Lecturer, Computer Science
Department of Computer Science · University of Houston
3551 Cullen Blvd, Houston, TX 77204 · USA
You can reach me at: [email protected] or [email protected]
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I am a Geospatial Data Scientist with a decade-long focus on ML/AI. I particularly specialize in remote sensing, geotechnical engineering, geostatistics, agent-based modeling and visual place recognition. I have worked in blockchain-based edge computing, post-disaster recovery systems and Lunar exploration methodologies. I enjoy lecturing and teaching undergraduate students.
University of Houston, Houston, TX
Dissertation: "Spatial Computing Frameworks for Adaptive Disaster Response and Visual Place Recognition." Supervisor: Dr. Christoph F. Eick.
Lamar University, Beaumont, TX
Dissertation: "A Data Mining Framework for Analysing Geospatial-temporal Data." Supervisor: Dr. Sujing Wang.
Indian Institute of Remote Sensing, Dehradun, India
Project: "Designing an efficient web-based 3D GIS platform for LU/LC index measurement."
West Bengal University of Technology, Kolkata, India
University of Houston
Adjunct Faculty, teaching Senior undergraduate level courses in Data Science, Artificial Intelligence and Computer Networks
University of Houston
University of Houston
Lamar University
DEIMOSBC: a blockchain-based system for crowdsensing after natural disasters
3rd Conference on Blockchain Research & Applications for Innovative Networks and Services (BRAINS), IEEE,pp. 17–20, 2021.
Cross-modal knowledge distillation for vision-to-sensor action recognition
IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP), IEEE, pp. 4448–4452, 2022.
COVID19-CBABM: A City-Based Agent Based Disease Spread Modeling Framework
Society for Epidemiologic Research, Mid-Year Conference, 2025.
DESPINA: Synthesis of High-Fidelity Planetary Horizon Reconstructions Using DEM-Guided Diffusion
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XI-2-2026, 881–890. 2026.
Proteus: A system for combining paths collected using crowdsensing
GeoInformatica, pp. 1–24, 2026.
"Professor Raunak was one of the better professors in the Computer Science department. He seemed knowledgeable about the subject. I was able to reach him with questions outside of class easily and he would respond immediately. He made all class material easily available to us and his notes were easy to understand. I do not have anything bad to say about the instructor. "
— Student, COSC 4368: Fundamentals of Artificial Intelligence
"The instructor was able to convey his ideas and lectures clearly. He was very enthusiastic about the material and made it easy to digest the knowledge he wanted to present. The presentation format is pretty great too. Groups of students come together to present a given research paper to explain to other students what it's about allowing us to understand current standings of the AI field. Overall, I really like this class."
— Student, COSC 4368: Fundamentals of Artificial Intelligence
"+ prof obviously knows about the topics and has most of the techniques taught in real life + pretty good lectures, good at explaining and not just reading slides + exams were pretty straightforward (in terms of the actual questions) + project was fun + textbooks were similar to lecture so textbooks were a good resource - we covered a lot so we were only able to learn about the fundamentals of all the techniques (not necessarily bad)"
— Student, COSC 3337: Data Science I
"hi raunak, thank you for your help this semester, you helped me a lot with this class and i think youre the best TA ive ever had for any class"
— Student, COSC 3337: Data Science I
"Well hopefully we get blessed with your skills next semseter. By far the best TA I have ever had."
— Student, COSC 3337: Data Science I