HMData 2020 : Fourth IEEE Workshop on Human-in-the-Loop Methods and Future of Work in BigData

  in Conferences   Posted on June 25, 2020

Conference Information

Submission Deadline Sunday 11 Oct 2020 Proceedings indexed by :
Conference Dates Dec 10, 2020 - Dec 10, 2020
Conference Address Online, Online
Conference & Submission Link
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Call for Papers


The fourth IEEE Workshop on

Human-in-the-Loop Methods and Future of Work

in BigData (HMData 2020) co-located with IEEE Bigdata 2020 (online)

Dec. 10th (Planned)



HMData workshop, which originally began as the “Human-Machine

collaboration in BigData” workshop, will investigate the

opportunities and challenges in human machine collaboration in

work with bigdata, which are described by two terms: Human-in-

the-Loop Methods and Future of Work. Human-in-the-Loop is a

term focusing on the employer’s viewpoint while Future of Work

focuses more on worker’s viewpoint, in both of which the division

of labor among humans and machines is a key issue. This area is

likely to be heavily AI driven, and we intend to invite papers

covering the following aspects, (a) Capturing human capabilities

through intelligent models and how to adapt them through changing

perceptions, needs, and skills. (2) High level tools that provide

the ability for all stakeholders in the new ecosystem, including

regulators for policies and AI workers, to specify their

requirements. (3) system design and engineering of job platforms

for collection, storage, retrieval, and analysis of data deluge

about workers, jobs, and their activities. (4) Benchmarking and

the development of appropriate metrics to measure system

performance as well as human aspects, such as satisfaction,

capital advancement, and equity.

We welcome any interesting ideas and results on any relevant

topics, but this year, we also encourage submitting papers on

new projects inspired by the COVID-19 crisis, such as those on

human-in-the-loop solutions in the pandemic, those on re-evaluating

how we organize labor and how we share work with machines in the

future. To make the workshop an attractive place for those people,

we solicit practitioner papers as well as research papers, in order

to facilitate discussion among researchers who know solutions and

practitioners who know problems. We also would like to make the

place valuable for young researchers. All papers accepted for the

workshop will be included in the Workshop Proceedings published by

the IEEE Computer Society Press, made available at the Conference.



This workshop covers a wide range of topics of human-machine

collaboration in work with bigdata. Keywords include: crowdsourcing,

collaborative recommendation, crowdsensing, workflow model for

humans and machines, incentives, human-assisted bigdata analysis,

bigdata-human interaction, human-machine collaboration in real-world

applications (such as natural disaster response, education, and citizen

science), and ELSI in Human-in-the-loop systems and Future of Work.

We expect submissions to address some of the following issues:

– capturing human characteristics and capabilities,

– stakeholder requirement specification,

– social processes around the human-in-the-loop systems,

– platforms and ecosystems,

– computation capabilities, and

– benchmarks and metrics for human-in-the-loop systems and Future of Work



Kurt Luther (Virginia Tech)

Bio: Dr. Kurt Luther is an associate professor of computer science and

(by courtesy) history at Virginia Tech, based in the Washington, D.C.

area. He directs the Crowd Intelligence Lab, creating new ways for

experts to leverage the complementary strengths of crowdsourced human

intelligence and artificial intelligence (AI) in domains like journalism,

national security, and history. His current research focuses on

supporting open source intelligence (OSINT) investigations, combating

disinformation and misinformation, and identifying unknown people and

places in historical and modern photos. Dr. Luther has been honored with

the National Science Foundation CAREER Award, the Virginia Tech College

of Engineering Outstanding New Assistant Professor Award, and the Purdue

Polytechnic Institute Outstanding Technology Alumni Award. His papers

have received the ACM CSCW Best Paper Award, the AAAI HCOMP Notable Paper

Award, and the ACM IUI Best Paper Award. His software has won the

Microsoft Cloud AI Research Challenge Grand Prize and two HCOMP Best

Demo Awards. His research has been funded by DOD, Google, NEH, NHPRC,

NIH, and NSF; and featured in The Atlantic, CNN, NPR, Smithsonian, and

TIME. He is a member of AAAI and a senior member of ACM. Previously,

Dr. Luther was a postdoctoral fellow in the Human-Computer Interaction

Institute at Carnegie Mellon University. He received his Ph.D. in

human-centered computing from Georgia Tech, where he was a James D. Foley

Scholar. He received his B.S. in computer graphics technology, with

honors and highest distinction, from Purdue University. He also completed

internships at IBM Research, Microsoft Research, and YouTube/Google.


Important Dates (Tentative)

Oct 1 (Thu), 2020: Due date for workshop papers submission

Nov 2 (Mon), 2020: Notification of paper acceptance to authors

Nov 13 (Fri), 2020: Camera-ready of accepted papers

Dec 10-13(Thu-Sun), 2020: Workshops



All submissions must be submitted electronically through CyberChair.

Please prefix your submission category such as [Research Paper] to

the Title of Paper field in the submission page.

For example, if you would like to submit a project-in-progress paper

“Crowd-centric Approach to Digital Archive Maintenance,” you have

to put “[project-in-progress paper] Crowd-centric Approach to Digital

Archive Maintenance” into the Title of Paper field.

All papers accepted for the workshop will be included in the Workshop

Proceedings published by the IEEE Computer Society Press, made

available at the Conference.


Submission Categories

Research Papers (*) (long presentation): They report significant and

original results relevant to the scope of this workshop. We solicit

innovative or thought-provoking work but they do not necessarily

have to reach the level of completion. The expected length is between

4 and 6 pages. The maximum length is 10 pages, though the paper

should be commensurate with the size of the contribution.

Practitioner papers (*)(long presentation): They present interesting

problems that require human-in-the-loop solutions in a variety of

application domains, or present the interesting results of applying

existing human-in-the-loop solutions to their domains. The expected

length is between 4 and 6 pages. The maximum length is 10 pages,

though the paper should be commensurate with the size of the contribution.

Project-in-progress papers (short presentation): They present the goals,

challenges, and preliminary results of research or real-world projects

in progress. The maximum length is 3 pages.

(*) Some of the papers submitted to the research or practitioner paper

categories may be accepted as project-in-progress papers and allotted

to short presentation slots.


Papers should be formatted to IEEE Computer Society Proceedings

Manuscript Formatting Guidelines in the IEEE Bigdata 2020 CFP page




Senjuti Basu Roy (NJIT)

Alex Quinn (Purdue University)

Atsuyuki Morihsima (Univesity of Tsukuba)

Program Committee



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