BAKI MADHUSUDHANA REDDY

About

M.Tech student in Automotive Engineering with project experience in ADAS perception, EV fault diagnosis, platooning, and structural dynamics. Interested in vehicle simulation, virtual testing, and intelligent mobility solutions.

Experience

• Short term internship Training in Design (Solid Edge)
  APSSDC

  Training in Design (Solid Edge) at APSSDC – Siemens Center.

Education

• 2027
  Masters of Technology in Automotive Engineering

  Amrita Vishwa Vidyapeetham

  Automobile Engineering · 2025 – 2027

  Automobile Engineering · 2025 – 2027
• 2024 GV
  Bachelor of Technology in Mechanical Engineering

  Gayatri Vidya Parishad College of Engineering and Technology

  Mechanical Engineering · 2024

  Mechanical Engineering
• 2020 CC
  Intermediate

  Sri Chaitanya College

  2020
• 2017 PS
  SSC

  St. Paul's High School Srikakulam

  2017

Skills

Tools / apps / platforms

Languages

Projects

• Analysis of Dynamic Behaviour of Steel Structures

  Investigation of structural behaviour and failure mechanisms in steel structures under different boundary conditions using modal analysis, vibration analysis, simulation and experimental methods.

• EV Motor Bearing Fault Diagnosis Using Signal Processing and Machine Learning
  MATLAB, FFT, Support Vector Machine, CWRU dataset

  Development of an intelligent fault diagnosis system for electric vehicle motor bearings using vibration signal analysis and machine learning techniques. Signal processing methods such as envelope analysis, spectral kurtosis and FFT are implemented in MATLAB to extract fault features from vibration signals.

• Adverse Weather Data Augmentation for Robust ADAS Perception Using CycleGAN
  CycleGAN, BDD100K, IDD, ACDC, YOLOv8

  Improving robustness of vision-based ADAS perception systems under adverse weather conditions such as rain, fog and night. CycleGAN is implemented for unpaired image-to-image translation to generate synthetic adverse-weather images using datasets such as BDD100K, IDD and ACDC. The generated images are used to augment the training dataset and YOLOv8 object detection models are trained using both clear and augmented datasets.

• Adaptive Cooperative Platooning Under Communication Degradation
  ROS 2, autonomous mobile robots, digital twin, AI-assisted decision-making

  Developing an adaptive cooperative vehicle platooning system for safe and stable operation under communication degradation, investigating vehicle-to-vehicle coordination, inter-vehicle spacing, platoon stability and adaptive platoon behaviour under varying communication conditions. A simulation-based environment is being developed to evaluate platoon performance, with ROS 2 and autonomous mobile robots explored for laboratory-scale validation. The work also investigates digital twin and AI-assisted decision-making approaches using a hierarchical architecture that separates high-level decision-making from deterministic vehicle control.

Courses & certifications

• Motion in Control – ADAS Conference · SAE International · 2026
• CAD Modeling and Engineering Design Training
• Internship Training in Design (Solid Edge) · APSSDC Siemens Center

⚽ Extracurricular activities

• Technical Conferences Participation

  Actively participated in technical conferences related to ADAS and vehicle dynamics.

• IMTEX FORMING 2026 Attendee

  Attended IMTEX FORMING 2026 – International Forming Technology Exhibition in Bengaluru, exploring metal forming, tooling, and manufacturing technologies.

🎯 Hobbies & interests

• Art
• Gym