July 1, 2024 - PresentAccount: NBC Universal Pictures - Home Entertainment

March 2, 2023 - June 30, 2024Account: NBC Peacock

January 30, 2023 - March 1, 2023Account: NBC Peacock• Built and maintained data analysis pipelines, designing/training/validating machine learning models and algorithms based on state-of-the-art research• Led the development and utilization of machine learning techniques such as classification, clustering, regression, NLP, deep learning (CNN, RNN, GANs), time series forecasting, and Bayesian methods to build scalable solutions• Research new techniques and technologies in the space of ML and AI, and evaluated their potential for different business use cases.

September 21, 2021 - January 29, 2023Account: NBC Peacock• Built and maintained data analysis pipelines, designing/training/validating machine learning models and algorithms based on state-of-the-art research• Led the development and utilization of machine learning techniques such as classification, clustering, regression, NLP, deep learning (CNN, RNN, GANs), time series forecasting, and Bayesian methods to build scalable solutions• Research new techniques and technologies in the space of ML and AI, and evaluated their potential for different business use cases.

F20: CHEM 301- Biochemistry Chemistry IS21: CHEM 112-General Chemistry II

Created Python API for client to track hospital resources in real time.

CHEM 203 (General Chemistry II with lab)-Demonstrated an excellent in teaching and a commitment to integrating new technologies in the learning process-Demonstrated the ability to inspire, motivate and empower students to succeed-Design the course to meet learning outcomes, and promoted students’ active participation in their own learning-Created an effective learning environment that fostered students’ intellectual curiosity which allowed students to problem solve using chemistry-specific strategies-Contribute to and provide leadership in the student’s academic and professional communities, and promote collaboration and teamwork among members of these communities

Conducted nanoparticle research for the delivery of antagomirs combined with novel drug targets for treatment of MLL leukemia--Hypothesis--A combination of three specific anti-miRs, packaged into anti-CLEC12 antibody-conjugated nanoparticles (NP), may be more effective at delivering the anti-miR payload than non-conjugated NP to MLL fusion protein leukemia cell lines that express the cognate CLEC12 receptor. Novel MLL-targeting drugs may act additively or synergistically with the anti-miRs to inhibit cell colony forming ability, a surrogate for leukemia stem cell activity. The novel MLL-targeting drugs to be tested include:• DOT1L Inhibitor selectivity binds to DOT1L to decease H3K79 methylation and block MLL fusion targets expression• IBET blocks the BRD4 interaction with chromatin• MI-2 blocks the interaction between Menin–MLL inhibiting the interaction with LEDGF and chromatin association--Imaging Processing--Thirty images were taken of each well out of a possible 69 fields/well area. Matlab software was used to create an algorithm for counting colonies from the colony forming cell assays. Our algorithm consisted of four main components: image thresholding, morphological erosion to identify high-intensity objects, determining quasi-euclidean distances between centroids, and contour map generation.--Conclusions--1. We determined experimental inhibitory colony forming IC50 values for MLL targeting drugs that are currently in pre-clinical or early phase clinical trials2. K562, U937, MV4:11, and THP-1 illustrated increased sensitivity of MLL leukemia targeting drugs due to the NP delivery of anti-miRs at sub-optimum dosing levels3. K562 and THP-1 illustrated increased sensitivity due to the CLEC12 targeted NPs as compared to non-targeted NPs

Experience includes:-Liquid and gel cell culture-Handling biological samples (e.g., animal organs, biological cell lines)Analysis techniques include:-Cytospin centrifuge-Flow cytometry-RT-PCR

