Algorithms & Analytics

Home of Algorithmic Solutions

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Optimization Solutions


Artificial Intelligence


Data Visualization and Graph Analytics

Our Advocacy

We are a team of problem solvers with the advocacy of using the scientific method and computational thinking in providing solutions.

Computational Thinking

We are advocates of Computational thinking in problem solving. We utilize the fundamental techniques of computational sciences in application to different areas of domain.

Scientific Method

We use the scientific method to solve the problems at hand by asking the right question and providing solutions by building on top of the knowledge domain to develop a more sophisticated solution.

Problem Solving

Our Process

Problem Formulation

We want to understand our customers better.

Problem formulation involves asking the right question. We break down the main problem to several subproblems. We formalize the problem definition, we identify the complexity, and we characterize special use cases.

Algorithm Design

We search for the best solution.

Algorithm design involves identifying the appropriate tool set and methodology to solve the current problem at hand. We do not start from scratch, we get the best solution available and build on top of it.


We present solutions and provide actionable insights.

Results are visualized in a particular manner such that key decision makers can get actionable insights in a glance.


Data Visualization

We transform data to information with actionable insights to transform operations and aid up decision making.

Graph Analytics

We utilize network analytics to analyze and visualize relationships that exist between different entities in a complex system.



Artificial Intelligence

We use deep learning for detecting early signs of dementia from MRI scans using convolutional neural networks.

Machine Learning

We use unsupervised and supervised learning in getting to know the customers better through market segmentation.

Predictive Analytics

We use use mathematical models to uncover hidden patterns for predictions.


Operations Research

We use operations research to model complex real-life scenarios using mathematical formulations for multi-objective optimizations.


We use reoptimization to solve hard optimization problems emerging from dynamic environments to ensure fast and guaranteed quality of solutions.

Do you want to learn more?

As part of Algoheim's mission to bridge the knowledge gap between the theory and practice, we are conducting talks and hands-on training to anyone interested. Learn more about the foundations and currents trends in computational problem solving. What are you waiting for? Register to our training modules.

Training Modules

We believe that the best way to learn the fundamental techniques and the current advancements of any field is to teach it.

Data Science

In this module, we present the landscape of different computational methods and approaches for analyzing data, and their corresponding use cases in Healthcare, Logistics, and Finance.

Deep Learning

In this module, we'll cover the fundamentals of deep learning and its application to object and character recognition and Natural Language Processing using TensorFlow.

Data Science: R

In this module, we dive deep into the scientific process of answering relevant questions given available data using R programming language and established computational methods.

Data Science: Python

In this module, we dive deep into the scientific process of answering relevant questions given available data using Python programming language and established computational methods.

Graph Analytics

In this module, we present the different approaches in graph analytics that can provide insights from complex dataset containing different interrelated entities.

Information Visualization

In this module, we provide a practical list of visualization techniques described in terms of their major goals, fundamental principles, and state-of-the-art approaches.

Parallel Computation using GPUs

In this module, we aim to accelerate the trainees' CPU computations by utilizing massively parallel processors such as GPUs, thereby allowing "personal supercomputing."

Algorithmic Design Thinking

In this module, we provide an interactive workshop that will encourage creativity and test the problem solving skills of the participants.

Our Team

Algoheim's roster is a combination of seasoned professionals with the vision of bridging the gap between the academe and the industry.

Jhoirene Clemente


Jhoi is the VP of Algorithms and Analytics in MaroonStudios. She is a PhD candidate and an Assistant Professor in the Department of Computer Science, UP Diliman. She specializes on approaches in solving hard combinatorial optimization problems.

Jeffrey Aborot


Jeff is a Senior Science Research Specialist at the Computer Software Division of DOST-ASTI. He is a graduate student in Computer Science at the UP Diliman. His areas of interest are Quantum Computing, Parallel Computing, Deep Learning and Data Science.

Francis Cabarle


Francis received his PhD degree in computer science from the Algorithms and Complexity, Department of Computer Science, UP Diliman, in 2015. His current research interests include membrane computing, parallel computing, and automata and formal languages.

Grace Agustin


Grace is an MS Computer Science student in UP Diliman, and the founding CEO of HealthBlocks Inc., a next-generation health technology company for developing countries. Her expertise is on Machine Learning and Natural Language Processing.

James Mendoza


James is the founder and Chief Executive Officer of MaroonStudios, Inc. He is also the co-founder of an multi-awarded company called HealthBlocks. He was the Grand Winner of Asean's Next Big Idea and mentored by Silicon Valley along with Uber.

Jessie Suarez


Jessie is an MS Computer Science student in UP Diliman, and has research interests in Image Processing and Machine Learning. Currently, he is also an R&D Engineer in MaroonStudios and leads the company's blockchain development services.

Olivia Demetria


Olivia is a Data Acquisition and Data Feeds Specialist, and currently an R&D Engineer in MaroonStudios focusing on web applications development. She is also an expert on Deep Learning applications in Health.

Zandra Solis


Zandra spearheads the trainings and consultation services of Algoheim. She manages all the external affairs and engagement of the team with industry partners.

Our Core Values

We seek inspiration from nature to define the soul of our organization.
We are inspired by the flexibility and persistence of water and the mountain climber attitude in reaching greater heights.


Flexibility and Persistence


Continuous Improvement

Optima: Relief

Optimization Solutions for Transforming Humanitarian Logistics

Optima: Relief is a service transformation platform for disaster preparation and response that uses an adaptable and data-driven solution to efficiently plan, implement, and control the flow and storage of high priority goods and materials from the point of origin to the point of consumption. The result is an overall logistics plan which is a solution to an optimization problem that ensures minimal routes for faster delivery and response based from the road network and population of a certain region.

Facility Location

As part of pre-disaster preparations, we identify the location of the distribution centers that can supply the demand of all the neighboring evacuation centers in the fastest way possible.

Matching the Supply and Demand

To avoid spoilage of goods, we computed the number of supplies to deliver for each selected warehouse by taking into account the distribution of demand.

Vehicle Routing

To transport high priority goods to all the demand points over an unreliable road network, we produce the optimal route for the delivery trucks that minimizes the total cost of visiting all the identified distribution centers.


Home of Algorithmic Solutions.

8th Floor, Jafer Place
Eisenhower St.
San Juan City

Unit 2A
22 Malingap
Diliman, Quezon City

+63 938 1407