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Ben Blaiszik Profile picture
@BenBlaiszik
Nov 7, 2022 • 5 tweets • 3 min read • Read on X
Did you know you can create a Google Scholar profile for your research group?

While GS is mostly used to track individual metrics, this process allows you to track and highlight team and project metrics.

Here's 5 steps to get to this 👇 #AcademicChatter #AcademicTwitter Image
1. Create a group Google Account
2. Navigate to Google Scholar (scholar.google.com) and click "My Profile"
3. Fill in your details Image
4. Add your group's articles.
5. Be sure to select "Make my profile public" in Settings Image
💫 That's it. Now you can track citations and impact for your research group or shared research projects! I hope this can help encourage focus and celebration of team metrics instead of just individual metrics.

✅ Follow me for more tips and tricks like this #MaterialsDataMonth
If anyone makes a page for their research group of project, post a link and a brief description of your work!



scholar.google.com/citations?hl=e…

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More from @BenBlaiszik

Ben Blaiszik Profile picture
Jun 6
Sharing data is critically important for accelerating discoveries & reproducibility, especially in materials science and chemistry. @DataFacility makes it easy to publish large datasets (>TB, millions of files) as citable research objects and we've been busy. We wanted to share just a few enhancements with you!

First, we have redesigned the front page and created a data publication guide to help our users.

#OpenData #MaterialsScienceImage
We also rewrote the search functionality to make it easier to find the data already published.
Further, we added the ability to view Foundry-ML datasets within MDF. Foundry-ML datasets are ML-ready datasets with autoloaders. We've collected 60 of these datasets from the community to kick start your research!

Foundry-ML: github.com/MLMI2-CSSI/fou…
Read 7 tweets
Ben Blaiszik Profile picture
May 21
🚀How can we use LLMs to accelerate scientific discovery? Let's find out! This year, hundreds of people from across the globe worked together in a hackathon to BUILD groundbreaking prototypes — showing the path to breakthroughs in next generation batteries, sustainability, advanced computing, and more.

In this 💪megathread💪, we highlight the 34 incredible prototypes, built in only a day, and their potential impacts across areas of:

- Extracting and Organizing Knowledge
- Improving LLM Property Prediction
- Creation of Novel Human/Computer Interfaces
- Automating tasks and Improving Efficiency Automation
- Reducing Information Friction
- Empowering Learners
- Evaluating LLM Capabilities with Benchmarks

Let’s go!Image
📚It’s important that researchers have shared term definitions when discussing complex topics. Glossagen built a tool that enables automated creation of glossaries for knowledge graphs from research papers. @RadicalAI_inc 2nd prize winner

Team: Plessers, Dieter (KU Leuven), Lederbauer, Magdalena (ETH Zurich, EPFL), Schwaller, Philippe (EPFL)

Link:
🤖 Evaluating the capabilities of LLMs in materials science and helping students learn key concepts is challenging. MaSTeA developed an interactive web app for materials science question answering, and a way to generate an automated benchmark dataset to evaluate LLM capabilities to identify strengths and weaknesses in various subfields, enhancing educational and LLM tools.

Team: Circi, Defne (Duke University), Mohd, Zaki (Indian Institute of Technology Delhi), Gangan, Abhijeet (University of California, Los Angeles), Singh Grover, Hargun (Indian Institute of Technology Delhi), Anees, Faisal (Duke University)

Link:
Read 37 tweets
Ben Blaiszik Profile picture
Mar 24, 2023
We are less than a week from the virtual hackathon for #LLM applications in materials science and chemistry. Here is some inspiration from other's applications to drive you!

🗓️ Register and start teaming today: eventbrite.com/e/llm-march-ma…

#hackathon #openscience #ML #AI
@kmjablonka using fine tuned GPT-3 and GPT-4 (in-line prompting) as a model surrogate for various chemical modeling problems.

Have questions for Kevin? He will be giving a demo during the March 29th live session, and is a co-organizer.

ChatGPT can also be used for applications in drug discovery. Shared via @andrewwwhite01 who is also a hackathon co-organizer and judge.

Read 13 tweets
Ben Blaiszik Profile picture
Nov 18, 2022
Great story from @Mechanophore and colleagues @UofIllinois. From skeptic to believer: the power of models. Let's take a look at some of these journeys and what we can learn.

✨What is your story?✨

#MaterialsDataMonth #academictwitter @OpenAcademics
doi.org/10.1016/j.tet.…
@Mechanophore's story - seeing models make intriguing predictions into reaction behavior. "A key turning point for me was seeing how FEA of Frontal Ring-Opening Metathesis Polymerizations simulates autonomous curing processes by balancing reaction enthalpy with heat transport" Image
@MrBSussels Story - modeled complex reaction mechanisms using a simplified graphical abstraction to create a system of coupled linear equations and analytically solved them to provide an empirical rate law in agreement with the experimental observations. Skeptic → Believer Image
Read 4 tweets
Ben Blaiszik Profile picture
Oct 3, 2022
It's been a wild week already in #ML/#AI for science. Advancements in using diffusion models for protein folding, using learned potentials to discover new catalyst materials, a proposed battery data genome to speed energy storage material discovery, and so much more! 🧵 (1/8)
@KevinKaichuang et al use diffusion models to generate novel foldable protein structures. (2/8)
@_akhaliq presents NeuralPLexer to predict protein-ligand structures. This will help understand the interaction between small molecules and proteins. Also with diffusion models ✨ (3/8)
Read 11 tweets

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