Adrian Curic, Developer in Singapore, Singapore
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Adrian Curic

Verified Expert  in Engineering

Data Scientist and Developer

Location
Singapore, Singapore
Toptal Member Since
December 28, 2023

Adrian is a software engineer and data scientist working at the intersection of software engineering, computer vision, and machine learning. He has experience in research, multinational corporations, and startup environments and was awarded patents for real estate and financial modeling projects. Adrian also contributed to surveillance systems for Singapore's border security and participated in competitive coding and hackathons, consistently ranking in the top 1% on platforms like HackerRank.

Portfolio

Real Estate Analytics
Data Science, Computer Vision, Java, Machine Learning, JavaScript, Linux, MySQL...
Peach IntelliHealth
Python, Data Science, Machine Learning, PostgreSQL, Scikit-learn, Keras...
Vi Dimensions
C++, Computer Vision, Machine Learning, OpenCV, Scikit-image...

Experience

Availability

Part-time

Preferred Environment

Python, Data Science, AWS Deployment, PostgreSQL, Artificial Intelligence (AI), Natural Language Processing (NLP), Computer Vision

The most amazing...

...project I've worked on was the deduplication of real estate listings, which raised the interest of competitors, but they couldn't replicate it.

Work Experience

Senior Data Scientist

2020 - 2024
Real Estate Analytics
  • Created a framework that estimates the building's solar rooftop potential, detects buildings from satellite images, rooftop shape, and optimal placement of solar panels, and starts building information profiles using geodata and address matching.
  • Developed a real estate price prediction model that combined hedonic and machine learning approaches and was awarded the WIPO patent, number WO/2022/191775.
  • Built a record-linking framework that allows the consolidation and deduplication of real estate property listings across multiple data sources, which was awarded the WIPO patent, number WO/2022/225455.
  • Developed a framework for address parsing and matching using geodata and natural language processing (NLP). Trained it on over 20 million properties from Singapore, Hong Kong, and Malaysia.
  • Built a floor plan processing framework that extracts property information, generates composite floor plans based on multiple schematics, and restyles the property's floor plan into a design format.
  • Developed a property imputer that processes high-rise building data, identifies valid stacks and residential and commercial floors, and uses imputation techniques to generate data for the missing properties.
  • Built a record-matching library capable of computing similarity for categorical, textual, and numerical features using NLP and unsupervised learning models.
  • Analyzed governmental public transport data to identify daily traffic patterns, compute shop-front traffic numbers, and estimate the impact of property development on commute times.
  • Developed a land lot and address-matching project that can combine real-estate data from unconnected sources based on geodata analysis. The matching can handle complex land lot allocation and unmapped addresses.
  • Built a geodata integration framework to coalesce property data from multiple open source mapping services.
Technologies: Data Science, Computer Vision, Java, Machine Learning, JavaScript, Linux, MySQL, Natural Language Processing (NLP), OpenCV, PostgreSQL, Python, AWS Deployment, GraphQL, Keras, TensorFlow, PyTorch, Scikit-image, Scikit-learn, XGBoost, Pandas, SQL, PostGIS, GeoPandas, Natural Language Toolkit (NLTK), Non-Metric Space Library (NMSLIB), BERT, Generative Pre-trained Transformers (GPT), ChatGPT, PiLLoW, You Only Look Once (YOLO), Segment Anything Model (SAM), Residual Neural Network (ResNet), Seaborn, Folium, Tableau, AWS Elastic Beanstalk, Amazon S3 (AWS S3), Time Series, Artificial Intelligence (AI), Video & Audio Processing, Image Generation, Image Processing, Predictive Modeling, Prompt Engineering, OpenAI GPT-3 API, Recommendation Systems, Machine Learning Operations (MLOps), Neural Networks, Trend Analysis, Real Estate, Data Modeling, Speech to Text, Text to Speech (TTS), Named-entity Recognition (NER), Software, Data Analysis, Statistical Data Analysis, Statistics, Data Engineering, Algorithms, Data Mining, Data Reporting, Analytics, Data Analytics, Data Scraping, Big Data, Data Visualization, Reporting, Web Scraping, Mixed Media, Docker, Data Matching, Dashboards, CSV File Processing, Databases, Data Cleaning, Pricing, Logistic Regression, Deep Learning, Amazon Web Services (AWS), Text to Image, Reinforcement Learning, Agile, Cloud, Clustering, Excel 2013, Forecasting, Microsoft Power BI, Large Language Models (LLMs), OpenAI GPT-4 API, ETL, Data Cleansing, CSS, HTML, Excel 365, Data Scientist, Time Series Analysis, Statistical Analysis, Optimization, Regression Modeling, Statistical Modeling, OpenAI, FastAPI, REST APIs, Architecture, GIS, AWS Lambda, Kubernetes, OCR

