Project Showcase

The traditional KDD Project Showcase Track offers a full day focused exclusively on innovative KDD-relevant projects from national and regional funding programs, as well as corporate, start-up, and nonprofit channels. We seek to bring together a diverse community of researchers in Machine Learning and Data Analytics, as well as partnerships in the social and physical sciences/arts, to show the state-of-the-art in research and applications.

We are excited to announce the project showcase program for 2019. We will be hosting two keynote talks: Kuansan Wang, Microsoft Research Outreach Academic Services and Dennis Pamlin, RISE Research Institutes of Sweden and UN Development Programme.

The program this year features 17 papers that will be presenting their demos/poster. Additionally, ten out of them will have a short oral presentation prior to the corresponding demo/poster session. The program is structured in three presentation sessions and two demo/poster sessions.

Welcome to the KDD-2019 Project Showcase Track!


Wednesday August 7, 2019

08:30AM-3:30PM Program (location: Dena’ina Center)

Chairs: Dunja Mladenic and James Hodson


  • 08:30am – 09:10am Keynote: Kuansan Wang “Challenges of Innovative Research Projects
  • 09:10am – 09:30am Data & Frameworks (2 projects, 10 mins each)
  • 09:30am – 10:00am Coffee break
  • 10:00am – 11:10am Data & Society (5 projects, 10 mins each)
  • 11:10am – 12:00pm Demos I (the presented 7 projects + 2 posters)
  • 12:00pm – 13:30pm Lunch break·
  • 13:30pm – 14:10pm Keynote: Dennis Pamlin, “AI, Big Data, and the UN Sustainable Development Agenda
  • 14:10pm – 14:40pm Data for Earth Sensing (3 projects, 10 mins each)
  • 14:40pm – 15:30pm Demos II (thepresented 3 projects + 5 posters)

Detailed Program

Data & Frameworks, Demos 1

MLsploit: A Framework for Interactive Experimentation with Adversarial Machine Learning Research
Nilaksh Das, Siwei Li, Chanil Jeon, Jinho Jung, Shang-Tse Chen, Carter Yagemann, Evan Downing, Haekyu Park, Evan Yang, Li Chen, Michael Kounavis, Ravi Sahita, David Durham, Scott Buck, Polo Chau, Taesoo Kim and Wenke Lee

Midas - An interactive data catalog for data science teams
Patrick Holl and Kevin Goßling

Data & Society, Demos I

CubeNet: Multi-Facet Hierarchical Heterogeneous Network Construction, Analysis, and Mining
Carl Yang, Dai Teng, Siyang Liu, Sayantani Basu, Jieyu Zhang, Jiaming Shen, Chao Zhang, Jingbo Shang, Lance Kaplan, Timothy Harratty and Jiawei Han

Bridging Social Graphs with Character-Centered Story Contexts in Videos
Jiang Gao

X5GON: Connecting OER Repositories
Jasna Urbančič and Erik Novak

Technology Trend Analysis: Visualizing the popularity and development
Zhenhuan Chen, Jie Tang, Yutao Zhang and Bo Gao

SILKNOW – Multilingual Text Analysis for Silk Heritage
Dunja Mladenic, Mar Gaitán and Raphäel Troncy

Demos 1

Multi-Modal Context Aware Monitoring System for Smart Classrooms
Sangeeta Ghangam, Sanjay Addicam, Gabriel Silva, Wendy Chin and Michelle Sim

AnaBot: Lessons from Building a Serial Chatbot in Collaboration with Analysts and Linguists
Hongche Liu, Jaewon Yang and Qi He

Data for Earth Sensing, Demos II

Urban-Net: A System to Understand and Analyze Critical Infrastructure Networks for Emergency Management
Anika Tabassum, Supriya Chinthavali, Sangkeun Lee, Liangzhe Chen and B. Aditya Prakash

enviroLENS – An innovative Earth Observation Platform for Environmental law enforcement
Samo Kralj, Klemen Kenda, Erik Novak, Inna Koval, Florian Girtler, Magdalena Steidl and Franziska Albrecht

TopicMine: User-Guided Topic Mining by Category-Oriented Embedding
Yu Meng, Jiaxin Huang, Zihan Wang, Chenyu Fan, Guangyuan Wang, Chao Zhang, Jingbo Shang, Lance Kaplan and Jiawei Han

Demos II

Efficient Real-Time Big Data Processing at the Edge of the Network – The PrEstoCloud project
Salman Taherizadeh, Blaz Novak, Sebastjan Vagaja, Marija Komatar and Marko Grobelnik

Mining Large-scale News Articles For Predicting Forced Migration
Sadra Abrishamkar, Forouq Khonsari, Aijun An, Jimmy Huang and Susan McGrath

A Novel Approach for Retrieving Chlorophyll-a Concentrations from Satellite Ocean Color Data
Yingying Wu and Joaquim Goes

Seeing the Unseen: Mining an ocean of data for retrieving the vertical distribution of Chlorophyll-a from Satellite Ocean Color Data
Jinghui Wu, Joaquim Goes and Yingying Wu

Modeling and predicting human social behavior
Ashwin Bahulkar, Boleslaw K. Szymanski, Kevin Chan and Omar Lizardo

Program committee

  • Santiago Barona, Bloomberg LP
  • Janez Brank, J. Stefan Institute
  • Kaja Dobrovoljc, University of Ljubljana
  • Jasminka Dobsa, University of Zagreb
  • Johannes Erett, Cognism Ltd
  • James Hodson, J. Stefan Institute & AI for Good Foundation
  • Branko Kavsek, University of Primorska
  • Omar Malik, Rensselaer Polytechnic Institute
  • Dunja Mladenic, J. Stefan Institute
  • Inna Novalija, Jozef Stefan Institute
  • Jasna Urbancic, Jozef Stefan Institute
  • David Yeniclik, ETH Zurich

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