Welcome to my GitHub profile! I'm a passionate AI enthusiast and a Master's student in Computer Science at Arizona State University. My goal is to revolutionize healthcare and solve real-world problems using the power of Artificial Intelligence. 🚀
- 🏛️ Master of Computer Science (Thesis) Specializing in Artificial Intelligence, Arizona State University, Aug 2023 - May 2025
- 🎉 Proud recipient of the ASU Engineering Graduate Fellowship 2023
- 🔬 Member of the cutting-edge JLiang lab at ASU
- 🎓 Thesis guided by the brilliant Prof. Jianming Liang
- 🎓 Bachelor of Technology in Computer Science Specialized in Big Data Analytics, SRM University, July 2019 - June 2023
- 🏅 Served as a board member at SRM E-Cell and SRM student government
- 📚 Thesis guided by the esteemed Dr. Pradyut Kumar Sanki
- 🌟 Proud recipient of SRM's Merit Scholarship (2019-23)
- 💻 Programming Languages: Python, Matlab, Java, C/C++
- 🧠 AI Domains: Deep Learning, Computer Vision, NLP, Machine Learning
- 🚀 Tools: PyTorch, TensorFlow, Sklearn, Keras, TensorRT, Timm, Transformers, Git/VCS, Docker, Kubernetes, VMWare, AWS, GCP
- 🔍 Machine Learning Researcher, Dept of ECE, SRM University, AP, India, July 2022 – July 2023
- 🩸 Developed a Ridge-regression-based ML framework for non-invasive blood glucose detection
- 📈 Surpassed existing benchmarks in accuracy by optimizing RMSE, MAD, and MARD metrics
- 🏥 Ark-II: Integrative Learning from Open-Source Heterogeneous Datasets, Spring 2024
- 🔒 Implemented Ark: Open-Source privacy-preserving Foundational Framework with InternImage as Backbone
- 🩺 Achieved breakthrough results in detecting and classifying 14 diseases
- 🩻 Self-Supervised Adaptive Large Scale Chest X-ray Disease Prediction, Fall 2023
- 🎨 Pretrained DINOv2, a self-supervised, no-label model, on diverse Chest X-ray datasets
- 🏆 Achieved groundbreaking accuracy, surpassing numerous state-of-the-art self-supervised baselines
- 📝 P N S B S V PRASAD V, Ali Hussain Syed, M. Himansh, Biswabandhu Jana, Pranab Mandal, and Pradyut Kumar Sanki, "Augmenting Authenticity for Non-Invasive In Vivo Detection of Random Blood Glucose with Photoacoustic Spectroscopy using Kernel-based Ridge Regression," Accepted by Scientific Reports, Nature Journal.
- 📝 M. Jha, A. Tiwari, M. Himansh and V. M. Manikandan, "Face Recognition: Recent Advancements, and Research Challenges," 2022 13th International Conference on Computing Communication, and Networking Technologies (ICCCNT), Kharagpur, India, 2022, pp. 1-6.
- 🥇 Received gold medal for a paper titled "Learning Styles Based Students Classification Using Neurolinguistics and Natural Language Processing," presented on Research Day (6th edition) at SRM University, AP.
- 🌐 LinkedIn: linkedin.com/in/himudigonda
- 📧 Email: himudigonda@asu.edu
- 🐙 GitHub: github.com/himudigonda
Feel free to explore my projects and publications, and let's collaborate on exciting research opportunities that leverage AI for social good. Together, we can make a positive impact on the world! 🌍✨