Senior Data Scientist

2017 - 2019
Peach IntelliHealth
  • Participated in developing a resource management framework that optimizes the management of medical personnel. Based on intensive care unit (ICU) data, it identifies times when medical attention is most likely to shorten a patient's time in ICU.
  • Researched a model that can predict cardiac arrest events based on real-time data from portable medical devices.
  • Collaborated with Singapore's National University Hospital (NUH) and processed data from ICUs with over two million event records.
Technologies: Python, Data Science, Machine Learning, PostgreSQL, Scikit-learn, Keras, TensorFlow, Pandas, Seaborn, Inventory Management, Demand Planning, Time Series, Artificial Intelligence (AI), Predictive Modeling, MySQL, SQL, Recommendation Systems, Machine Learning Operations (MLOps), Neural Networks, Trend Analysis, Data Modeling, Software, Data Analysis, Statistical Data Analysis, Statistics, Data Engineering, Algorithms, Data Mining, Healthcare, Data Reporting, Analytics, Data Analytics, Big Data, Data Visualization, Reporting, Dashboards, CSV File Processing, Databases, Data Cleaning, Logistic Regression, Deep Learning, XGBoost, Clustering, Excel 2013, Forecasting, Excel 365, Data Scientist, Bayesian Inference & Modeling, Bayesian Statistics, Time Series Analysis, Statistical Analysis, Regression Modeling, Statistical Modeling, Architecture, OCR

Senior Software Engineer

2015 - 2017
Vi Dimensions
  • Contributed to developing surveillance systems based on real-time video processing by working on algorithms for detecting abnormal behavior using flow detection, object detection, and event clustering.
  • Tested and improved system performance for specific client goals. As a result, we won contracts from Singapore's Immigration and Checkpoints Authority and Resorts World Sentosa.
  • Contributed to the deployment of surveillance systems over distributed networks and improved the systems' scalability and robustness.
Technologies: C++, Computer Vision, Machine Learning, OpenCV, Scikit-image, You Only Look Once (YOLO), C, Artificial Intelligence (AI), Video & Audio Processing, Image Processing, Predictive Modeling, MySQL, TensorFlow, Keras, Machine Learning Operations (MLOps), Neural Networks, 3D Tracking, Motion Tracking, Data Modeling, Software, Algorithms, Data Mining, Data Reporting, Analytics, Data Analytics, Data Visualization, Reporting, CSV File Processing, Databases, Data Cleaning, Logistic Regression, Deep Learning, Scikit-learn, Agile, Clustering, Forecasting, Data Scientist, REST APIs, Architecture

Software Engineer

2009 - 2015
IBM
  • Served as a consultant and provided technical support for IBM ILOG CPLEX Optimization Studio and IBM ILOG Supply Chain Applications.
  • Developed business model specifications in IBM ILOG CPLEX Optimization Studio that captured clients' business constraints and goals.
  • Collaborated with clients and the development team to identify, investigate, and resolve software issues.
Technologies: C++, JavaScript, IBM ILOG Supply Chain Applications, WebSphere Application Server, IBM ILOG CPLEX Optimization Studio, Inventory Management, Demand Planning, Data Modeling, Software, Algorithms, Data Reporting, Reporting, CSV File Processing, Databases, Consulting, Mathematics, Optimization

