Overview
About Me
Santosh Pandey is an Associate Professor in the Department of Electrical and Computer Engineering at Iowa State University. He has published over 65 refereed papers with his students and collaborators in the areas of bioengineering, microelectronics, microfluidics, sensors, machine intelligence, plant pathology, electrophysiology, data analytics, and drug screening. After graduating with Bachelor of Technology in Electronic and Electrical Communication Engineering from the Indian Institute of Technology (Kharagpur), he completed his M.S. and Ph.D. in Electrical Engineering from Lehigh University in Bethlehem, Pennsylvania.
Santosh Pandey has taught courses in engineering problem solving, semiconductors, microelectronics, MEMS, sensors at Iowa State University, including:
- Engineering Problems with Computer Applications Laboratory (Engr 160)
- Electronic Circuits and Systems (EE 230)
- Semiconductor Materials and Devices (EE 332)
- Physics of Semiconductors (EE 535)
- Physics of Semiconductor Devices (EE 536)
Our Research Interests
We are interested in applications of engineering for life sciences, along with faster & efficient collection of data, and data analysis for extracting key information.
On the hardware side, we have built automated systems, microfluidic chips and sensors for nematode pests, bacteria, and other micro-organisms in plant and animal sciences.
Our students also develop skills in imaging, data science, machine learning, deep learning, and bioengineering in general.
Hosted Podcasts
Contact Info: Santosh Pandey, Email: pandey(AT)iastate.edu
Lab Address: 1050 Coover Hall, ECpE Department, Iowa State University
We are interested in applications of engineering for life sciences, along with faster & efficient collection of data, and data analysis for extracting key information.
On the hardware side, we have built automated systems, microfluidic chips and sensors for nematode pests, bacteria, and other micro-organisms in plant and animal sciences.
Our students also develop skills in imaging, data science, machine learning, deep learning, and bioengineering in general.
