About Me

Alauddin Ahmed, Ph.D. (Principal Investigator)
Assistant Research Scientist

My vision is:

To address some of the grand challenges of our society such as clean energy, carbon dioxide capture, and responsible use of machine learning (ML) and artificial intelligence (AI). 

My belief as a PI is:

Solving complex problems requires three ingredients: interdisciplinary collaboration, a diverse team, and a bridge between conventional and out-of-the-box thinking. Respect and kindness connect these ingredients towards achieving a sole purpose: innovation.  

My major research contributions are:

  • Published in prestigious venues such as Nature Communications, Journal of the American Chemical Society, Energy & Environmental Science, Angewandte Chemie International Edition, Patterns (cell press), and Chemistry of Materials.
  • Discovered seven world-record-setting materials for hydrogen and natural gas storage in metal organic frameworks (MOFs).
  • Developed computational methods for the discovery and design of material.
  • Developed a novel approach for generating machine-learning-guided phenomenological equations.
  • Developed a novel computational method for connecting solvation thermodynamics and structure- property relationships of chemical compounds.

My research is highlighted in premier journals such as Energy & Environmental Science, Nature Communications, Chemistry of Materials, and Patterns (cell press).

Also, my research is featured in several news outlets, including R&D, Physics.org, Futurity, Tech Xplore, and Newswise.

My expertise is:

At the intersection of multiple technical domains, including high-throughput computing; materials science & engineering; chemical science & engineering; data science & engineering; machine learning (ML) & artificial intelligence (AI). I have a proven history of Research and Development (R&D) in the following areas:

  • Carbon capture materials & systems 
  • Hydrogen storage materials & systems 
  • Thermal energy storage materials & systems 
  • Novel liquid electrolyte discovery for batteries
  • Multiscale modeling and simulation of battery electrodes 
  • Responsible ML/AI and causal inference