Data Science

Aditya Deshpande

Tempe, AZ 602-***-**** ********@***.*** LinkedIn Github Google Scholar

EDUCATION

Arizona State University Tempe, AZ

Master of Science in Data Science, Analytics, and Engineering (Computing and Decision Analytics)August 2024 - May 2026 Symbiosis Institute of Technology Pune, India

Bachelor of Technology in Information Technology, Honors in AIML Specialization July 2019 - June 2023 SKILLS

Programming Languages: Python, Julia, GoLang, C/C++, SQL, Java, JavaScript, D3.js, LLMs, Bash, UNIX Frameworks: TensorFlow, PyTorch, Pandas, NumPy, Matplotlib, Scikit-Learn, TensorFlow libraries, Torch libraries, Django, Flask, FastAPI, OpenCV, ArcGIS Pro, Huggingface, CUDA, OpenCL Developer Tools: Anaconda, Git, Docker, VS Code, Visual Studio, PyCharm, Google Colab, Google Cloud Platform, Firebase, PowerBI EXPERIENCE

Arizona State University Tempe, AZ

Graduate Research Assistant February 2025 - Present

● Developing AI models to analyze geospatial data, identifying invasive species patterns and ecological impacts, and significantly improving climate-change predictions.

● Leveraged deep learning to automate species identification from geospatial imagery, enhancing analysis accuracy and efficiency.

Symbiosis Centre for Applied AI Pune, India

Research Assistant March 2024 - June 2024

● Utilized AI-driven pipelines (TensorFlow, PyTorch) for medical image segmentation of Retinopathy of Prematurity (ROP), increasing screening accuracy by 15%.

● Partnered with the University of Exeter, the University of Winnipeg, and ASU on an Academy of Medical Science (UK) grant, streamlining multi-institution data collection efforts.

● Implemented FRNN-based segmentation to identify critical retinal abnormalities, reducing manual diagnosis time by 30%. Symbiosis Centre for Applied AI Pune, India

Research Associate June 2023 - March 2024

● Led a Ministry of Electronics & IT-funded initiative developing ML frameworks (Scikit-Learn, PyTorch) for multimodal data

(EEG, ECG, GSR), improving predictive performance by 20%.

● Built robust data pipelines for real-time video and audio processing using Python, enabling faster iteration and insights from a dataset of 1,000+ hours.

● Developed multimodal deception detection models achieving significant accuracy improvements, resulting in a peer-reviewed publication (DOI).

● Authored a comprehensive review on ML-driven cognitive behavioral analysis, published in a high-impact journal (DOI), and proposed a patent-pending data collection architecture.

● Proposed to develop a comprehensive data collection structure currently under patent submission. Dassault Systèmes, Pune, India

AI Training for Leaders: Seminar Speaker January 2024

● Conducted a AI leadership training, bridging technical and managerial insights effectively. Chiba University, Japan Online

Multimodal Deception Detection: Guest Lecturer September 2023

● Delivered lectures on advanced multimodal deception detection techniques using video and audio data. Symbiosis Centre for Applied AI Pune, India

Undergraduate Research Intern June 2022 - May 2023

● Applied under a government grant with CDAC Delhi and DRDO INMAS Lab.

● Analyzed video and audio modality data.

● Optimized deep learning pipelines using TensorFlow and Python for improved data processing. PROJECTS

Covicare Website for Tracking COVID-19 cases with a live dashboard

● Designed and developed Covicare, a website for tracking COVID-19 cases with a live dashboard, enhancing public health monitoring.

● Utilized Power BI, ReactJs, and Firebase for robust data visualization dashboards and real-time updates.

● Implemented various web pages, including Home, Dashboard, Survey, Patient Dashboard, and Doctor Dashboard.

● Collaborated with a team to significantly improve website performance, resulting in a published research paper (DOI).

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