Meghana Bhange

AI Engineer | Grad Student

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About Me

I am a machine learning engineer and a graduate student dedicated to tackling challenges using data. I'm pursuing my Master's Degree in Information Technology Engineering, with research focusing on privacy-preserving technologies at the Trustworthy Information Systems Lab, ÉTS Montréal. My research focuses on developing a private and anonymous system for handling collective complaints. The aim is to allow group complaints to be filed without revealing the complainant's identity while still providing authorities proof of the complaints' integrity, validity, and legitimacy. I conduct this research under the supervision of Prof. Ulrich Aïvodji and Prof. Jean-Marc Robert.

Additionally, I am a Master's Researcher at Mila - Quebec AI Institute, also under the supervision of Prof. Ulrich Aïvodji. In parallel with my academic pursuits, I work as a Machine Learning Freelancer at Toptal, specializing in Natural Language Processing projects. I enjoy working on creative projects and continually seek new opportunities to apply my skills.

Resume

Education

May 2023 - April 2025

Master's in Information Technology Engineering

École de Technologie Supérieure, Montréal, Canada

Aug 2016 - Jul 2020

B.Tech. in Electronics and Telecommunication

Cummins College of Engineering for Women, Pune, India

Publications

🔗 Survey on AI Ethics: A Socio-technical Perspective

The past decade has observed a great advancement in AI with deep learning-based models being deployed in diverse scenarios including safety-critical applications. As these AI systems become deeply embedded in our societal infrastructure, the repercussions of their decisions and actions have significant consequences, making the ethical implications of AI deployment highly relevant and important. The ethical concerns associated with AI are multifaceted, including challenging issues of fairness, privacy and data protection, responsibility and accountability, safety and robustness, transparency and explainability, and environmental impact. These principles together form the foundations of ethical AI considerations that concern every stakeholder in the AI system lifecycle. In light of the present ethical and future x-risk concerns, governments have shown increasing interest in establishing guidelines for the ethical deployment of AI. This work unifies the current and future ethical concerns of deploying AI into society. While we acknowledge and appreciate the technical surveys for each of the ethical principles concerned, in this paper, we aim to provide a comprehensive overview that not only addresses each principle from a technical point of view but also discusses them from a social perspective.

Selected Talks/Hackathons

Kaggle AI Report 2023: Awarded Top Essay in AI ethics topic for the essay "Exploring the landscape of AI Ethics".

UN PET Lab’s Hackathon 2022: Awarded Best All Female Team for the hackathon on Privacy Enhancing Technologies using differential privacy techniques.

Toptal Hackathon 2022: Awarded Second Prize. Used Stable Diffusion for creating AI-assisted Cards Against Humanity Game.

PyData Meetup Bangalore 2019: Talk on Extracting Names from multi-lingual conversation.

Skills

Natural Language Processing (NLP)

Machine Learning

Python

Data Processing Pipelines

Experience

Jan 2023 - Present

Toptal - Remote

Freelance Machine Learning Engineer

Freelance NLP Specialist at UInclude. Inc (2023 - Present): Developed and deployed a biased word matching model and synonym enricher using SpaCy, GPT-3, and FastAPI on AWS. Achieved effective bias reduction in job listings and efficient data handling with DynamoDB. Key technologies: AWS, Python, FastAPI, Sentence-Transformer.

Freelance ML Engineer for Denaro Capital Partners L.P. (2024 - Present): Developed automated trading platform using Technical Indicators and Optimisation Algorithms. Key technologies: Interactive Brokers API, Backtrader, DigitalOcean

Sept 2021 - Oct 2022

Hunters Security - Remote

Machine Learning Engineer

Researched and built analytical tools for evaluating threat-hunting detectors, creating data processing pipelines and ETLs for analysis. Key technologies: Snowflake, AWS RDS.

July 2020 - Sept 2021

Verloop.io - Bangalore, India

Machine Learning Engineer

Improved intent recognition service accuracy and designed a multi-lingual name recognition service. Refactored model routing and deployment processes, reducing deployment time significantly.

May 2019 - Aug 2019

Verloop.io - Bangalore, India

Machine Learning Intern

Created a person-name extractor customized for multilingual chatbot conversations using Facebook's Flair NLP library.