SA
SRIRAM ANBALAGAN
Sastra Deemed University, SRM TRP Engineering College, Anna University, Chennai, Arasu Engineering College
About
Sriram Anbalagan received the Ph.D. degree in Image Processing from Anna University, Chennai, India, in 2024, and is currently pursuing the Post Doc Fellowship (PDF) Under Visvesvaraya PhD Scheme for Electronics and IT: Phase II (Sponsored by MeitY, Government of India) at SASTRA Deemed University, Thanjavur, India. His research interests include low-power ASIC design, near-sensor computing architectures, and hardware algorithm co-design for wearable biomedical systems.
Employment
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Sastra Deemed University Post-Doctoral Research Fellow (MeitY Visvesvaraya PDF Scheme)2025 - Present
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SRM TRP Engineering College Associate Professor2015 - 2025
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Arasu Engineering College Assistant Professor2015 - 2022
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Spaira Tech. Private Limited Website Programmer2011 - 2012
Education
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Anna University, Chennai PhD2017 - 2022
Projects & Funding
Projects & funding information is unavailable.
Publications (25)
- Self-Verifed FIR Filter ASIC with Vedic Arithmetic and Han-Carlson Accumulation at 90-nm Save
- REAL-TIME SOIL CONTAMINANT MONITORING USING MICROBIAL BIOSENSORS AND SUPPORT VECTOR MACHINE Save
- Dedicated Astronomical Computation Unit for Luni-Solar Calendrical Systems in 90nm CMOS Save
- Ultra Low Power Safety Aware Elevator Controller ASIC with Near-Zero-Skew Clocking Save
- A Hardware Efficient Near Sensor Computing Architecture for Gait Analysis: Utilizing Alpha Max Approximation and Wallace Tree Synthesis Save
- AI-enhanced operation and control of isolated AC micro-grids with renewable energy and energy storage systems Save
- Reliability verification of a dual-car elevator ASIC in SCL 180-nm CMOS: NBTI aging, multi-corner timing, and ISO 26262 ASIL-B collision avoidance Save
- Design and Implementation of PVT-based Built-In Self-Repair for TSV Delay Faults Save
- IoT-based vulnerability assessment for sustainable computing Save
- Optimized IoT protocol stack for seamless smart home communication using Random Forest-based interoperability analysis Save