Curriculum Vitae
[Download CV]
Education
- Ph.D. in Electrical Engineering - GPA 4.00/4.00
- THE UNIVERSITY OF TEXAS AT DALLAS, Dec 2024 Expected
- Masters in Electrical Engineering - Signal Processing - GPA 4.00/4.00
- THE UNIVERSITY OF TEXAS AT DALLAS
- B.S. in Electrical Engineering - GPA 3.67/4.00
- UNIVERSITY OF WISCONSIN – PLATTEVILLE
Work experience
- May 2024 - Aug 2024: Applied Scientist Intern
- Amazon Web Services - AWS AI Labs
- Part of Amazon Q team working on audio-visual to speech translation.
- Sept 2020 – Present: Research Assistant
- Multimodal Signal Processing (MSP) Lab, Richardson, TX
- Currently working on developing machine learning algorithms for studying expressive behavior. My research topics include emotion recognition, self-supervised learning, multimodal modelling, handling missing modalities, and audio and video signal processing. Collecting the largest spontaneous speech emotion dataset based on real-world podcast audios.
- Supervisor: Dr. Carlos Busso
- Feb 2024 – May 2024: Research Intern
- Openstream.ai
- Developed emotion recognition systems with 20% improvement in recognition performance for conversational AI avatars to enhance user interaction and engagement.
- Collaborated with a multidisciplinary team to design and refine generative AI avatars for conversational interfaces.
- June 2023 - Oct 2023: Applied Scientist Intern
- Amazon Web Services - AWS AI Labs
- Part of AWS Transcribe Team working on multimodal learning.
- Jan 2019 – Aug 2020: Electrical Design Engineer
- Seagrave Fire Apparatus LLC, Clintonville, WI
- Principal electrical engineer on research and development of new generation of Seagrave’s fire apparatus. Coordinated with mechanical and hydraulics teams updates needed to implement CAN bus J1939 protocol rate change-over from 250 kbits/s to 500 kbits/s. Developed a database to enable easy access from other teams to electrical parts and reduce time spent consulting with electrical engineers.
- Jan 2018 – Dec 2018: Student Researcher
- Pioneer Speech Signal Processing Lab, Platteville, WI
- Researched statistical methods used in machine learning clustering algorithms. Studied and implemented different clustering algorithms in MATLAB, such as, k-means, hierarchical clustering, and decision trees. Successfully investigated and implemented techniques to improve k-means clustering, such as, optimal initialization, best number of centroids, and stopping criterion methods.
- Supervisor: Dr. Hynek Boril
Skills
- Languages
- Python, MATLAB, Verilog, VHDL, C++, HCS12
- Frameworks & Tools
- Pytorch, TensorFlow, Kaldi, OpenCV, SolidWorks, AutoCAD, Simulink, LabVIEW, IQAN
Publications
[Access to Publications]
Teaching
