Leverage AI and machine learning to develop cutting-edge solutions that empower designers in the electronic design industry.

Grant proposal preparation

▶️ 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗦𝗖𝗢𝗣𝗘Lead the data science team with the development of energy planning and modeling tools to support sales, and energy market bidding platform to automate bid placement for optimal revenue stream.▶️ 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗛𝗜𝗚𝗛𝗟𝗜𝗚𝗛𝗧𝗦➊ Vault-Bidder: Lead the research and development of market bidding platform including 🔋Concurrent bid optimization across multiple energy and ancillary markets using deterministic and stochastic linear programming 🔋Energy market price forecasting model in CAISO using convolutional and recurrent neural network.➋ Optimized Dispatch: Lead the development of a fully modular linear programming model for energy dispatch capable of creating a robust optimization model for various configurations of power plants with unique or mixed-use cases. 🔋Core module was used for future energy planning simulations to support sales, as well as creating intelligent schedule for controlling energy assets in real time, making sure existence of harmony between control and simulation.

▶️ 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗦𝗖𝗢𝗣𝗘I supported the data science team in financial modeling projects, using algorithm design and machine learning to simulate business problems involving energy cost, asset sizing, and bid optimization.I have troubleshooted and generated solutions that supported the pre-sales team in understanding customers and their evolving energy needs.Additionally, I mentored new Data Scientists on developing and testing mathematical models concerning the energy sector.▶️ 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗛𝗜𝗚𝗛𝗟𝗜𝗚𝗛𝗧𝗦➊ 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗕𝗶𝗱𝗱𝗶𝗻𝗴 𝗠𝗼𝗱𝗲𝗹 | Designed a stochastic linear programming model for our Intelligent Bidding tool that automated monetization of solar generation and energy storage assets.🔋 Used forecast uncertainty to optimize the commitment schedule, delivering 80% of revenue capture compared to perfect information.➋ 𝗘𝗻𝗲𝗿𝗴𝘆 𝗔𝘀𝘀𝗲𝘁 𝗦𝗶𝘇𝗶𝗻𝗴 𝗧𝗼𝗼𝗹 | Built a financial model using mixed-integer programming to simulate energy lifecycle costs and footprints across photovoltaic, solar, wind, energy storage, and traditional fossil fuel assets.🔋 Generated solutions in real-time at 1-sec/1-min/1-hour intervals, using CAPEX, OPEX, fuel costs, historical renewable generation, and load profiles as inputs.➌ 𝗘𝗻𝗲𝗿𝗴𝘆 𝗠𝗮𝗿𝗸𝗲𝘁 𝗕𝗶𝗱𝗱𝗶𝗻𝗴 | Created an AI-based platform, using mixed-integer programming that optimized energy bids using renewable energy pricing forecast through an integrated table of pre-defined energy price bins in energy and ancillary markets.🔋 Achieved +85% revenue capture through 10-minute pre-dispatched prices published by AEMO.➍ 𝗘𝗻𝗲𝗿𝗴𝘆 𝗣𝗿𝗶𝗰𝗶𝗻𝗴 𝗧𝗼𝗼𝗹 | Supported pre-sales teams by using linear programming to solve a network flow model representation of energy storage system configurations and automating the calculation of systems and configurations in real-time.

IMS allowed me to apply the skills and knowledge from my Master's program and transition into data science.▶️ 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗦𝗖𝗢𝗣𝗘As a software development team member, I helped support multiple bioinformatics initiatives by designing and developing web-based applications for new products and enhancements to existing ones on behalf of biomedical research organizations.My efforts mainly focused on developing prototypes, code applications, and maintaining the existing application quality through front- and back-end debugging, new support feature implementation, unit testing, and website deployment.▶️ 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗛𝗜𝗚𝗛𝗟𝗜𝗚𝗛𝗧𝗦🖱️ Contributed to database query improvements for the Bioshare data repository by collaborating on open-source Django package developments.🖱️ Enhanced programming skills in Python, Django, HTML, CSS, SQL, JavaScript, Git, and Postgres.

After wrapping up my postdoc research, I pursued my Master's in computer science.▶️ 𝗠𝗔𝗦𝗧𝗘𝗥'𝗦 𝗧𝗛𝗘𝗦𝗜𝗦I focused my thesis topic on how to solve 2 different escape routing problems using mixed-integer programming.My NASA experience inspired this topic, where I worked with sensor arrays in analog design layouts. This time, I applied that concept to challenges in electronic device applications.▶️ 𝗧𝗘𝗔𝗖𝗛𝗜𝗡𝗚 𝗔𝗦𝗦𝗜𝗦𝗧𝗔𝗡𝗧The university offered me a TA position to support my studies.For 2 semesters, I taught courses in object-oriented programming, emphasis in Java, and introductory computer programming in the context of developing websites.This experience was a lot of fun. I enjoyed interacting with the students during lectures and in problem-solving sessions.

