@himudigonda

👋 Hi! I'm Himansh Mudigonda

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. 🚀

🎓 Education

🏛️ 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)

🛠️ Skills

• 💻 Programming Languages: Python (Proficient), Matlab, Java, C/C++
• 🧠 AI Domains: Deep Learning, Computer Vision, NLP, Machine Learning, LLMs, GenAI
• 🚀 Tools: PyTorch, TensorFlow, Sklearn, Keras, TensorRT, Timm, Transformers, Git/VCS, Docker, Kubernetes, VMWare, AWS, GCP
• 🛠️ Other Skills: Research & Experimentation, Rapid Prototype Development, Problem Solving

💼 Work Experience

🔍 Machine Learning Researcher: SRM University, AP, India, July 2022 – July 2023

• 🩸 Developed a polynomial kernel-based ridge regression model for non-invasive in vivo detection of random blood glucose using photoacoustic spectroscopy (PAS)
• 📈 Achieved an RMSE of 10.94 mg/dl, MAD of 10.13 mg/dl, and MARD of 8.86%
• 🔍 Implemented robust feature extraction methods, including the Mutual Information Gain algorithm, and integrated BMI as a significant feature
• 🧩 Contributed to the development of a portable IoT-based PAS device using a pulsed laser source and piezoelectric transducer, transmitting data securely to the ThingSpeak Cloud platform via MQTT protocol
• 📊 Conducted comprehensive validation using Clarke Error Grid Analysis and Bland-Altman Plot
• 🛠️ Implemented realtime data acquisition and processing pipeline on a Raspberry Pi 4
• 📜 Publication: Scientific Reports, Nature Portfolio

🧠 Cognitive AI Researcher: NeXTech Lab, AP, India, March 2021 - November 2022

• 🧩 Designed and implemented deep learning models processing EEG and 9-axis motion data from a 14-Channel Emotiv EPOC X, achieving a 92.7% accuracy in classifying students based on cognitive learning styles
• 🚀 Developed a transformer-based architecture that improved peer performance in exams, quizzes, and assignments by 17%
• 🧑‍🏫 Collaborated with cross-functional teams of neuroscientists, psychologists, and English experts
• 🔍 Conducted a comprehensive evaluation of 9 machine learning algorithms, with Random Forest achieving the highest accuracy
• 📜 Publication: Learning Styles Based Students Classification Using Neurolinguistics and Natural Language Processing

Projects

📸 Realtime End-to-End Object Detection and Segmentation using Live Drone Feed From DJI Mini SE 2, Spring 2024

• 🛰️ Developed and deployed an object detection pipeline utilizing realtime camera feed for live drone applications
• 🏆 Achieved seamless integration with DJI Mini SE 2 drone
• 🎨 Delivered a lightweight distilled AI framework capable of processing 22 frames per second, achieving an mAP of 59.32 on the COCO dataset

🩻 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 93.11±0.23% and 95.32±0.06% accuracy on classification tasks
• 🧩 Conducted thorough ablation studies and utilized advanced data augmentation techniques such as CutMix and MixUp

📜 Publications

[1] 📝 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," Scientific Reports, Nature Journal.

[2] 📝 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.

🏅 Awards

• 🥇 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.

🔗 Let's Connect!

• 🌐 Website: himudigonda.github.io
• 🫱🏽‍🫲🏻 LinkedIn: linkedin.com/in/himudigonda
• 📧 Email: himudigonda@gmail.com
• 🐙 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! 🌍✨