Current
Principal R&D Engineer, Halliburton Singapore
Applied AI · Signal Processing · Digital Twins
Prasad Anjangi, Ph.D.
I work on data and communication systems that have to operate in difficult physical environments: underwater, subsea, industrial, and downhole.
Background
Ph.D., Electrical & Computer Engineering, NUS
Interests
Telemetry, sensing, time-series models, edge data systems
About
Engineering intelligence from difficult signals.
I am an engineer and researcher working at the intersection of applied AI, signal processing, communications, and physical systems. My work is motivated by a simple problem: useful data are often hardest to obtain in the environments where they matter most.
My career has moved across academic research, deep-tech R&D, and industrial engineering in Singapore. I have worked on underwater acoustic networks, subsea communication systems, diver localisation, downhole telemetry, digital twins, and real-time signal decoding.
Selected work
Projects and outputs
A few representative projects that show how the research moves between algorithms, field systems, software, and industrial deployment.
AI-augmented telemetry and digital twins
At Halliburton, I work on signal processing, time-series modelling, and physics-based simulation for downhole telemetry systems operating in high-noise drilling environments.
Cooperative receiver for long-range underwater links
A distributed receiver architecture for underwater acoustic communication, where spatially separated devices share received signal observations and combine them to recover transmitted data.
View patentDiver communication and underwater localisation
Designed and implemented communication, localisation, and sensor fusion methods for underwater acoustic systems used in field demonstrations and marine operations.
Networking tools and RFCs
Contributor to unetpy, fjagepy, and the unetsocket module.
Research themes
Applied AI and signal systems for the physical world
My interests are practical and systems-oriented. I like problems where models, sensors, communications, and deployment constraints all have to be considered together.
Time-series and telemetry
Signal decoding, anomaly detection, and measurement-driven modelling for telemetry systems with noise, attenuation, and limited bandwidth.
Digital twins and simulation
Physics-based simulators and synthetic signal generation for algorithm design, validation, and operational decision support.
Underwater and edge networks
Adaptive communication, cooperative reception, localisation, and robust data movement across constrained wireless and acoustic networks.
Experience
Research, engineering, and deployment
My professional path has kept me close to both the mathematical and operational sides of engineering.
Principal R&D Engineer, Halliburton
Signal processing, applied AI, digital twins, and real-time decoding for downhole telemetry systems.
Senior Research Scientist, Subnero
Underwater acoustic networking, adaptive modulation, edge deployment, diver localisation, and subsea communication architectures.
Ph.D., National University of Singapore
Transmission scheduling strategies for underwater acoustic networks with large propagation delays.
Embedded systems and firmware
Wireless stacks, platform abstraction layers, Zigbee applications, and smart energy devices at Atmel and STMicroelectronics.
Publications
Selected papers
A selection of peer-reviewed work in underwater communications, adaptive link tuning, field systems, and telemetry.
Adaptive Modulation and Coding With Feedback Scheduling for an Underwater Acoustic Link
W. Shuangshuang, M. Chitre and P. Anjangi, IEEE Journal of Oceanic Engineering.
AI-Aided Real-Time Data Decoder for Mud Pulse Telemetry: A Case Study
P. Anjangi, R. D. Navarro, R. R. Sobhana, F. C. O. Chagas and B. Pillai, SPE Conference at Oman Petroleum & Energy Show.
Monte Carlo Tree Search and Feedback Adaptation for Underwater Acoustic Link Tuning
W. Shuangshuang, M. Chitre, P. Anjangi, IEEE OCEANS.
Diver Communications and Localisation System Using Underwater Acoustics
P. Anjangi and M. Chitre, IEEE Global OCEANS.
Model-based Data-driven Learning Algorithm for Tuning an Underwater Acoustic Link
P. Anjangi and M. Chitre, Fourth Underwater Communications and Networking Conference.
Propagation Delay Aware Unslotted Schedules with Variable Packet Duration for Underwater Acoustic Networks
P. Anjangi and M. Chitre, IEEE Journal of Oceanic Engineering.
Invited papers on super-TDMA and unslotted transmission schedules
P. Anjangi and M. Chitre, IEEE Third Underwater Communications and Networking Conference.
Design and Implementation of Super-TDMA
Best Experimental Student Paper Award, ACM WUWNet, Washington DC.
Teaching and mentorship
Learning by building real systems
I enjoy teaching and mentoring through projects. My preferred mode is to connect theory to working prototypes, field data, testing, and clear technical communication.
Past teaching and workshop experience includes NUS signals and systems laboratories, underwater networking tutorials, software-defined modem workshops, and industry mentorship.
Topics I like teaching
- Signal processing for real-world data acquisition
- Time-series modelling and adaptive communication
- Embedded and edge data pipelines
- Underwater acoustic networking and localisation
Contact