Dr. Shad Ahammed

• Design and implementation of core anomaly detection algorithms using AI for industrial preventive maintenance • Develop methods for real-time processing and fusion of heterogeneous sensor data • Apply Explainable AI to improve maintenance protocol providing confidence score and better trust • Contribute to the development of RAG-LLM based chat box as a maintenance recommendation system

• Designed and deployed computer vision MVPs for dynamic and static obstacle detection in safety-critical automotive systems • Integrated AI models into CI/CD pipelines to ensure rapid iteration, testing, and scalable deployment • Applied STPA to evaluate AI failure modes and enhance system safety compliance • Managed project planning, coordination, and supervision of junior researchers in the development of safety-critical perception systems

• Development of AI-based decision-support MVPs for emergency health complication prediction • Advanced data analysis using time-series signals from sensors and medical equipments • Designed and integrated large language models for generating health assistance reports • Applied Explainable AI to increase user trust, enabling adoption in high-stakes medical environments • Optimized models for embedded deployment (ARM, FPGA, microcontrollers) to enable real-time predictions

• Acceptance Test Specifications for state-of-the-art integrated modular avionics equipments following /DO-254/, /DO-297/, AIRBUS standard • Developed general purpose automatic test equipment to perform Production acceptance tests for aerospace equipments • Define system requirements to test wired (Discrete/Analog/PWM) and BUS communication (CAN/A429/A664/A717) interfaces • Requirement engineering using DOORS document management

• Reduced 75% of test run time by developing unique MATLAB based automated system for processing scattered protein droplet image • Successfully implemented image processing technique to deduce complex refractive index measurement

• Designed Python based machine learning model for detecting epileptic seizure with accuracy over 98% • Developed hardware prototype with FPGA(Altera) using VHDL without time slack • Designed test bench for verification of the software and debug with ModelSim

• Worked with IMU(MPU9150) sensor to obtain data from wireless netwrok • Designed sensor based electronic system with Raspberry Pi using OCTAVE/MATLAB

 Led several projects with efficiency-based planning from production till delivery  3 times customer credibility award in 1.5 years for maintaining project timeline  Increased production efficiency by 25-30% in 1 year by using smart planning tools e.g. SAP, ETS, FAST React

Artificial Intelligence in Healthcare and Automotive

1. Quantitative Business Analysis 2. Supply Chain

1. Electrical Circuit 1 and 2 2. Electronic 3. Electronic circuit simulation 3. Engineering Electromagnetics 4. Electrical Machine