• Complex Systems Lab

    The Ground Zero of Computational Gastronomy

  • Complex Systems Lab

    Making Food Computable

  • Complex Systems Lab

    Transforming Food with Artificial Intelligence

We make food computable

‘Computational Gastronomy' presents an all-new paradigm for data-driven investigations of food and cooking, considered to be artistic endeavors.

Join us to witness a blend of food and computing.
Symposium on Computational Gastronomy
Registration Link
21 December 2022 (Wednesday)

Kaggle Challenges for Data Scientists
How sweet is that? | What cuisine is that?
What dish is that? | Bitter or not? | Sweet or not?

We are scouting for Ph.D. Research Scholars (and research interns). Apply!


We build keystone data repositories for food. RecipeDB, FlavorDB, BitterSweet, DietRx, SpiceRx & Ayurveda Informatics.


We create algorithms for analyzing food data. Food pairing analysis, culinary fingerprints, taste & sweetness prediction.


Among other exciting things, we are 'generating novel recipes' using artificial Intelligence.


Making Food Computable with Data Science and Artificial Intelligence.

  • RecipeDB

    A structured repository of recipes from across the globe

  • FlavorDB

    A repository of flavor molecules found in food ingredients

  • SpiceRx

    A platform for exploring the health impacts of culinary herbs and spices

  • DietRx

    A platform for exploring the health impact of dietary ingredients

  • SerpentinaDB

    A resource for prospection of therapeutic compounds of R. serpentina


Setting the foundations of data-driven food innovations

Our team skills

The team of research scholars and interns is highly skilled in computer science, data science, machine learning, and artificial intelligence.

Food Databases
Gastronomy Applications

News & Views


  • "BitterSweet: building machine learning models for predicting the bitter and sweet taste of small molecules", Scientific Reports (2019).
  • "Data-driven analysis of biomedical literature suggests broad-spectrum benevolence of culinary herbs and spices", PLoS One (2018).
  • "A hierarchical anatomical classification schema for prediction of phenotypic side effects", PLoS One (2018).
  • "SpiceRx: an integrated resource for the health impacts of culinary spices and herbs", bioRxiv (2018)
  • "A distance constrained synaptic plasticity model of C. elegans neuronal network", Physica A (2016).
  • "Differential network analysis reveals evolutionary complexity in secondary metabolism of Rauvolfia serpentina over Catharanthus roseus", Frontiers in Plant Science (2016).
  • "Tyrosine and tryptophan coated gold nanoparticles inhibit amyloid aggregation of insulin", Amino Acids (2015).
  • "Engineering a thermo-stable superoxide dismutase functional at sub-zero to >50 degree celcius, which also tolerates autoclaving", Scientific Reports, (2012).
  • Ganesh Bagler*, "Complex Network Models of Protein Structures: Structural correlates of biophysical properties", Lambert Academic Publishing (Germany), ISBN: 978-3-8433-5860-6 (2010; BOOK).
  • "Analysis of Airport Network of India as a Complex Weighted Network", Physica A (2008).


Making a case for data-driven explorations of food

Get in touch

Prof. Ganesh Bagler
Infosys Center for Artificial Intelligence
Department of Computational Biology, IIIT-Delhi, New Delhi