabella Grasso, David Russell, Jeanna Matthews, Clarkson College; Abigail Matthews, College of Wisconsin-Madison; Nick Report, Bigelow Laboratory for Ocean Sciences

Ecological forecasts are used to drive choices that may have important impacts on the lives of people and on the well being of ecosystems.

On this paper, the authors focus on their expertise with making use of algorithmic accountability rules and frameworks to ecosystem forecasting, particularly to forecasting shellfish toxicity within the Gulf of Maine utilizing a dataset produced by the Marine Biotoxin Monitoring Program performed by the Division of Marine Sources (DMR).

 5.“Fashion CAPTCHA: CAPTCHA primarily based on style-transferred photographs to defend in opposition to Deep Convolutional Networks”

  • Haitian Chen, Bai Jiang, and Hao Chen

CAPTCHA has discovered widespread functions for bot detection within the our on-line world.

Many CAPTCHAs are primarily based on visible notion duties equivalent to textual content recognition, objection recognition, and picture classification.

Nonetheless, they’re below severe risk from trendy visible notion applied sciences, particularly deep convolutional networks (DCNs).

The authors suggest a novel CAPTCHA, referred to as StyleCAPTCHA, which asks customers to categorise stylized human versus animal face photographs.

Every stylized picture in StyleCAPTCHA is created by combining the content material representations of a human or animal face picture and the fashion representations of a mode reference picture, each of that are hidden from the consumer.


  1. “Causal Reasoning Tutorial”
  • David Blei, Columbia College

Blei is a professor of Statistics and Laptop Science at Columbia College. He’s additionally a member of the Columbia Knowledge Science Institute. He works within the fields of machine studying and Bayesian statistics.

2.“Equity, Privateness, and Ethics in Knowledge Science Tutorial”

  • Michael Kearns, College of Pennsylvania

Kearns is a professor of Laptop and Data Science on the College of Pennsylvania.

He’s additionally the Founding Director of the Warren Middle for Community and Knowledge Sciences on the College of Pennsylvania.

His analysis pursuits embody matters in machine studying, algorithmic sport concept and microeconomics, computational social science, and quantitative finance and algorithmic buying and selling.

About ACM

ACM, the Affiliation for Computing Equipment, is the world’s largest academic and scientific computing society, uniting computing educators, researchers, and professionals to encourage dialogue, share assets, and tackle the sphere’s challenges.

ACM strengthens the computing occupation’s collective voice by way of robust management, promotion of the best requirements, and recognition of technical excellence.

ACM helps the skilled progress of its members by offering alternatives for life-long studying, profession growth, {and professional} networking.

About IMS

IMS, the Institute of Mathematical Statistics, is the main group fostering the event and dissemination of the speculation and functions of statistics.

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