In my life, I have had numerous role models and mentors who were leaders in their chosen field, but who were also excellent teachers; one of the best was my mom. My mom had a phrase that she would always say to me, “Never let anyone tell you that you can’t do something, because if you put your mind to it, you can do anything.” To this day, when I am standing in front of a classroom and I see that my students are struggling with a topic, I remind them of what my mom always used to say and I feel that it helps to give them the encouragement they need. Many of my students never had an adult tell them this before, and mean it. The reason why I teach, specifically introductory courses, at HCC is to give back to students who may not have had similar opportunities early on in their educational careers. I hope to inspire my students to see the beauty and the awe-inspiring wonder found in the world of chemistry, because being able to make slime dance is pretty darn cool.Undergraduate courses:Sum10: ENGR 1201-Introduction to EngineeringSum13, Sum14: CHEM 1105-Introductory Chemistry (Laboratory) F10, S11, F12: CHEM 1305-Introductory Chemistry (Lecture) S12, F13, S14: CHEM 1405-Introductory Chemistry I F11, F12, S13, Sum13, F14, S15: CHEM 1411-General Chemistry IThe following table summarizes my overall instructor rating from 145 electronic course surveys collected over 7 semesters at Houston Community College (F11, S12, F12, S13, F13, S14, F14).Very Good: 60.1%, Satisfactory: 31.6%, Unsatisfactory: 6.0%, Very Unsatisfactory: 2.3%

Created a 2D computational model to describe the transport of AAV serotype 2 protease-activatable virus nanoparticles through a tumor microenvironment. This work was based on published literature by accounting for changes in the bulk radial porosity and the spatial homogeneity found in the tumor spheroid. We then extended the 2D computational model to examine the effects of different intratumoral and intravascular administration routes within a 3D tumor spheroid microenvironment to predict the effects of fluid dynamics and reactive surface phenomena on nanoparticle transport.

Supported the efforts of the Amine R&D business function of Dow Oil & Gas by leading the thermodynamic property modeling group for natural gas and synthesis gas plants for both in-house and customer applications. Managed and coordinated the efforts of global resources (+5 engineers) to validate and test new amine process simulation models and databases. During my tenure at The Dow Chemical Company, I have authored or co-authored 10 peer reviewed confidential publications.

Supported the efforts of the Amine R&D business function of Dow Oil & Gas by leading the thermodynamic property modeling group for natural gas and synthesis gas plants.

Lead the development efforts to complete an CO2 electrolyte NRTL physical property model based on proprietary experimental data from LTP, Dow Analytical, and Fauske & Associates. Managed and updated the physical property models in support of the UOP Selexol business function of Dow Oil & Gas. Taught and assisted process engineers in resolving technical and modeling issues associated with the Aspen Plus simulation suite.

Served as the Co-Site Implementation Leader for the Texas Operations Diversity Network within the Dow Chemical Company. Organized quarterly events for the membership to include: Out with GLAD and Discussions with GLAD. Served on the United Way Chili Cook-Off Steering Team as the GLAD representative.

-Developed and maintained electrolyte NRTL and Equation of State physical property models utilizing custom Fortran subroutines in Aspen Plus to describe the speciation, calorimetry, and equilibrium phase behavior for carbon capture absorption technologies-Coordinated the efforts of European resources to validate and test new amine models-Served as Co-Site Implementation Leader for a Texas Operations Diversity Network

-Developed an electrolyte NRTL model utilizing Aspen Plus to describe the speciation, calorimetry, and equilibrium behavior of potassium carbonate, piperazine, and monoethanolamine solutions-Supervised, mentored, trained, and consulted with several visiting scholars and undergraduate researchers for their various projects-Taught and assisted various industrial sponsors in resolving technical and modeling issuesassociated with Aspen Plus-Constructed a closed-loop equilibrium apparatus for multi-component vapor phase analysis

Conducted experiments to expand on the previous thermodynamic understanding of CO2 in the potassium carbonate/piperazine system in terms of the solubility of CO2 at elevated temperatures and to report calorimetric measurements over the range of temperatures studied.This project was undertaken as part of a collaborative effort between The University of Texas at Austin and the Norwegian University of Science and Technology.

-Conducted computer simulations of EO/BO surfactants in oil/water/surfactant solution systems to predict solubilizing efficiencies of surfactants-Modeled microemulsions by lattice simulations to explore the effects of the chain length of EO/BO block copolymers and the cosurfactant concentration on solubilization efficiency

-Developed a model to predict critical physical properties for a blend of ESI (Ethylene Styrene Intercopolymer) polymers with selected thermoplastic engineering polymers-Analyzed and characterized samples produced in the project described above-Analysis included: Tensile Strength, Sore A Hardness, and Gel Analysis

-Researched and designed an automated indicator spreadsheet to give updated information for the operations for a particular plant, an inline analysis of the finishing streams, and give real time statistical analysis for the plant-Designed and built an VLE apparatus to collect data for epi/water binary systems