Name: Suvendu Mohanty
Job Role: Mechanical Engineer
Experience: 5+ Years
Address: Dubai, UAE
Skills
Reliability & Maintenance 95%PhD Mechanical Engineer specialising in Prognostics & Health Management, condition monitoring and industrial AI. 5+ years building diagnostics and Remaining Useful Life models for real industrial assets.
0 + Projects completed
PhD Mechanical/Production Engineer and Postdoctoral Researcher at IIT Madras with 5+ years of experience in predictive maintenance, Prognostics and Health Management (PHM), mechanical diagnostics, condition monitoring, tribology, and reliability engineering. Expertise in wear-debris and oil analysis, vibration monitoring, RGB image processing, computer vision, multi-sensor data fusion, machine learning, deep learning, and Remaining Useful Life (RUL) estimation, supported by a validated prognostics engine with 92% accuracy. Experienced in translating mechanical-system degradation data into predictive models, health-monitoring frameworks, and maintenance decision-support solutions, achieving an 18% reduction in spare-parts costs for industrial equipment.
ThesisFailure Prediction of Engine Driven by CNG Through Prognostic Approach.
ThesisAnalysis of Exhaust Emission of Internal Combustion Engine Using Biodiesel Blend.
ThesisTheoretical Investigation of Turbulent Fluid Flow & Heat Transfer in a Mixing Junction.
Peer-reviewed research on wear analysis, prognostics and predictive maintenance — click any card to open the full paper.
Industry–academia work carried out at IIT Madras with aerospace, industrial-automation and retail-operations partners — translating condition-monitoring data into diagnostics, prognostics and maintenance decision support.
Beyond the laboratory — a decade of teaching physics, chemistry and mathematics free of cost to tribal and rural students in Tripura and Odisha, so that a postcode never decides who gets to become an engineer.
What began as evening tuition for a handful of neighbourhood children grew into SM Classes and later SUVTEC Science Academy — classrooms in Agartala and in remote hill villages where students from the Debbarma, Reang and Rava communities prepare for CBSE boards, JEE, NEET and beyond, without paying a rupee in fees.
Alongside teaching, I run book, stationery and study-material drives with the Anex Charitable Trust, reaching residential hostels such as Maa Dhanswari B/G Hostel at Chanmari Khumulwng. Every batch is mentored personally — from the first algebra class to the college admission letter.
The payment arrives differently: a hand-drawn whiteboard on Teachers’ Day, a hand-woven risa, and a first-generation graduate walking into an engineering college.
I build models that predict when machines will fail.
These classrooms make sure no student does.