Lakshay Arora

PhD Candidate | AI/ML Researcher Engineer | Turning Research Into Scalable Solutions

X logo Google Scholar

About Me

I’m a Ph.D. candidate with 5+ years of experience applying AI and machine learning to real-world challenges across finance, healthcare, and engineering. My work spans traditional machine learning, deep learning, reinforcement learning, generative AI, and optimization under uncertainty—translating research into impactful, data-driven solutions. I enjoy building intelligent systems that are both innovative and practical.

Download Resume

Experience

Assistant (Independent Consultant – Part-time)

Deloitte Inc.
Mar 2025 – Present | Toronto, Canada

  • Built Python-based transaction rule filters to support AML compliance for CIBC’s review process.
  • Applied financial heuristics and backend data analysis to identify suspicious activity patterns.
  • Accelerated false-positive triage by 28%, enhancing review speed and detection efficiency.
  • Tools: Python, Excel, AML backend system.

Applied Machine Learning Researcher

Spacecraft Robotics and Control Lab, Carleton University
Sep 2020 – Present | Ottawa, Canada

  • Designed spacecraft guidance policies under uncertainty using Koopman Expectation and nonlinear optimization.
  • Integrated deep learning models (TensorFlow) with Julia-based simulators for trajectory generation.
  • Improved guidance accuracy by 84% and reduced simulation runtime by 50%.
  • Tools: Julia, Python, TensorFlow, MATLAB, Simulink.

AI/ML Research Associate

AI Quest Inc. & George Brown College (Mitacs BSI)
May 2022 – Sep 2022 | Toronto, Canada

  • Developed an NLP-based pharmacovigilance system using Python, XGBoost, and Twitter API.
  • Processed 30GB+ of pharma and social data to detect ADRs with a 15% improvement in prediction accuracy.
  • Delivered dashboards for stakeholders to support real-time healthcare monitoring and drug safety reporting.
  • Tools: Python, Pandas, XGBoost, Streamlit, Tweepy, NLTK.

Machine Learning Researcher

Wichita State University
Sep 2017 – Feb 2020 | Kansas, USA

  • Applied reinforcement learning to the spacecraft orbit-raising problem by designing a reward-adaptive control framework.
  • Formulated dynamic cost reweighting strategies to balance fuel consumption and time-of-flight in long-duration transfers.
  • Improved simulation efficiency and fuel optimization by up to 18% through deep Q-learning in MATLAB.
  • Tools: Python, MATLAB, Simulink.

Projects

Cost of Living Tool

Student Cost-of-Living Calculator

Streamlit app for Canadian students to estimate expenses using Gemini Pro AI.

Live Site
GitHub Repo
Pharmacovigilance Project

Pharmacovigilance via Twitter NLP

Built during Mitacs Internship (Mitacs BSI), this project leveraged Natural Language Processing to extract and analyze adverse drug reactions (ADR) from tweets for pharmacovigilance applications. Processed over 30GB of data to improve ADR prediction accuracy by 15%.

GitHub Repo
Rendezvous Guidance

Deep RL for Spacecraft Rendezvous

Reinforcement learning-based trajectory optimization under uncertainty.

GitHub Repo
Flight Fare Prediction

Flight Fare Prediction using ML

A complete end-to-end project to predict the domestic flight prices in India depending on various features using Random Forest Regressor and XGBoost Regressor which is then deployed as a Flask Web Application on Render.

Live Site
GitHub Repo
Robotic Arm

Adaptive Robotic Arm Control

Adaptive control for 2-DOF robotic arm with uncertain payloads.

GitHub Repo
HR Analytics Project

HR Analytics for Retention

Analyzed HR data using classification models to identify key employee attrition factors and predicted churn risk. Delivered actionable insights to improve retention strategies for organizations.

GitHub Repo

Skills

Programming Languages

  • Python
  • Julia
  • MATLAB
  • R
  • C++
  • SQL

Machine Learning and Artificial Intelligence

  • Generative AI
  • Agentic AI
  • Reinforcement Learning
  • Deep Learning & NLP
  • Bagging & Boosting

Libraries & Tools

  • NumPy, Pandas, Scikit-learn
  • TensorFlow, Keras, PyTorch
  • LangChain, PySpark

Cloud & Platforms

  • GCP
  • VertexAI
  • Google BigQuery
  • IBM Watson Studio
  • Jupyter Notebook

Model Validation

  • Uncertainty Quantification
  • Statistical Testing
  • Probabilistic Modeling

Visualization

  • Tableau
  • Excel, PowerPoint
  • LaTeX

Other Tools

  • Simulink
  • Microsoft Office Suite

Education

Ph.D. in Aerospace Engineering

Carleton University — Ottawa, Canada
2020 – 2025

Focus: Spacecraft Guidance, Path Planning under Uncertainty, AI in Autonomous Space Missions.

MS in Aerospace Engineering

Wichita State University — Kansas, USA
2017 – 2020

Thesis: Reinforcement learning framework for spacecraft low-thrust orbit raising
View Thesis

B.Tech in Aeronautical Engineering

Manipal Institute of Technology — India
2013 – 2017

Certifications

IBM Certificate

IBM Data Science

Specialization on Coursera

View Certificate
IMS Certificate

Business Analytics

By IMS Proschool

View Certificate

Publications

AAS Conference

Koopman Expectation-Based Guidance for Spacecraft Rendezvous and Proximity Operations under Uncertainties

35th AAS Space Flight Mechanics Conference (Accepted)

SciTech

Reinforcement Learning for Sequential Low-Thrust Orbit Raising Problem

AIAA Scitech 2020 Forum

Paper Link
AAS

Objective function weight selection for sequential low-thrust orbit-raising optimization problem

AIAA/AAS Space Flight Mechanics Meeting

Paper Link
Download Resume

Contact

Email: lakshaya32@gmail.com

X logo