Mohak Sharma

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About

I am Mohak Dwarkadhish Sharma, a graduate researcher at Arizona State University working at the intersection of stochastic modeling, actuarial risk analysis, and applied machine learning. I currently lead two active research projects: building a high-dimensional spatial vine-copula framework for hydropower revenue risk and parametric insurance pricing with Dr. Petar Jevtic, and developing multi-objective stochastic optimization frameworks for UAV path planning under uncertainty with Dr. Giulia Pedrielli. I am a published author with peer-reviewed work on deepfake detection, AI-driven cybersecurity, and multimodal analysis, and a recipient of a competitive $35,000 full funding award from ASU. Find me on LinkedIn and GitHub.

Mohak Sharma

Graduate Researcher — Stochastic Modeling & Risk Analysis

My research focuses on high-dimensional dependence modeling, actuarial risk quantification, and multi-objective optimization under uncertainty. I am driven by problems that sit at the boundary of rigorous statistical theory and real-world consequences — in energy infrastructure, autonomous systems, and AI.

  • Website: mohaksharma2507.github.io
  • Phone: +1 (623) 221 0363
  • City: Tempe, Arizona
  • Degree: MS in Data Science, Analytics and Engineering
  • Email: mshar118@asu.edu
  • Affiliation: Arizona State University
  • Research Areas: Vine Copula Modeling, Actuarial Risk Analysis, Stochastic Optimization, Monte Carlo Simulation, Parametric Insurance Design, Computer Vision, Multimodal AI

I am currently in the second year of my MS at Arizona State University, where I hold positions as both a Graduate Research Assistant and a Research Assistant on two independently funded research tracks. My work bridges advanced statistical theory with applied problems in energy systems resilience, autonomous vehicle safety, and AI integrity — and has produced three published papers with more research currently in progress.

Publications

Projects

Selected projects spanning computer vision, NLP, autonomous systems, and AI — each grounded in research-driven thinking and practical application.

Eyeball Cursor Control System

Engineered a hands-free gaze-controlled cursor system using Python and OpenCV, achieving 90% real-time tracking accuracy and improving accessibility response time by 30%.

Medical Chatbot (Dr. Chat)

Built a healthcare query chatbot using Flask and Hugging Face models, achieving 85% prediction accuracy with a 20% reduction in API latency for real-time health query resolution.

Animal Identification App

Developed an Android application using Google Vision API for wildlife species classification, achieving 90% accuracy for educational and field identification use cases.

Story Generation Model

Developed a narrative generation model on Google Cloud's Vertex AI, leveraging NLP pipelines for language generation and semantic consistency, achieving 85% structural accuracy.

Crypt-lock

Collaborative project implementing encryption, multi-factor authentication, and anomaly-based fraud detection to secure e-commerce transactions against data breaches.

STASH Robot — Autonomous Obstacle Detection

Mentored a team of three to build an autonomous navigation robot integrating ultrasonic sensors with an Arduino microcontroller, achieving real-time obstacle detection and avoidance in confined spaces.

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Skills

My technical expertise is built through active research and hands-on project work, spanning advanced statistical theory, machine learning, and software development. Every skill listed here is directly backed by published research, funded projects, or deployed applications.

Python 95%
R 85%
Stochastic Modeling & Simulation 90%
Vine Copula Modeling 90%
Monte Carlo Simulation 90%
Multi-Objective Optimization 85%
Power BI 90%
Machine Learning (TensorFlow, PyTorch) 85%
Computer Vision (OpenCV, CNN) 85%
Bayesian Inference & MLE 85%
SQL 80%
MATLAB 80%
pyvinecopulib 85%
Java 75%

Resume

A research-driven academic and professional journey focused on stochastic modeling, risk analysis, and applied machine learning.

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Summary

Mohak Dwarkadhish Sharma

Graduate researcher in stochastic modeling, actuarial risk analysis, and applied machine learning at Arizona State University. Published author, $35,000 GRA funding recipient, and conference presenter.