Software Engineer

2007 - 2009
ILOG
  • Provided consulting services and technical support for IBM ILOG CPLEX Optimization Studio and IBM ILOG Supply Chain Applications.
  • Identified, investigated, and resolved software issues while working closely with clients and the development team.
  • Documented clients' business limitations and goals by creating business model specifications in IBM ILOG CPLEX Optimization Studio.
Technologies: C++, JavaScript, Business Rules Management System (BRMS), IBM ILOG CPLEX Optimization Studio, IBM ILOG Supply Chain Applications, Inventory Management, Demand Planning, Data Modeling, Software, Algorithms, Data Reporting, Reporting, CSV File Processing, Databases, Consulting, Mathematics, Optimization

Research Fellow

2006 - 2007
National University of Singapore
  • Researched the modeling of video stream properties using Markov chain probabilities.
  • Contributed to developing the ASTRA: System-Level Design and Analysis of Architectures for Streaming Applications project.
  • Developed a framework for the simulation of mobile biomonitoring applications.
  • Contributed to the development of the project EASEL: Engineering Architectures and Software for the Embedded Landscape.
Technologies: C++, Markov Model, Markov Chain Monte Carlo (MCMC) Algorithms, Data Science, Predictive Modeling, Software, Data Analysis, Statistical Data Analysis, Statistics, Data Engineering, Algorithms, Data Mining, Data Reporting, Analytics, Data Analytics, Data Visualization, CSV File Processing, Generalized Linear Model (GLM), Databases, Data Cleaning, Logistic Regression, Scikit-learn, Forecasting, Mathematics

Research Scholar

2001 - 2005
Verimag
  • Researched methods of partitioning, scheduling, and executing synchronous programs with real-time constraints.
  • Developed tools for code compilation, scheduling, and verification of distributed real-time programs using C, Simulink, and Lustre.
  • Researched methods for scheduling and verifying asynchronous programs in a multithread environment.
Technologies: C++, Simulink, Lustre, Linux, Predictive Modeling, Algorithms, Generalized Linear Model (GLM), Data Cleaning, Logistic Regression, Mathematics

Research Scholar

2000 - 2001
INRIA Rhone-Alpes
  • Contributed to developing distributed model checking of the LOTOS specification using C and Lotus languages.
  • Developed a library for hash table-based storage methods.
  • Created parallel verification tools, including cluster platforms, hash tables, code generation, and intra-cluster communication.
Technologies: C++, C, Linux, Predictive Modeling, Algorithms, Analytics, Data Analytics, Reporting, Data Cleaning, Logistic Regression, Mathematics

Real Estate Price Prediction Model

https://www.sumobrain.com/patents/wipo/System-generating-value-index-properties/WO2022191775A1.html
As a key developer in the project, I worked on developing a real estate price prediction model combining hedonic and machine learning approaches. This work resulted in obtaining the patent, number WO/2022/191775, while working for Real Estate Analytics.

Framework for Deduplication of Real Estate Property Listings

https://www.sumobrain.com/patents/wipo/System-generating-deduplicated-property-listing/WO2022225455A1.html
The record-linking framework allows the consolidation and deduplication of real estate property listings across multiple data sources. I played a key role in developing this framework, and as a result, the project was patented under the number WO/2022/225455.

AI-based Video Surveillance Systems

Contracted by Singapore's Immigration and Checkpoints Authority and Resorts World Sentosa, we developed video surveillance systems to secure national borders. My work involved creating algorithms for detecting abnormal behavior using flow detection, object detection, and event clustering. These algorithms allow AI models to be unsupervised and reinforcement learning for event detections.

Contact Tracing for COVID-19

A project proposal that I developed for contact tracing for COVID-19. The proposal entered the top 12 at the Startup Weekend Singapore 2020 competition. The CANTrack track project uses EZ-Link cards to identify exposure periods and environmental simulation models to determine risk coefficients.

