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arjun sawhney

193 days ago
Unfiled. Edited by arjun sawhney 193 days ago
 
184 days ago
Unfiled. Edited by arjun sawhney 184 days ago
Renata R Join WebEx Call: Click Below 
Meeting number: 738 401 704
Meeting password: Learning20170216
 
Speakers
Dr. Polo Chau Machine Learning Tools: blend techniques from machine learning (Belief Propagation), data mining (anomaly detection), visualization and user interaction 
Dr. Le Song Machine Learning in gene regulatory networks, recommendation systems, and more 
 
Dr. Polo Chau is an Assistant Professor at Georgia Tech’s School of Computational Science and Engineering, and an Associate Director of the MS Analytics program. He holds a PhD in Machine Learning and a Masters in human-computer interaction (HCI). His PhD thesis won Carnegie Mellon’s Computer Science Dissertation Award, Honorable Mention. His research group at Georgia Tech bridges data mining and HCI -- innovates at their intersection -- to synthesize scalable, interactive tools that help people understand and interact with big data. He leads the popular annual IDEA workshop that catalyzes cross-pollination across HCI and data mining. He served as general chair for ACM IUI 2015, and is a steering committee member of the conference. His research group have created novel detection technologies for malware (patented with Symantec, protects 120M+ people), auction fraud (WSJ, CNN, MSN), comment spam (patented & deployed with Yahoo), fake reviews (SDM’14 Best Student Paper), insider trading (SEC), unauthorized mobile device access (Wired, Engadget); and fire risk prediction (KDD’16 Best Student Paper, runner up). He received faculty awards from Google, Yahoo, and LexisNexis. He also received the Raytheon Faculty Fellowship, Edenfield Faculty Fellowship, Outstanding Junior Faculty Award. He is the only two-time Symantec fellow. 
 
Talk abstract
At the Polo Club of Data Science, we innovate at the intersection of data mining and human-computer interaction (HCI), combining the best fom both worlds to synthesize scalable interactive tools for making sense of billion-scale graph data. I will present some of our latest systems:
(1) Visage: an interactive visual graph querying approach that empowers users to construct expressive queries, without writing complex code (e.g., finding money laundering rings of bankers and business owners).
(2) Facets & Apolo: combine machine inference and visualization to guide the user to interactively explore large graphs. The user gives examples of relevant nodes, and the systems recommend interesting and surprising areas the user may want to see next.
 
 
Renata R Notes: (Feel free to add questions, links or ideas below) 
arjun s Polo Chau Presentation-Analysis of Big Data as well as small data to understand the challenges. Although, we have access to a large amount of data the question remains how do we understand all the data. The approach we use is by interacting Data mining with Human-computer interaction. both develop methods fro understanding data and we work towards combine both to get the best of both worlds.  Scalable and interactive tool.
Human- In0The-Loop- Graph Analysis
Detecting Fake Yelp Reviews: 6 + common venues within days
 
But, is it easy to build graph queries? 
Query formulation is an incremental process.
VISAGE uses graph autocomplete which helps prevent over specification
 
Compare VISAGE(faster) vs CYPHER
Leading to finding mroe relevant nodes:Apolo (Machine learning + interactive Vis)
 
Renata R
  • Audio Data Analysis | Thursday, January 19th, 1:00 -2:00 pm EST
arjun s Join this open panel discussion if you are a researcher or company working on audio data, in any sector. We will be discussing topics like 3D audio, sonification, speech recognition, and more. It is a two-way discussion so tell us about yourself.
 
 
 
Renata R Speakers:
Audio Data for Virtual and Augmented Reality: Dr. Kyla McMullen, University of Florida
arjun s Audio Data in Monitoring Digital Networks: Dr. David Worrall
 
Renata R Join WebEx Call: Click Below 
Meeting number: 734 713 995
Meeting password: Audio20171901
 
 
arjun s Notes: (Feel free to add questions, links or ideas below) 
 
Dr. David Worrall's Project Link- http://avatar.com.au/netson
 
The Netson(Network Sonification) Project- Representing digital network data in real time
  • Challenges- Capture network data flow charachteristics with minimal impact on network 
  • Induction of minimal monitoring fatigue and also multiple levels of data protection in remote monitoring situations.
  •  
 
Dr. Kyla McMullen Project
Renata R 3D Audio data for variety of projects including Virtual reality, Health, situational awareness, and defense.
 
For more information please visit: https://southbdhub.wordpress.com/vital-data-series/  
 
  • Text Data Analysis | Thursday, December 8th, 1:00 -2:00 pm EST

Join this open panel discussion if you are a researcher or company working on text mining, in any sector. We will be discussing topics like web-scraping, semantic web, analysis tools in R and Python, the benefits of open source search engines such as Solr and elasticsearch as well as current industry search options. It is a two-way discussion so tell us about yourself.
 
 
 
 
Meeting number: 738 118 709
Meeting password: 20161208_Text
The call will be recorded and posted Here: 
 
Speakers:
Text mining in Jobs and Industry: Trey Grainger, Lucidworks (formerly Career Builder) 
Text mining in Business: Matt DeAngelis, Georgia State
Text mining in Urban Planning: Gordon Zhang / Subhro Guhathakurta, Georgia Tech
Text mining in Health: Charity Hilton / Jon Duke, MD, Georgia Tech GTRI/CSE/CS
Text Mining in Education: Renata Rawlings-Goss, South Big Data Innovation Hub
 
Participants:
Renata Rawlings-Goss, co-Executive Director, South Hub
Suranga E Suranga Edirisinghe, HPC Facilitator, GSU
Steve S Stephen Slota, University of California, Irvine/Socio-Technical Team 
Andrew H Andrew S. Hoffman, HCDE/U. Washington/Socio-Technical Team 
Renata R Jinfeng Zhang, Florida State Univ - Statistics/ Text Mining
Giti Javidi, University of South Florida 
Melissa Cragin, Midwest Big Data Innovation Hub
Renata R Trey Grainger, Lucidworks
 Matt DeAngelis, Georgia State
 Gordon Zhang, Georgia Tech
 
Notes: (Feel free to add questions, links or ideas below) 
Trey: Looking into advanced use of Solr to automate some of the common features and integrations. 
What is next: Working toward a text mining spectrum from keyword search to self learning
...

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