  • Tempe, Arizona
  • +1 (623) 221 0363
  • mshar118@asu.edu

Education

MS in Data Science, Analytics and Engineering

2024 – 2026

Arizona State University, Tempe, Arizona

Pursuing the Computing and Decision Analytics track with active research in stochastic optimization and financial risk modeling under Dr. Petar Jevtic and Dr. Giulia Pedrielli.

P.G. Diploma in Information Technology (Computer Vision)

2023 – 2024  |  7.55 CGPA

D.G. Ruparel College, Mumbai University, Mumbai

Specialized in Computer Vision; completed two research projects on deepfake detection and AI-driven cybersecurity, resulting in two published papers and a national conference presentation.

BSc in Information Technology

2020 – 2023  |  8.28 CGPA

D.G. Ruparel College, Mumbai University, Mumbai

Built a strong foundation in software development, algorithms, and data systems. Served as Creative Head of the college techfest DOTTECH (January 2023).

Honors & Recognition

Full Funding Award — Graduate Research Assistantship

Aug 2025 – Jan 2026

Arizona State University, Tempe, AZ

Competitively selected for a fully funded GRA under Dr. Giulia Pedrielli, receiving a $22,000 tuition waiver and a $13,000 research stipend (total award: $35,000).

Invited Panelist — International Students and Scholars Center, ASU

2025

Arizona State University, Tempe, AZ

Selected to speak at an ASU student success session, sharing graduate research experiences and academic insights with an international student audience of 100+ attendees.

Conference Presenter — Anveshak 2024

Feb 2024

Allana Institute of Management Sciences, Pune

Presented peer-reviewed research on Deepfake Awareness at a national interdisciplinary research conference, representing D.G. Ruparel College, Mumbai.

Research Experience

Graduate Research Assistant

Aug 2025 – Jan 2026

Arizona State University, Tempe, AZ — Dr. Giulia Pedrielli

  • Formulated a multi-objective stochastic optimization framework to generate Pareto-optimal UAV flight paths that simultaneously minimize collision risk with civilians and obstacles while maximizing mission-level target reachability.
  • Designed probabilistic simulation environments to stress-test UAV operational logic across adversarial and edge-case scenarios, enabling formal safety-performance trade-off analysis across the full Pareto frontier.
  • Implemented scenario generation pipelines grounded in uncertainty quantification to evaluate robustness of candidate control policies under distributional shift.

Research Assistant

Jan 2025 – Present

Arizona State University, Tempe, AZ — Dr. Petar Jevtic

  • Developing a high-dimensional spatial vine-copula framework to jointly model inflow, electricity generation, and market revenue across a portfolio of 356 Southwest U.S. hydropower facilities, capturing asymmetric tail dependencies arising from reservoir buffering dynamics.
  • Quantifying systemic drought exposure through Monte Carlo simulation, demonstrating that independence-based actuarial models substantially underestimate aggregate portfolio tail risk — a finding with direct implications for insurance pricing and capital adequacy.
  • Designing and pricing dual-trigger parametric index insurance contracts using the Wang distortion transform, formally characterizing structural basis risk rooted in inflow-revenue decoupling during moderate drought regimes.
  • Validating the pricing framework through a five-module robustness pipeline covering holdout stability, bootstrap uncertainty quantification, Shapley premium attribution, regime-dependent copula diagnostics, and non-stationarity stress testing.

Industry Experience

Software Developer Intern

Jan 2024 – Jun 2024

Sketo Info Tech, Mumbai, India

  • Built Power BI sales dashboards integrating multi-source pipelines, improving forecasting accuracy by 25% and reducing server downtime by 20% through infrastructure hardening.
  • Redesigned the company website using WordPress, streamlining UI/UX workflows and boosting user engagement by 30%.

Contact

Location:

1265E University Dr, Tempe, AZ 85281

Call:

+1 (623) 221 0363