Aashish Dhawan

+1-352-***-**** # ad0d6q@r.postjobfree.com ï linkedin.com/in/aashish-dhawan/ § github.com/dhawan98 EDUCATION

University of Florida May 2023

Master of Science in Computer Science

• Courses: Deep Learning for Computer Graphics, Computer Graphics, Mathematics for Intelligent Systems, Natural Language Processing

Kurukshetra University Jun 2019

Bachelor of Technology in Computer Science and Engineering EXPERIENCE

University of Florida Aug 2023 - Present

Adjunct Lecturer

• Teaching Programming Languages and introduction to machine learning courses to undergraduate classes with 100 and 50 students respectively.

University of Florida Jan 2021 - May 2023

Graduate Research Assistant

• Built a PROGAN to artificially generate highly impbalanced multi spectral medical images.

• Wrote a review on Neural Networks used in quantum mechanics and Physics informed neural networks

• Assisted in teaching Courses including Programming Languages, Operating Systems and Digital Computing

• Took office hours, live discussions, doubt sessions and a few lectures for classes of over 600+ students at time. UBTECH AI Lab, University of Sydney Dec 2019 – Apr 2020 Visiting Researcher: Advisor - Dr. Dacheng Tao

• Developed a Domain Adaptation technique for deep learning and computer vision

• Worked on moment matching for Multi-source domain adaptation for various data sources. Space Applications Center, Indian Space Research Organization Jun 2018 – Aug 2018 Research Intern

• Developed a Post Processing technique for Image Segmentation using Graphical Models.

• Used predictive analysis to get better accuracy on segmentation tasks.

• Increased the segmentation accuracy from existing 92 to 98 percent PROJECTS

Post Processing of image segmentation using Conditional Random Fields (CRF) Python, Cuda, Tensorflow

• Implemented the CRF post processing technique on a neural network to achieve higher accuracy

• Achieved 97% accuracy in segmentation tasks on satellite images Multispectral image generation using PROGANs Python, Tensorflow

• Used the base PROGAN built to generate 1024*1024 images and translated it to generate images with up to 7 bands.

• Used medical and aerospace data to test the model. Multi-Source Domain Adaptation Python, Pytorch

• Implemented Moment matching multi-source domain adaptation

• Worked with 5 different data sets simultaneously to adapt a single machine learning model to the different data sets Evaluating ChatGPTs Code Generation Abilities Python, javascript, LLMs, NLP

• Developed a project to test ChatGPTs code generation abilities on various difficulties of coding problems .

• Led a team of 5 people .

Peer-to-Peer File Sharing Network Java

• Implemented a peer-to-peer file sharing application across multiple clients using Java.

• Addressed the fairness problem by implementing choke and unchoke mechanisms, similar to BitTorrent. SKILLS

Languages:Python, Java, C++, JavaScript, C#, SQL

Web Technologies: HTML5, CSS3, JQuery, Angular, Android Studio Databases:MySQL, SQLite3

Frameworks and Platforms: TensorFlow, Pytorch, Pandas, kotlin, AWS, Git, SAS, Docker, Excel Publications

• “Post processing of Image Segmentation using Conditional Random Fields”, – 13th INDIACOM 2019; 6th International Conference on Computing for Sustainable Global Development, 13th -15th March 2019