Jihene Bouhlila

Lead author of a 2024 IEEE ISCAS paper with novel findings in data science. Developed an ML approach for SRAM stability prediction, significantly boosting early assessment accuracy. Conducted extensive analysis using advanced simulations, optimizing ML models for reliability. Built automated SPICE simulations in Python/Bash, and conducted high sigma simulations using Solido for robust circuit design. Collaborated with Intel (Germany, USA) and Siemens (Canada), enhancing cross-functional research expertise.

Academic Excellence: Translated a comprehensive thesis from English to French for a Brown University graduate researcher. High-Quality Delivery: Ensured precision and academic rigor in the translation. Linguistic Expertise: Maintained clarity, tone, and intent, with meticulous attention to detail. Project Management: Managed a complex, time-sensitive project in an international academic context, showcasing adaptability and professionalism.

Conducted research on satellite image processing, advancing remote sensing tech. Optimized satellite algorithms by converting C code to Intel SIMD instructions, boosting efficiency. Improved algorithm speed through loop unrolling, branch prediction, and operation simplification. Validated optimization effectiveness with Read Time Stamp Counter (TSC) to confirm performance gains.

Developed and integrated functionalities for sensors on STM32L4, enabling real-time data acquisition and system monitoring. Applied ML and deep learning to accelerometer data for advanced insights. Built a custom dataset from accelerometer readings across scenarios, creating a strong basis for analysis. Visualized sensor data on a cloud platform, offering a user-friendly dashboard for monitoring and insights.

Researched and developed a module for 4-20mA and 0-10V analog outputs, enabling precise control and compatibility with industrial sensors. This development ensured accurate data transmission and enhanced the system's adaptability for a wide range of applications.

Designed and developed a single-phase dimmer using the STM32 Nucleo-L432KC card, managing both hardware and software aspects. This project ensured effective control and functionality, optimizing the dimmer’s performance for real-time adjustments.

Developed a tool to convert a client’s Bill of Quantities (BoQ) with bundles into a logistics-friendly format, improving workflow efficiency. Used macros and VBA to automate the conversion process, saving time and minimizing manual input.

Electronics and Embedded Systems