Manisha Dhiman

Results-driven Technical Architect with 8+ years of experience in ADAS radar perception and automotive safety systems, specializing in object detection, classification, tracking, and ghost object mitigation for short- and long-range radar sensors. Proven track record of improving algorithm accuracy and reducing false positives by up to 80% while delivering production-ready solutions for global OEMs including Toyota, Daimler, Volkswagen, and Hyundai. Expert in C/C++, MATLAB, Python, and radar signal processing, with strong experience driving architecture design, cross-functional collaboration, and successful client demonstrations across complex ADAS programs.

Technical Architect (ADAS) - AUMOVIO (Continental) - Bangalore

(2018-11)

• Built radar perception algorithms for object detection, classification, and tracking across ADAS programs, improving object stability and enabling scalable deployment for multiple global OEM platforms.
• Reduced BSD false positives by over 80% by developing a static mass detection concept for SRR630 radar, strengthening detection accuracy during production validation cycles.
• Improved ghost object classification performance by contributing to TSS4 perception enhancements, enabling successful client demonstrations and higher environment model reliability.
• Resolved critical object dimension inconsistencies during Daimler BSIS demonstrations by implementing algorithmic corrections, ensuring stable object representation under real-world driving scenarios.
• Strengthened object tracking robustness by leveraging road-feature-based modeling in the SIAC project, minimizing ghost detections and improving perception confidence in complex environments.
• Designed association and mirror-object handling algorithms for ARS6XX radar sensors, enhancing multi-object tracking accuracy across moving and stationary traffic conditions.
• Accelerated signal validation and feature testing cycles through radar signal simulations, supporting long-range (ARS) and short-range (SRR) sensor releases for OEM programs including Volkswagen and Toyota.

Project Assistant–III - CSIR–CSIO - Chandigarh

(2018-09 - 2018-11)

• Designed multimodal adaptive biofeedback control systems for stroke rehabilitation using signal processing techniques, improving patient interaction accuracy in therapy simulations.
• Developed virtual reality–based rehabilitation applications for stroke and spinal injury patients, enabling immersive therapy support through real-time system response.
• Implemented prototype solutions using C, MATLAB, LabVIEW, and Python, accelerating research validation and functional testing of rehabilitation models.

Project Supervisor - Sarav Shiksha Education Society (CDAC) - Una

(2016-08 - 2017-12)

• Supervised execution of multiple C and C++ application development projects, ensuring timely delivery and adherence to programming standards.
• Developed embedded software modules in C for microcontroller-based applications, supporting practical implementation of academic engineering projects.
• Guided and monitored programming teams through project lifecycle activities, improving solution quality and successful completion rates.

M.TECH - Electronics & Communication Engineering - Deenbandhu Chhotu Ram University of Science & Technology (2014-06 - 2016-05)

B.TECH - Electronics & Communication Engineering - Beant College of Engineering & Technology (2009-06 - 2013-05)