Academic Activities
Talks, paper presentations, conferences, and teaching activities.
🏆 Competitions & Challenges
Competition participations and organised challenges.
- Participated as a two-member team in the Multi-modal Aerial View Imagery Classification (MAVOC) Challenge.
- Developed a multi-modal deep learning framework learning domain-invariant features from Electro-Optical (EO) and SAR data.
- 🥇 Track 1 — 5th / 82 teams Track 2 — 9th / 77 teams
- Methodology published in "Multi-modal aerial view object classification challenge results – PBVS 2022." CVPR Workshops, 2022.
- Organised India's first drone-based object detection competition using RGB and IR imagery on the Indraeye dataset.
- Hosted at the International Conference on Emerging Technology in Autonomous Aerial Vehicles (ETAAV), IISc Bangalore.
- Sponsored by SwaYaan (MeitY, Government of India).
🎓 Paper Presentations
Also available on the AIRL YouTube Page.
- 16 Oct 2024
IROS 2024 Abu Dhabi, UAE
"SSL-RGB2IR: Semi-supervised RGB-to-IR Image-to-Image Translation for Enhancing Vision Task Training in Semantic Segmentation and Object Detection."
Oral & Poster Presentation
- 26 Jun 2024
CyPhyss 2024 IISc, India
"MRFP: Learning Generalizable Semantic Segmentation from Sim-2-Real with Multi-Resolution Feature Perturbation."
Oral Presentation
- 15 May 2024
ICRA 2024 Yokohama, Japan
"SKD-Net: Spectral-based Knowledge Distillation in Low-Light Thermal Imagery for Robotic Perception."
Oral Presentation
🎤 Talks & Tutorials
- 30 Jan 2026
IIT Bombay Maharashtra, India
"Development of Robust Perception Systems for Real-World Applications."
Machine Learning for Remote Sensing II
- 20 Aug 2025
ETAAV 2025 IISc Bangalore, India
"AI-Driven Perception for UAVs under Adverse Weather."
- 21 Aug 2025
Atria Institute of Technology Bangalore, India
"AI-Driven Personalized Learning: Transforming Education with Generative Models."
Faculty Development Program – Exploring Generative AI
- 12 Feb 2025
Dept. of Aerospace Engg., IISc Bangalore, India
"Advancing Drone Perception: Multi-Spectral Learning for Segmentation and Detection."
Faculty Development Program – AI-Driven Autonomous Drone
- 29 Jan 2025
Lossfunk Residency Bangalore, India
"Domain Generalization for Autonomous Navigation."
Invited Talk (formerly Turing's Dream)
- 26 Jun 2024
PES University Karnataka, India
"Target Recognition in Aerial Imagery: Current Trends and Challenges."
Faculty Development Program – Drone Perception
- 22 Feb 2024
Dept. of Aerospace Engg., IISc Bangalore, India
"Deep Learning for Autonomous Navigation."
Industrial Workshop for Ashok Leyland – Autonomous Navigation
- 09 Jan 2024
Dept. of Aerospace Engg., IISc Bangalore, India
"Deep Learning for Drone Applications."
Faculty Development Program – Drone Applications
- 16 Sep 2023
Dept. of Aerospace Engg., IISc Bangalore, India
"AI Perception for Aerial Robotics."
Faculty Development Program – UAV Technology and Applications
đź“š Teaching Activities
Courses where I served as Co-Principal Investigator or Teaching Assistant.
Master's Courses — Inria / 3IA UCA
Deep Learning for Computer Vision
Instructor Winter 2026–27 · Université Côte d'Azur Course Website ↗
Graduate-level course at Université Côte d'Azur, delivered by the Inria STARS team in partnership with 3IA Côte d'Azur. Held every Friday, 1:30–4:30 PM, beginning October 9, 2026. Co-taught with Prof. François Brémond, Diana Laura Borza, Aglind Reka, Mahmoud Ali, and Seongro Yoon.
- Introduction to PyTorch — tensors, autograd, building and training neural networks from scratch.
- Semantic Segmentation — pixel-level scene understanding, encoder-decoder architectures, and evaluation on real-world benchmarks.
- Target Tracking — single and multi-object tracking, motion models, and appearance-based methods.
My Modules
Lecture Videos
NPTEL Courses
AI-Driven Perception, Learning and Mapping for Drones
Co-Principal Investigator NPTEL ↗  · YouTube ↗
- Co-developed and delivered this NPTEL course on AI-driven perception and mapping for autonomous drones.
- Covered multi-spectral perception, domain adaptation, semantic segmentation, object detection, and SLAM for UAVs.
- Managed content preparation, assignments, and learner engagement.
Advanced Perception for Autonomous Systems
Co-Principal Investigator Upcoming · NPTEL
This course provides an in-depth exploration of modern perception techniques for autonomous systems, with a focus on the latest advances in foundation models and efficient adaptation strategies for real-world deployment.
- Large-scale foundation models for vision — architectures, pre-training paradigms, and zero-shot capabilities.
- Parameter-Efficient Fine-Tuning (PEFT) — LoRA, adapters, prompt tuning, and their application to perception tasks.
- Video understanding — temporal modelling, action recognition, multi-object tracking, and anomaly detection in video streams.
- Vision-Language Actions (VLAs) — grounding language in visual perception for robotic planning and autonomous decision-making.
Topics at a Glance
Graduate Courses
- TA for the graduate-level course on Neural Computation.
- Conducted tutorials on deep learning, backpropagation, optimization, and neural architectures.
- Assisted with assignments, project mentoring, and evaluation.