RESEARCH EXPERIENCES

1. Research Scholar at The University of Tokyo Tokyo, Japan | April 2023 – April 2025
   • Researched recommender systems for news, addressing popularity bias and news avoidance. Published at SIAM International Conference on Data Mining (SDM'25), under the guidance of Professor Toyotaro Suzumura.
   • Collaborated closely with Nikkei Inc. on the design and implementation of novel recommender system models under the guidance of Dr Yuichiro Yasui.
   • Developed deep learning models for high-frequency stock price forecasting, with a focus on predicting market behavior during election periods.
   • Conducted research on foundational models of large language models (LLMs), exploring the use of retrieval-augmented generation (RAG) and long-context handling.
   • Tech Stack: Python, PyTorch, Lightning AI, TensorFlow, Keras, Plotly, CrewAI
2. Research Intern at Cellcrypt Arkansas, US | September 2020 – June 2021
   • Optimized machine learning models to improve VoIP performance, enhancing call quality and reducing latency.
   • Built a machine learning pipeline for automated PJSIP parameter tuning, boosting call quality metrics by 7%.
   • Tech Stack: C, C++, PyTorch, Flask, AWS ECS.

PROFESSIONAL EXPERIENCES

1. Technology Coordinator at VOGA Brasília, Brazil | February 2022 – April 2023
   • Led system integration and scalability efforts following VOGA's acquisition by BTG Pactual, South America's largest investment bank. Developed a centralized investment monitoring and stock tracking system, integrating internal platforms with BTG's API, and managing over USD 300 million in assets.
   • Tech Stack: FastAPI, Nx, Flask, NestJS, AWS services (EC2, DynamoDB, RDS, Lambda, S3), and Cloudflare.
2. Development Team Lead at VOGA Brasília, Brazil | July 2021 – January 2022
   • Led a team to build a web platform for stock market monitoring and equity crowdfunding, launching BridgeHub, a spin-off company within VOGA.
   • Tech Stack: FastAPI, Nx, NextJS, NestJS, TailwindCSS, and AWS services (ECS, Lambda, RDS).

RESEARCH PAPERS

1. A Look Into News Avoidance Through AWRS: An Avoidance-Aware Recommender System
   January - July 2024 | SDM'25 Proceedings | ArXiv
   • Collaboration: Toyotaro Suzumura (The University of Tokyo) and Yuichiro Yasui (Nikkei Inc.)
   • Highlights: Developed AWRS, an Avoidance-Aware Recommender System for news that incorporates article avoidance as a key factor to improve recommendations. Evaluated on datasets in English, Norwegian, and Japanese, AWRS outperformed existing methods by leveraging avoidance as an indicator of user preferences.
2. POPK: Mitigating Popularity Bias via a Temporal-Counterfactual
   April - July 2024 | ArXiv
   • Collaboration: Toyotaro Suzumura (The University of Tokyo) and Yuichiro Yasui (Nikkei Inc.)
   • Highlights: Developed POPK, a model which uses temporal-counterfactual analysis to reduce popularity bias in news recommendations. POPK improves accuracy and diversity by systematically removing the influence of popular articles.
3. From Votes to Volatility Predicting the Stock Market on Election Day
   August - December 2024 | ArXiv
   • Collaboration: Toyotaro Suzumura (The University of Tokyo)
   • Highlights: Developed POPK, a model which uses temporal-counterfactual analysis to reduce popularity bias in news recommendations. POPK improves accuracy and diversity by systematically removing the influence of popular articles.
4. A SHA-3 Co-Processor for IoT Applications
   January - November 2020 | Paper (IEEE - WCNSPS'20)
   • Collaboration: Alexandre S. Nery (University of Brasília) and Alexandre da C. Sena (Rio de Janeiro State University)
   • Highlights: Designed and implemented a SHA-3 hardware co-processor on FPGA for IoT applications, achieving 65% faster performance than ARM Cortex-A9 with improved energy efficiency and reduced circuit area.

AWARDS

1. Japanese Government (MEXT) Research Scholarship April 2023 - April 2025 | certificate
   About: The Japanese Government (MEXT) Research Scholarship supports international students conducting research at Japanese higher education institutions.
2. Brazilian Government (CNPq) Institutional Scientific Initiation Scholarship (PIBIC) August 2019 - July 2020 | certificate
   
   About: The PIBIC program, funded by the Federal Government of Brazil, aims to support undergraduate students in engaging with research, technological development, and innovation.
3. SIAM Travel Award – SDM25 May 2025 | award letter
   About: Granted by the Society for Industrial and Applied Mathematics (SIAM), this award supported travel to the 2025 SIAM International Conference on Data Mining (SDM25) held in Alexandria, VA. It recognized promising early-career researchers contributing to the field.

CERTIFICATIONS

• IELTS: Overall Band Score: 8.5 (Listening: 8.0, Reading: 8.5, Writing: 7.0, Speaking: 8.5)

PROJECTS

1. N2S - Knowledge Made Accessible
   Open-source platform focused on knowledge dissemination, simplifying deep learning, algorithms, and information theory with clear, visual explanations. Website
2. Life Before The End
   An open-source platform designed to promote Indigenous awareness and scientific work to support Indigenous communities. Website

OPEN SOURCE CONTRIBUTIONS

1. NewsrecLib
   Implemented the PP-REC SOTA model into the news recommendation framework. code
2. Qlib
   Added support for the Brazilian stock market, enabling local investors and researchers to use Qlib's machine learning models and data processing pipelines on Brazilian stock data. code

ESSENTIALS

COURSES

• Deep Learning @ Carnegie Mellon University | certificate
• Digital Signal Processing @ EPFL | certificate
• Information Theory @ The Chinese University of Hong Kong | certificate
• Algorithms and Data Structures @ UCSD | certificate
• Model United Nations @ Harvard University | certificate
• Model United Nations @ Yale University | certificate

LEADERSHIP EXPERIENCES

• Commercial Director, Electrical Engineering Junior Enterprise (ENETEC) June 2019 - April 2020
  
  Led the team to achieve annual goals set by the National Association of Junior Enterprises in Brazil (Brasil júnior), securing projects worth approximately USD 30,000, which funded training and development for company members.

LANGUAGES

TECH STACK