Employer: Coohom
Date: May 2018 - Aug 2018
Location: Shanghai, China
Contributed to frontend and backend development for a high-growth SaaS interior design platform, focusing on UI/UX improvements and automation scripts for localization.
Employer: Open-Source at Illinois (RSO)
Date: Nov 2020 - May 2021
Location: Remote
Fostered growth of a campus open-source community through technical education programs, and the successful launch of multiple student-driven software projects.
Employer: Technology Entrepreneur Center
Date: Aug 2021 - May 2023
Location: Champaign, IL, USA
Led technical instruction and mentorship for over 20 undergraduates in the Developing Breakthrough Projects course, guiding teams through hands-on product development in machine learning, robotics and data science.
Employer: KK Stevens Publishing Co
Date: Jan 2023 - Jun 2023
Location: Astoria, IL, USA
Architected a modern web-based enterprise application to replace legacy management information systems, working closely with stakeholders to optimize business processes and improve operational efficiency.
Employer: Undergraduate Research in Scientific Advancement
Date: Dec 2024 - Jan 2024
Location: Champaign, IL, USA
Drove a team of undergraduate researchers in developing novel signal processing applications for robotics, providing technical mentorship and professional development guidance throughout the year-long program.
Employer: The Common AI, Inc.
Date: Jun 2025 - Current
Location: Dallas, TX, USA
As the co-founder and CTO, I lead the company’s technical vision, product architecture, and engineering execution. Our mission is to build a sophisticated AI platform to solve high-stakes challenges for enterprise clients.
Completed:
Prototyped a microservice to provide students with actionable budgeting data by integrating public APIs (Reddit) with federal economic statistics (BLS).
Completed:
Architected a scalable robotics framework to autonomously generate a massive AI training dataset, demonstrating expertise in data engineering and systems integration for machine learning.
Completed:
An award-winning research project that investigated the critical business risk of data bias in AI, quantifying the performance gap of an English-trained model on unseen languages.
Completed:
Led the end-to-end development of a modern web platform to replace a legacy enterprise system, improving efficiency and removing bloat.
Completed:
Engineered a novel control system using physics-informed neural networks, proving the viability of advanced AI for high-value industrial and commercial applications.
Completed:
Pioneered a novel sensor fusion system for Edge/IoT devices, using AI/ML to dramatically improve voice clarity in extreme environments and exploring LLM-based contextual enhancement.
Completed:
A strategic R&D initiative that pioneered the use of diffusion models to generate high-fidelity synthetic data for complex engineering systems, creating a new paradigm for digital simulation and AI training.
Published: May 2022
Venue: Institute of Electrical and Electronics Engineers (IEEE)
This paper presents a mechatronic system designed to generate large-scale dynamic datasets for acoustics research, facilitating the development and evaluation of acoustic signal processing algorithms.
A. Lu, E. Moore, A. Nallanthighall, K. Sarkar, M. Mittal, R.M. Corey, A.C. Singer, "Mechatronic Generation of Datasets for Acoustics Research," 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), 2022, pp. 1-5.
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Published: Oct 2022
Venue: American Institute of Physics (AIP), Institute of Electrical and Electronics Engineers (IEEE)
Demonstrated a cloud platform for remotely orchestrating multi-robot experiments and real-time data collection across international locations.
Published: Mar 2023
Venue: American Institute of Physics (AIP)
This study explores the use of air and body-conduction microphones to enhance speech by extending bandwidth, aiming to improve speech quality in various applications.
A. Lu, M. Mittal, K. Sarkar, R.M. Corey, P. Smaragdis, A.C. Singer, "Bandwidth extension with air and body-conduction microphones for speech enhancement," The Journal of the Acoustical Society of America, vol. 153, no. 3_supplement, pp. A51-A51, 2023.
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Published: Mar 2023
Venue: American Institute of Physics (AIP)
This study introduces mechanized acoustic panels capable of adjusting reverb characteristics in a room, offering dynamic control over acoustic environments.
