Panacea: a remedy for all ills or difficulties

As defined by Merriam-Webster: "In the Middle Ages and the Renaissance, alchemists who sought to concoct the "elixir of life" (which would give eternal life) and the "philosopher's stone" (which would turn ordinary metals into gold) also labored to find the panacea. But no such medicine was ever found, just as no solution to all of a society's difficulties has ever been found. Thus, panacea is almost always used to criticize the very idea of a total solution. "

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About Us

In current times people think that machine learning is the panacea, a belief that is far from the truth. At panacea lab we aim to build machine learning, computer vision, and NLP methods that help to generate insights from multi-modal large-scale data sources. With applications to precision medicine, medical informatics, astroinformatics and other domains, our work addresses domain-specific problems with data science methods and practices. Additionally, we are fully invested in helping science reproducibility by releasing (when possible) open-source and publicly available datasets and tools to aid reproducibility efforts.

With the new challenges brought by the data deluge in all fields, we are open to collaborations. Contact us here.

Our lab at Georgia State University department of Computer Science is supported by: Department of Veterans Affairs (Grant 1 I01 HX002487-01), National Institute of Aging through Stanford Universitiy's Stanford Aging & Ethnogeriatrics Transdisciplinary Collaborative Center (SAGE) center (Grant 3P30AG059307-02S1), and an internal GSU Research Initiation grant

Software and Datasets

COVID-19 Dataset

COVID-19 Twitter dataset with over 730 Million tweets for scientific research. Downloaded over 30K Times and over 220 stars on GitHub

Zenodo Link |
Github Link


Social Media Mining Toolkit (SMMT) a set of tool to facilitate the gathering and mining of social media data

Github Link


R package for Automated PHenotype Routine for Observational Definition, Identification, Training and Evaluation (APHRODITE). Built the OHDSI collaborative.

Github Link


A curated and standardized adverse drug event resource to accelerate drug safety research. Built for the OHDSI collaborative.

Dryad Link | Github Link


R package for Mapping Between OHDSI Concept Identifiers to Unified Medical Language System (UMLS). Built for the OHDSI collaborative.

Github Link


Provenance-centered dataset of drug-drug interactions.

Github Link


A large-scale solar dynamics observatory image dataset for computer vision applications.

Dataverse Link | Github Link


Introducing a Data Mining Framework for the Creation of Large-scale Content-based Image Retrieval Systems

Github Link

For a other code and datasets visit the lab's github page.

Lab Members


Juan M. Banda, Ph.D.

Principal Investigator


Luis Alberto Robles Hernandez

CS PhD Student


Ever Augusto Torres Silva

Visiting PhD Student

Lab alumni

Ramya Tekumalla - PhD Student - Currently: Data Scientist at Atropos Health
Rajath Chikkatur Srinivasa - MS Student - Currently: KPMG Consultant
Nikhil Gupta - MS Student - Currently: Data Scientist at Domino's
Shivani Bhoite - MS Student - Currently: Software Development Engineer at Amazon
Cynthia Khan - MS Student - Currently: Big Data Engineer at Novelis
Geeth Anirudh Suryadevara - MS Student - Currently: SDE at Spartan Camera
Junzhi Wen - MS Student - Currently: PhD student at GSU
Toqi Tahamid Sarker - PhD Student - Currently: Co-founder,
Bhaskar Ray - PhD Student - Currently: PhD student at GSU
Kimberly Luviano-Garcia - UAP Scholar

Contact Us

Contact info

25 Park Place - Suite 752,
Atlanta, GA 30303

+1 404-413-5585

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