Debasis Mitra is a Professor in the Department of Computer Science at Florida Institute of Technology. He received a Ph.D. in Computer Science from the Center for Advanced Computer Studies of the University of Louisiana at Lafayette. His first Ph.D. was in Physics from the Indian Institute of Technology at Kharagpur. He was an Assistant and Associate Professor in Computer Science at the Jackson State University before joining Florida Institute of Technology in 2001. His current research focus lies somewhere in the mix of knowledge modeling and inverse problems in Physics and Bio-medicine. In the past he has worked on reasoning with spatial and temporal knowledge. He is a recipient of the National Science Foundation Career Award and the HEADWAE award for research and teching excellence in Mississippi.

Courses

• Spring 2009 Course: Computational Molecular Biology
• Fall 2008 Course: Analysis of Algorithms
• Past Course: Constraint Reasoning
• Past Course: Formal Language and Automata Theory

Graduate Students

• Stephen Johnson
• Richard Hoch
• Scott White
• Gary Hrezo
• Ioana Policeanu

Undergraduate Student

• Sammy Waweru

Current Collaborators

• Marcus Hohlmann, Physics and Space Sc. department, FIT
• Trsitan Fiedler, Biological Sc. department, FIT

Summer Interns 2009

• Avishek bannerjee, IIT Khragapur
• Gaurav Mangukya, IIT Kharagpur

Acknowledgements

• US National Science Foundation
• US Department of Homeland Security
• Peter Belhumeur, Columbia U

Projects

INVERSE PROBLEMS

Muon Tomography

Muons are leptons (weakly interacting elementary particles) that are highly penetrating because of low charge (same as that of electron) but high momentum (about two hundred times heavier than electron). This makes them ideal probe for detecting materials with higher atomic numbers )Z). And, steady flux of muons are produced free by cosmic ray at upper atmosphere. For sometime, this type of natural muons are being studied as non-invasive probes for charting magma chambers in volcanos, hidden chambers in pyramids, and yes, you guessed it right, for detecting Uranium-like high-Z materials in cargo containers. We are one of the new kids in the town. Muons are also one of the major by-products of particle-smashing High Energy Physics (HEP) experiments, and muon detector technology development is big game in HEP. We collaborate with a local HEP group which works on such detector development for nuclear contraband identification project for Homeland Security. We work on reconstruction algorithms.

KNOWLEDGE MANAGEMENT

Knowledge Base on Science/Engineering Experiments

In this work, we address the issue of organizing knowledge behind a scientific or engineering experiment. Our objective is help scientist in answering queries about the experiment or data produced for the experiments. A long term goal is to understand how creativity can be computationally modeled in scientific works and how such a knowledge management system can debug an experimental set up. Our application focus is in bio-medical experiments and those in physics.

Database for Science/Engineering Experiments

Science or engineering researchers produce copious amounts of data in their experiments. Often management of data becomes unwildy, even when each data set is not necessarily very large. Typically a researchers keep track of data with directory hierarchy and file naming conventions. This becomes extremely cumbersome and expensive in terms of time needed to find out necessary data and resulting in repeatition of experiments that may have been done before. A database for keeping track of metatdata is essential. We are engaged in studying this aspect of experiment-related data management.

SPATIO-TEMPORAL CONSTRAINT REASONING

Detecting inconsistency in interval-time network

A typical constraint reasoner detects satisfiability in input set of constraints. For a satisfiable network it may also generate a consistent scenario. However, traditionally nothing is done with an inconsistent set of information. Any user of such a system would often wish that the system were more helpful in debugging an inconsistet situation. We address this issue in relation to time-interval relations where constraints are qualitative (e.g., before/after) and disjunctive in nature.

COMPUTATIONAL MOLECULAR BIOLOGY

Protein Structure Comparison

A protein a chain of amino acids that forms a complex structure in 3D. Each protein typically has the same structure and its function is often determined by its structure. Thus, protein's are classified according to their strucutures and comparing prptein structure is a serious algorithmic business. We are engaged in studying and developing such structure comparison techniques.

Publications

Muon Tomography

• “Muon Tomography Algorithms for Nuclear Threat Detection,” "Lecture Notes in Artificial Intelligence" series, Springer Verlag, June 2009, (Proc. of the 22nd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems - IEA/AIE-2009)
  Richard Hoch, Debasis Mitra, Marcus Hohlman, and Kondo Gnanvo. [PDF]
• “Performance Expectations for a Tomography System Using Cosmic Ray Muons and Micro Pattern Gas Detectors for the Detection of Nuclear Contraband,” in Proc. of the IEEE Nucl. Sci. Symp. 2008, Dresden, Germany, pp. 1278-1284, IEEE Cat. CFP08NSS-CDR, ISBN 978-1-4244-2715-4, ISSN 1082-3654, e-Print: arXiv:0812.1007.
  Kondo Gnanvo, Patrick Ford, Jennifer Helsby, Richard Hoch, Debasis Mitra, and Marcus Hohlman. [PDF]
• “GEANT4 Simulation of a Cosmic Ray Muon Tomography System with Micro-Pattern Gas Detectors for the Detection of High-Z Materials,” IEEE Trans. Nucl. Sci., Vol.56, No.3, pp. 1356-1363, June 2009. (Proc. of the 2008 Symposium on Radiation Measurements and Application - SORMA West, Berkeley, June 2008,)
  Marcus Hohlmann, Patrick Ford, Kondo Gnanvo, Jennifer Helsby, David Pena, Richard Hoch, and Debasis Mitra. [PDF]

Spatio-temporal Reasoning

• “Spatial-reasoning for Agents in Multiple Dimensions,” Journal of Universal Computer Science, vol. 8, no. 8, pp. 774-791, August, 2002
  Debasis Mitra, and Gerard Ligozat. [PDF]
• “Explanation Generation over Temporal Interval Algebra,” in Technical Note of AAAI Spring Symposium on Bechmarking Spatial and Temporal Reasoning Systems, Stanford University, March 2009.
  Debasis Mitra. [PDF]
• “Qualitative Direction Calculi with Arbitrary Granularity,” in Pacific Rim Conference on AI (PRICAI), 2004
  Jochen Renz and Debasis Mitra. [PDF]
• More to be posted soon

Computational Molecular Biology

• Coming Soon

Other areas

• “Three generations of research in computational creativity and beyond,” in Association for Advancement of Artificial Intelligence Spring Symposium on Creative Intelligent Systems (AAAI Tech Report). (Eds.) Ventura, D., Maher, M. L., and Colton, S.; Stanford, California, March 2008.
  Debasis Mitra. [PDF]
• “Creativity in Knowledge-bases,” an abstract in NSF Workshop Notes on Creative IT at Washington D.C., January 2009.
  Debasis Mitra. [PDF]
• More to be posted soon