Intro
Data Scientist and Engineer with proficiency and experience in various technical tools in the realm of Data Analytics,
ML/AI, Statistical Learning, Design, System Dynamics and Optimization. I am detail oriented and enthusiastic about seeking
solutions to challenges, and new growth opportunities. I have a particular interest and a depth of experience in
the energy sector. I am currently involved in several research projects, such as those involving a deeper understanding
and quantification of the potential risks that bulk electric grids face on the road to decarbonization. Check out my work.
Here is my Linkedin profile.
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Work
Check out some of my NEWER projects on my Github and Publications pages.
Below are some of the PREVIOUS projects I really enjoyed working on.
I wrote a program to scrape news data from the www.space.com/news web page. I then extracted specific information I needed namely the author, date, headline and synopsis. The initial unstructured data had 166,000 characters (excluding spaces) and this was reduced to a structured form with 5,698 characters.
Web Scraping of News Data From space.com Website.
I implemented A/B testing on an Employee dataset to determine whether there was a relationship between marital status and attrition.
I utilized statistical metrics like the t-test and ANOVA. I went ahead to evaluate the reasons( if any) for this trend.
A-B Testing and Statistical Analysis on Employee Attrition Dataset
I designed a smart way to know the best time to purchase/invest in properties in New York City through a combination of time series analysis, clustering and supervised learning.
Property Prices in New York : A Time Series Analysis.
I predicted the likelihood of customers of a telecom business to churn. After obtaining the best machine learning model, I used statistical analysis to determine the factors that had the greatest
impact on the churn rate, and I made pertinent recommendations.
Prediction of Customer Churn Rates for a Telecommunications Business
I used unsupervised learning (clustering analysis) on energy consumption of buildings in Chicago to identify the potential differences on the energy markets. This would be useful for the company to better understand customer energy consumption behavior, improve services delivered and optimize the energy storage and distribution mechanisms.
Unsupervised Learning Analysis on Energy Consumption of Buildings in Chicago.
I predicted the price of houses using machine learning given information about the property. I effectively improved the model by using an external dataset on the federal interest rates at the time.
Prediction of houseprices using Machine Learning.
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About
I am a Data Scientist and Engineer with experience in using a myriad of technologies to unravel actionable insights and identify pragmatic solutions to problems.
I am enthusiastic about using engineering, design and data skills to add value and improve efficacy in different environments.
In my free time, I enjoy learning something new, hiking, traveling, trying new foods, ...
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Publications
I look forward to collaborate on analytics/ software engineering/ design/ data science projects. I am always open
to discussing new projects, research collaborations, or opportunities to contribute to impactful work. I am currently
especially interested in working on energy-related projects.
Email me if you have some interesting ideas and would like to work together (see contact page). Also feel free to
check out my google scholar profile.
1. Lead Author Publications
Ssembatya et al., 2024
Dual Impacts of Space Heating
Electrification and Climate Change Increase Uncertainties in Peak Load Behavior and Grid Capacity Requirements in Texas.
We explore how fully electrifying residential space heating as a means of direct decarbonization (moving away from fossil
fuels for home heating to electrified means), via the adoption of electric heat pumps, alongside the synchronous impacts
of climate change, would affect electricity demand (load) patterns and grid reliability. We use Texas as a case study. We found a lot of
interesting insights regarding the challenges and opportunities.
Ssembatya & Ershaghi, 2019
A Prediction Method for Estimating Time to
Convert From Cyclic to Drive in Steam Injection Processes.
We use data analytics in combination with geological and numerical methods to design a diagnostic tool that would optimize
an oil recovery technique, reduce the carbon footprint and save companies money.
2. Co-Author Publications
DOI: 10.1088/2753-3751/ad1751, 2024
An open-source framework for balancing
computational speed and fidelity in production cost models.
We introduce and describe the development, instantiation, and validation of new open source, scale-adaptive, direct current optimal power flow (DC OPF),
production cost models for the Western U.S bulk electric grid, which are designed with the intention of providing user flexibility in
balancing computational speed and model fidelity.
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★ Highlights ★
We are pleased to announce the final winner of the 2024 Kurz Wind Scholarship is Henry Ssembatya of North Carolina State University.
Texas Winter Grid Strain Spared by High-Efficiency Heat Pumps
CCEE Ph.D. student Henry Ssembatya chosen for 2023 KIETS Climate Leaders Program
Upcoming
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Past
DEC 2024: KURZ WIND SCHOLARSHIP RECEPIENT
I want to express gratitude to the Kurz Wind Division for awarding me this prestigeous 2024 Kurz Wind Scholarship.
DEC 2024: PRESENTATION AT AGU
Our recent work titled "Comparing the Relative Influences of Hydrologic Information and Dams’ Production Decisions on Electricity Price Forecasts"
will be presented at AGU. Check out the session on Thursday 12th Dec, 2024. See details here.
OCT 2024: ATTENDING THE 2024 INFORMS ANNUAL MEETING
Looking forward to attending the 2024 INFORMS ANNUAL MEETING on October 20-23. I hope to learn a lot regarding new advances on research in the power sector.
I am also co-chair in the heat decarbonization session on October 22.
I am especially excited about the new networking, new ideas, making connections, and seeing Seattle.
If you plan to attend, send me a message so we can catch up.
PS: Here is my post on LinkedIn about my experience last year.
JUL 2024: 2024 FAEE SCHOLARSHIP RECEPIENT
Thanks to the Association of Energy engineers Foundation
for awarding me this scholarship. I am exceedingly grateful!
JUL 2024: ATTENDING THE 2024 INTERSECT Research Software Engineeering Bootcamp
I am very fortunate and grateful to have the opportunity to attend the 2024 INTERSECT RSE Bootcamp
at Princeton University. The program is heavily packed with hands-on learning; a deep dive into best practices in software develompent and how that can make me a better/ more efficient
programmer and software developer/engineer. I will be learning alongside some very smart scholars from universities across the country. Thanks to Princeton University, all the instructors, and sponsors
of this worthwhile program.
JUN 2024: NEW PAPER PUBLISHED IN EARTH'S FUTURE
I am so excited to share our most recent publication: "Dual Impacts of Space Heating Electrification and Climate Change
Increase Uncertainties in Peak Load Behavior and Grid Capacity Requirements in Texas".
We explore how fully electrifying residential space heating as a means of direct decarbonization
(moving away from fossil fuels for home heating to electrified means), via the adoption of electric heat pumps, alongside the synchronous impacts of climate change,
could affect electricity demand (load) patterns. We use Texas as a case study. This was an interesting project to work on.
APR 2024: ADMISSION TO JOIN TAU BETA PI
I am very thrilled to be officially counted as a member of Tau Beta Pi, the prestigeous engineering honor society.
Tau Beta Pi recognizes “those who have conferred
honor upon their Alma Mater by distinguished scholarship and exemplary character as students in engineering,
or by their achievements as alumni in the field of engineering.”
I am delighted to get to know/meet/learn from fellow engineers from divergent fields/backgrounds.
MAR 2024: ORAL PRESENTATION AT THE 2024 NC STATE UNIVERSITY'S EWC GRADUATE RESEARCH SYMPOSIUM
I am looking forward to presenting insights from our recent work titled: "How the Dual Effects of Space Heating Electrification
and Climate Change Could Impact Seasonal Peaking and Reliability of the Texas Power Grid." at this year's NC State University,
Environment Water Coastal (EWC) Graduate Research Symposium.
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