Real-estate High-rise Property Imputer

The imputer is used to fill information gaps in real-estate data. As a key developer, I built a framework that processes high-rise building data, identifies valid stacks, automatically classifies residential and commercial spaces, and uses imputation techniques to generate data for the missing properties in the building's estimated schematics.

AI-based Record Matching and Recommendation System

As a key developer, I built a record-matching framework capable of computing similarity over mixed categorical, textual, and numerical features. The framework uses NLP processing to compute textual feature similarities. An ensemble architecture uses unsupervised and reinforced learning to maximize identity-to-non-identity separation.
2001 - 2005

PhD in Computer Science

Université Grenoble Alpes - Grenoble, France

2000 - 2001

Master's Degree in Computer Science

Université Grenoble Alpes - Grenoble, France

1995 - 2000

Bachelor's Degree in Computer Science

Politehnica University of Bucharest - Bucharest, Romania

FEBRUARY 2024 - PRESENT

Machine Learning, Data Science and Generative AI with Python

Udemy

JANUARY 2024 - PRESENT

Data Scientist Professional

DataCamp

JANUARY 2024 - PRESENT

Associate Data Scientist

DataCamp

Libraries/APIs

OpenCV, Pandas, Keras, TensorFlow, Scikit-learn, XGBoost, Natural Language Toolkit (NLTK), REST APIs, PyTorch, PiLLoW, Folium, OpenAL

Tools

Seaborn, AWS Deployment, Scikit-image, Named-entity Recognition (NER), Excel 2013, GIS, ChatGPT, You Only Look Once (YOLO), Tableau, Microsoft Power BI

Languages

Python, C++, SQL, CSS, HTML, Java, JavaScript, GraphQL, Simulink, Lustre, C

Paradigms

Data Science, Agile, ETL

Platforms

Amazon Web Services (AWS), Linux, Docker, AWS Elastic Beanstalk, AWS Lambda, Kubernetes

Storage

PostgreSQL, MySQL, Databases, PostGIS, Amazon S3 (AWS S3)

Industry Expertise

Healthcare

Other

Computer Vision, Machine Learning, Non-Metric Space Library (NMSLIB), Time Series, Predictive Modeling, Machine Learning Operations (MLOps), Neural Networks, Real Estate, Data Modeling, Software, Data Analysis, Statistical Data Analysis, Statistics, Data Engineering, Algorithms, Data Mining, Data Reporting, Analytics, Data Analytics, Data Visualization, Reporting, Mixed Media, Data Matching, Dashboards, CSV File Processing, Generalized Linear Model (GLM), Data Cleaning, Logistic Regression, Deep Learning, Cloud, Clustering, Forecasting, Data Cleansing, Data Scientist, Time Series Analysis, Statistical Analysis, Optimization, Regression Modeling, Statistical Modeling, OCR, Natural Language Processing (NLP), GeoPandas, BERT, Inventory Management, Artificial Intelligence (AI), Video & Audio Processing, Image Processing, Recommendation Systems, Motion Tracking, Trend Analysis, Data Scraping, Big Data, Pricing, Consulting, Reinforcement Learning, Mathematics, Excel 365, Bayesian Inference & Modeling, Bayesian Statistics, OpenAI, Architecture, Generative Pre-trained Transformers (GPT), Segment Anything Model (SAM), Residual Neural Network (ResNet), IBM ILOG Supply Chain Applications, WebSphere Application Server, Business Rules Management System (BRMS), IBM ILOG CPLEX Optimization Studio, Markov Model, Markov Chain Monte Carlo (MCMC) Algorithms, Demand Planning, Image Generation, Prompt Engineering, OpenAI GPT-3 API, 3D Tracking, Speech to Text, Text to Speech (TTS), Web Scraping, Text to Image, Large Language Models (LLMs), OpenAI GPT-4 API, Generative AI, FastAPI

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