AKSHAY KULKARNI
  • Home
  • Research Experience
  • Projects
    • Post-hoc Gen-CBM (CVPR25)
    • IG-Defense (ECCV24)
    • Mixup-SFDA (ICML22)
    • SFDA-Seg (ICCV21)
    • Sticker-SFDA (ECCV22)
    • SPA-UniDA (NeurIPS22)
    • AST-OCDASeg (AAAI22)
    • Autonomous Driving Platform
    • Semantic Segmentation using PyTorch Lightning
    • Human Activity Recognition using IMU
    • Real-Time Stair Detection
    • Mini-Projects >
      • ESP32 & IMU interfacing with ROS
      • Implementation of DL Models
      • Hand Written Symbol Recognition
      • Wizards' Chess
      • Snake Gaits Implementation
      • Maze Solver
      • Sudoku Solver
    • Simulations >
      • Offboard Control of Pixhawk
      • Turtlesim Experiments
      • 3DOF Robotic Arm
  • Notes

Research Experience

  • Sony R&D Center, Tokyo - June 2023 - Sept. 2023: I worked as a research intern with Takeshi Ohashi and Sho Inayoshi on labeled dataset generation with generative AI models (vague description due to NDA).
  • Video Analytics Lab (VAL), Indian Institute of Science (IISc) - June 2020 - Aug. 2022: I worked as a Project Assistant under the supervision of Prof. R. Venkatesh Babu.
    • Research projects: I worked with Prof. Babu's Ph.D. students Jogendra Nath Kundu  and Sunandini Sanyal on empirical and theoretical contributions to the topic of Domain Adaptation for Semantic Segmentation and Object Recognition. I was also fortunate to collaborate with and receive guidance from Dr. Varun Jampani, Research Scientist at Google Research.
    • Industry projects: I worked on Airport Ground Management Video Analytics under the ANRC research initiative by Boeing, Wipro, HCL, and IISc. Primarily, I worked on object detection and airport vehicle classification in airport scenes.
  • AIRLab, Politecnico di Milano - June 2019 - July 2019 : I worked as a research intern under the supervision of Prof. Andrea Bonarini at the AI & Robotics Lab at PoliMi. My work involved analysis of signals from an accelerometer attached to a person to classify their activity. I implemented the sensor system able to send the signal to a remote computer. Further, I worked on the classification of the signal using many different traditional Machine Learning and Deep Learning techniques, implementing the corresponding system and analyzing data. [Hardware] [Software]
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  • Home
  • Research Experience
  • Projects
    • Post-hoc Gen-CBM (CVPR25)
    • IG-Defense (ECCV24)
    • Mixup-SFDA (ICML22)
    • SFDA-Seg (ICCV21)
    • Sticker-SFDA (ECCV22)
    • SPA-UniDA (NeurIPS22)
    • AST-OCDASeg (AAAI22)
    • Autonomous Driving Platform
    • Semantic Segmentation using PyTorch Lightning
    • Human Activity Recognition using IMU
    • Real-Time Stair Detection
    • Mini-Projects >
      • ESP32 & IMU interfacing with ROS
      • Implementation of DL Models
      • Hand Written Symbol Recognition
      • Wizards' Chess
      • Snake Gaits Implementation
      • Maze Solver
      • Sudoku Solver
    • Simulations >
      • Offboard Control of Pixhawk
      • Turtlesim Experiments
      • 3DOF Robotic Arm
  • Notes