Md Farhan Tasnim Oshim

Md Farhan Tasnim Oshim

PhD Candidate in Computer Science at CICS, UMass Amherst

I am Md Farhan Tasnim Oshim, a PhD candidate in Computer Science at UMass Amherst, specializing in HCI through radar sensing, applied machine learning, and autonomous systems. With extensive experience in contactless sensing, signal processing, and AI-driven perception, I focus on leveraging advanced radar techniques to enable impactful applications in healthcare and human-object interaction.

Beyond academia, I have held research roles at industry leaders like Tesla, Qualcomm, and Bosch, where I developed real-time solutions for radar-based gesture recognition, sensor fusion, and passive entry systems. Whether designing complex radar algorithms or implementing neural networks for critical perception tasks, my goal is to drive research forward, bridging real-world challenges and advanced technology.

My other passions include photography, hiking, and spending time with my toddler. Feel free to explore my publications and reach out if you’d like to connect or discuss collaborative projects!

I’m on the job market - seeking Research Scientist or Engineer positions, focusing on contactless sensing, AI-driven perception, radar signal processing and imaging, and machine learning for healthcare, human–computer, or human–robot interaction. I am based in the US, willing to relocate anywhere in the US, and have unlimited work authorization.

News

  • I will be teaching CICS 256: Make - An Introduction to Physical Computing at UMass Amherst this Fall (2025)! This will be my fourth time teaching the course, and I’m looking forward to guiding students through hands-on learning at the intersection of hardware, coding, and creativity.
  • Our paper “Anti-Sensing: Defense against Unauthorized Radar-based Human Vital Sign Sensing with Physically Realizable Wearable Oscillators” got accepted in 2025 IEEE Conference on Robotics and Automation, ICRA 2025.
  • Delighted to share that I was awarded the 2025 Dr. Dave Lomet Graduate Scholarship for Systems Research at UMass Amherst.
  • Our paper “NeRF-enabled Analysis-Through-Synthesis for ISAR Imaging of Small Everyday Objects with Sparse and Noisy UWB Radar Data” got accepted in the International Conference on Intelligent Robots and Systems, IEEE IROS 2024.