After completing my PhD in materials science and engineering, I received multiple offers for postdoctoral assignments.I joined the University of Maryland to learn more about inorganic compounds and their material design.▶️ 𝗥𝗘𝗦𝗘𝗔𝗥𝗖𝗛 𝗦𝗖𝗢𝗣𝗘I managed an NSF-funded research project that evaluated the potential of inorganic titanium oxide compounds, with hollandite structures, in photovoltaic and electronic applications.I developed a research plan and experimental procedures to study the electronic structure of these solid-state, transition-metal oxides and identified ways to increase functionality and control.▶️ 𝗞𝗘𝗬 𝗗𝗜𝗦𝗖𝗢𝗩𝗘𝗥𝗜𝗘𝗦I was challenged to use various synthesis methods, including solid-state synthesis and single crystal growth via the molten salt technique, to produce the hollandite titanite and vanadate compounds.From there, I designed and executed several photoelectron and analytical spectroscopy studies to characterize the electronic structure and collaborated with an expert in density-functional theory to calculate the optimal electronic band structure.⚛️ First-authored 2 scientific publications demonstrating material promise as an anode in solid oxide fuel cells.⚛️ Co-authored a second NSF study detailing optical conductivity and computational physics experiments that evaluated quasiparticle behavior in manganate materials, using XRD, XPS, UV-Vis, and magnetic and electrical resistivity measurements.I enjoyed the freedom I was given to do my research, including designing a study and its related experimental procedures and getting exposure to applying photoelectron and analytical spectra techniques to materials design.Along the way, I also had the chance to mentor an undergraduate student in best laboratory research practices.After completing my postdoc assignment, I stayed on with the university to pursue my Master's in computer science.

ASRC Federal contracted me to work under NASA's Detector System Branch in the Detector Development Lab.▶️ 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗦𝗖𝗢𝗣𝗘Working in a cleanroom environment, I supported a team of Engineers in the design, fabrication, and systems testing of advanced detectors, including infra-red filters using MEMS fabrication techniques for space-related applications.My prior research experience supported me in the fabrication and optical characterization of these filter arrays across the IR spectrum.▶️ 𝗧𝗘𝗖𝗛𝗡𝗜𝗖𝗔𝗟 𝗛𝗜𝗚𝗛𝗟𝗜𝗚𝗛𝗧𝗦➊ 𝗢𝗽𝘁𝗶𝗰𝗮𝗹 𝗠𝗲𝘀𝗵 𝗙𝗶𝗹𝘁𝗲𝗿𝘀 | Designed and fabricated a manufacturing process for a polymer-based, free-standing metal mesh optical filter capable of screening IR radiation in ground-, water-, and space-based instrumentation.⚛️ Leveraged chemistry background to develop an inductive-capacitive bi-layer.⚛️ Co-authored and submitted a patent application for the technology.➋ 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 & 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 | Used C# and .Net frameworks to develop a 2D CAD software layout that integrated with NASA's Flying Probe Tester and served as a QC tool that mapped a user-defined area and analyzed thousands of wafers and integrated circuit devices to detect circuit faults using automated processes.⚛️ Reduced data analysis time from several hours to a few minutes.⚛️ Enabled visualization of results in a tabulated or graphical format.⚛️ Streamlined editing of IPC files and setup of electrical tests.Working at NASA exposed me to new research areas, including polymers and MEMS fabrication. It provided a great learning opportunity to apply my data analysis skills in a quality control context.I also got to mentor a graduate student during the summer in device fabrication.During this time, I began a Master's program in computer science. When my contract ended, I used this opportunity to look for a role to hone my computer science skills further.

I relocated to the US to pursue my PhD in materials science and engineering, expanding my expertise beyond my Master's.▶️ 𝗥𝗘𝗦𝗘𝗔𝗥𝗖𝗛 𝗦𝗖𝗢𝗣𝗘My research focused on investigating the structural, magnetic, and electronic properties of rare earth and transition metal complex oxide thin films for electronic device applications.▶️ 𝗞𝗘𝗬 𝗗𝗜𝗦𝗖𝗢𝗩𝗘𝗥𝗜𝗘𝗦Throughout my graduate work, I authored and co-authored more than 15 scientific publications that offered insights into promising nanotechnology and semiconductor applications.⚛️ Optimized the process for thin film growth of GdTiO3, SrTiO3, and LaNiO3 structures using hybrid molecular beam epitaxy and RF magnetron sputtering methods, and characterized their electronic properties.⚛️ Investigated the magneto-transport properties of a prototype Mott/band insulator, explicitly assessing the origin of 2-dimensional electron gas formation at the interface between GdTiO3 and SrTiO3 compounds.

▶️ 𝗘𝗔𝗥𝗟𝗬 𝗖𝗔𝗥𝗘𝗘𝗥While earning my Master's in materials science and engineering, I applied computational analyses and machine learning techniques to 2 materials science projects.➊ 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗡𝗲𝘂𝗿𝗮𝗹 𝗡𝗲𝘁𝘄𝗼𝗿𝗸 | Developed and trained a model that predicted the oxidation behavior of magnesia graphite composites, achieving 99% fit, which allowed calculation of kinetic parameters, such as diffusion coefficient and diffusion activation energy.➋ 𝗙𝗶𝗻𝗶𝘁𝗲 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗠𝗼𝗱𝗲𝗹 | Solved the strain distribution in BaTiO3-based PCTR thermistors undergoing electro-thermal heating under different conditions, which offered insights for self-regulating heating elements and thermal control applications.