Live from Harvard: Join us at the #FASPDA Postdoctoral Symposium

Check out the poster session; meet Elsevier data scientists and our colleagues in the Harvard Data Science Initiative

Dr. Helena Deus, Director of Disruptive Technologies at Elsevier. shows her poster: “Pattern matching with machine learning can help systematic reviews of biomedical literature.” (Photos by Alison Bert)
Dr. Helena Deus, Director of Disruptive Technologies at Elsevier. shows her poster: “Pattern matching with machine learning can help systematic reviews of biomedical literature.” (Photos by Alison Bert)

Update: Check out some highlights of the event, including livestreams of researchers talking about their posters.


CAMBRIDGE, Mass —  About 400 people are expected to gather here Thursday afternoon, including faculty, grad students and undergraduates. Postdocs in a range of fields will discuss their research with each other in a relaxed, collegiate atmosphere. Several of Elsevier's data scientists will also present posters, featuring their work at the intersection of big data, AI and scholarly research.

The event begins at 2 pm with the keynote speech by Dr. David Parkes, Professor of Computer Science and Co-Director of the Harvard Data Science Initiative.

We will be there to live stream some of the activities.

The event is presented by the Faculty of Arts and Sciences Postdoctoral Association (FASPDA), which  represents over 1,000 postdocs from Harvard, including researchers in engineering, physics, mathematics, statistics, computational sciences, chemistry and molecular biology. Most are from life sciences.

The top three poster owners will be awarded travel grants to participate in scientific meetings.


Live broadcasting and updates

We're live streaming and posting updates here on Thursday afternoon, May 31. In addition, you can follow us on social media:


Congratulations to the postdoc poster winners!

Poster winners were Andrey V. Shubin, PhD, and Jenan Kharbush, PhD (tied for third place); Marianne Grognot, PhD (first place); and Sophie Pryal Regnault, PhD (second place). They are all postdoctoral researchers at Harvard.

  • First place: Dr. Marianne Grognot
  • Second place: Dr. Sophie Pryal Regnault
  • Third place (tie): Andrey V. Shubin and Jenan Kharbush

Using deep learning to improve knowledge extraction

Dr. Rick Misra, senior product manager for ScienceDirect, talks about using deep learning to improve foundational knowledge extraction.


Visualizing DNA molecules counting

PhD candidate Rui Wang of the Harvard School of Engineering and Applied Sciences (SEAS) talks about "visualizing DNA molecules counting."

Dr. Alison Bert, who covered the event as an Executive Editor at Elsevier, poses with Rui Wang, a PhD candidate in Harvard's School of Engineering and Applied Sciences, and her colleague Dr. Xingcai Zhang, a postdoctoral researcher at SEAS.


Extracting knowledge from Elsevier's content at scale

Dr. Kaushik Raha, Director of Smart Content, Health Sciences at Elsevier, talks about extracting knowledge from our content at scale.


Pattern matching with machine learning can help systematic reviews of biomedical literature

Dr Helena Deus, Director of Disruptive Technologies at Elsevier, talks about her poster.

A knowledge graph that captures the world's medical concepts

Elsevier’s Mev Samarasinghe, VP of Search and Discovery, Healthcare, talks about Elsevier’s knowledge graph that captures the world’s medical concepts and the relationships between them.


Dr. Nan Jiang on single cell nanoengineering

Dr Nan Jiang, a Postdoctoral Researcher in the School of Engineering and Applied Sciences, talks about her poster on single cell nanoengineering.


How rewards are encoded in the zebrafish brain

Neuroscience Postdoc Joao Marques talks about his research into how rewards are encoded in the zebrafish brain.


How can we train the brain (and win the Rhino Cup)?!

Dr. Steffen Wolff on how the brain works in training motor skills in animals and athletes. He's a postdoctoral fellow in Harvard's Dept. of Organismic and Evolutionary Biology/Center for Brain Science.


How many magnitude 9 earthquakes are possible?

Dr. Shannon Graham, a 2017 poster winner who is now Visiting Assistant Prof in Boston College Dept of Earth and Environmental Science, talks about using the Global Block Model to predict the number of magnitude 9 earthquakes that could occur in our lifetime.


Keynote: Prof. David Parkes

Computer Science Professor David Parkes, Director of the Harvard Data Science Initiative, gives the keynote. (Apologies: we had audio problems for the first several minutes.)

Learn about Elsevier's collaboration with the Harvard Data Science Initiative

Ceilyn Boyd, Research Data Program Manager for the Harvard Library, speaks at the roundtable on "Key Factors for Scientific Impact on Policy" as Dr. Michelle Gregory, VP of Content and Innovation at Elsevier (left), and Anita de Waard, VP of Research Data Collaborations at Elsevier, look on. (Photo by Alison Bert)

The Harvard Data Science Initiative (HDSI) was launched in March 2017 “to unite (data science) efforts across the university, foster collaboration in both research and teaching, and catalyze research that will benefit our society and economy.” Elsevier is making a substantial donation to HDSI over the next five years, while also providing datasets and ontologies when possible along with technological expertise.

Last November, experts from Harvard and Elsevier held a series of roundtables to see how we could join forces to address problems of societal importance through data curation and analytics. In exploring the application of data science to evidence-based policy, precision medicine and healthcare, participants talked about their research interests, compared the data they had access to, and suggested projects to collaborate on. The conversation traversed highly technical realms like causal inference, behavioral models and natural language processing, while delving into issues that affect our daily lives.

The roundtables were laid the foundation for future collaborative projects. Read more.

Quick question for you

Which terms do you most associate with Elsevier? (check all that apply)

Data and analytics
Research platforms
Technology
Decision support tools
Publishing
Books and journals
Scientific articles
Healthcare content

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