A. Nallanthighall, A. Lu, K. Sarkar, M. Mittal, A.C. Singer, "Mechanized acoustic panels for variable reverb control," The Journal of the Acoustical Society of America, vol. 153, no. 3_supplement, pp. A220-A220, 2023.
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Published: Mar 2023
Venue: American Institute of Physics (AIP)
This paper presents 3D-printed acoustic simulators capable of speech and movement, serving as tools for testing and developing audio equipment and AI.
X. Yue, A. Nallanthighall, M. Mittal, A. Lu, K. Sarkar, R.M. Corey, P. Smaragdis, A.C. Singer, "3D-printed acoustic head simulators that talk and move," The Journal of the Acoustical Society of America, vol. 153, no. 3_supplement, pp. A38-A38, 2023.
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Published: Mar 2023
Venue: American Institute of Physics (AIP)
This research explores source separation techniques employing bandlimited external microphones in conjunction with a microphone array to improve separation performance.
M. Mittal, K. Sarkar, A. Lu, R.M. Corey, A.C. Singer, "Source separation using bandlimited external microphones and a microphone array," The Journal of the Acoustical Society of America, vol. 153, no. 3_supplement, pp. A52-A52, 2023.
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Published: May 2023
Venue: University of Illinois Urbana-Champaign
This award-winning research quantified the risk of deploying multilingual AI models on real-world data.
Published: Oct 2023
Venue: American Institute of Physics (AIP)
This paper proposes a novel approach to source separation by combining multiple beamformers on a frame-by-frame basis, enhancing the separation of concurrent sound sources.
M. Mittal, K. Sarkar, A. Lu, R. Corey, A. Singer, "Frame-by-frame mixture of beamformers for source separation," Proceedings of Meetings on Acoustics, vol. 51, no. 1, pp. 050007, 2023.
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Published: Oct 2023
Venue: Institute of Electrical and Electronics Engineers (IEEE)
Delivered a live technical demonstration of my innovative IoT-enabled binaural data collection system to leading researchers in AI, ML, and HCI.
Published: Mar 2024
Venue: American Institute of Physics (AIP)
This research addresses the challenge of speech enhancement in hearing aids by utilizing a wireless remote microphone, focusing on minimizing delay to improve user experience.
A. Lu, Y. Zhuang, R.M. Corey, A.C. Singer, "Delay-constrained hearing aid speech enhancement using a wireless remote microphone," The Journal of the Acoustical Society of America, vol. 155, no. 3_Supplement, pp. A42-A42, 2024.
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Published: Aug 2024
Venue: Discovery Partners Institute
A technical showcase and progress update on cutting-edge robotics and AI research presented at the Discovery Partners Institute in Chicago
Published: Dec 2024
Venue: University of Illinois Urbana-Champaign
This thesis presents comprehensive research on automating acoustic signal processing experiments and generating audio machine learning datasets using robotic systems.
A. Lu, "Automating acoustic signal processing experiments and audio machine learning datasets using robots," Ph.D. dissertation, University of Illinois at Urbana-Champaign, 2024.
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Published: May 2025
Venue: American Institute of Physics (AIP)
This research explores denoising and bandwidth extension techniques using the fusion of air and bone microphones for improved audio quality.
A. Lu, K. Sarkar, M. Mittal, R.M. Corey, P. Smaragdis, A.C. Singer, "Denoising bandwidth extension via fusion of air and bone microphones," Proceedings of Meetings on Acoustics, vol. 51, no. 1, pp. 050010, 2023.
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Published: Jul 2025
Venue: European Acoustics Association
This paper presents Latent FxLMS, a novel approach to accelerating active noise control using neural adaptive filters.
K. Sarkar, A. Lu, M. Mittal, Y. Zhuang, R. Corey, A. Singer, "Latent FxLMS: Accelerating Active Noise Control with Neural Adaptive Filters," arXiv preprint arXiv:2507.03854, 2025.
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