Amit Chattopadhyay

Assistant Professor



  • Ph.D. (University of Groningen)

Dr. Amit Chattopadhyay received his PhD degree on "Certified Geometric Computation" in Jan 2011 from Johann Bernoulli Institute of Mathematics and Computer Science of University of Groningen in the Netherlands. After receiving his PhD he worked as a postdoctoral fellow at Universite Catholique de Louvain in Belgium (2011-2012), at University of Leeds in UK (2012-2015) and at IISc, Bangalore (2015-2016). He holds a M.Tech degree (2004) in Computer Science from Indian Statistical Institute (Kolkata) and M.Sc degree (2002) in Mathematics from Indian Institute of Technology (Kharagpur). His research interests include Computational Topology and Data Analysis, Certified Geometric Computation, Scientific Visualization, Optimization on Matrix Manifolds and Level Set Method.


Research Interests

  • Topological Data Analysis and Visualization, Certified Geometric Computation, Optimization on Matrix Manifolds and Level Set Methods.

Selected Publications


Computer Science:

  • GEN512-Mathematics for Machine Learning, for M.Tech and iMtech, IIIT-Bangalore, (Lecturer)
  • CS709-Geometric Modeling, for M.Tech, IIIT-Bangalore, (Lecturer)
  • CS815-Topological Data Analysis, Elective for M.Tech, IIIT-Bangalore (Lecturer)
  • Numerical Computation and Visualization, for Undergraduate, School of Computing, University of Leeds (Teaching Assistant)
  • Mechanics of Structures with Graphics, for Undergraduate, MEMA, UCL, Belgium (Teaching Assistant)


  • SM201-Maths 3, Vector Analysis, Differential Equation, for IM.Tech, IIIT-Bangalore, (Lecturer)
  • GEN504-Linear Algebra, for M.Tech, IIIT-Bangalore, (Lecturer)
  • BS109-Probability and Statistics, for IM.Tech, IIIT-Bangalore, (Lecturer)
  • Vector Analysis, for Undergraduate, JBI, University of Groningen (Teaching Assistant)

other Information

Open Positions:

I have few openings for students interested in doing PhD or MS by research or Master-project or internship positions in the following topics. Interested candidates can apply by sending (i) CV and (ii) a letter of motivation (please read the project descriptions first) to my e-mail-id:


1. Topological Data Analysis: Tools for Multivariate (funded by SERB-CRG, 2019-2022)

A wide range of data that appear in scientific experiments and simulations are multi-field or multivariate (involving multiple scalar fields simultaneously). For example, the time-varying spatial density data of proton and neutron in the nucleus of a Plutonium atom – where the goal is to detect the time stamp of nuclear scission; molecular biology data of Electrostatic and van der Waal forces – where the goal is to study the protein-protein interaction; combustion data – where the goal is to study the progress of combustion with the fuel in process and so on. Topological and geometrical analysis of such data aims to reveal interesting features useful to the domain scientists. The goal of this project is to develop robust tools for extracting and visualizing topological features based on Reeb space, Reeb skeleton, fiber surfaces, multi-dimensional persistent homology and other techniques from computational topology.


2. Certified Geometric Computation

Certified geometric computation, is a newly emerging branch of computing science where the main goal is not only numerical accuracy, but above all the geometric and topological correctness of the output. More precicsely, in certified geometric computation, the challenge is to develop algorithms for computing topologically correct and geometrically close approximations of implicit or explicit input shapes.


3. 3D Volumetric Shape Reconstruction from 2D Image Slices

In computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound imaging, reconstruction of 3D volumetric shape from the 2D cross-sectional images is a challenging problem because of large and unequal spacing between the slice images. In the current project we consider the information of the planar contours extracted from the cross-sectional images to reconstruct the topologically correct (certified) 3D shape.