Alibek Kaliyev
ML Engineer @ Point72 · New York
I'm a machine learning engineer at Point72 in New York. Before that I was at AWS (2024–2026), one of the first engineers on the six-person team that built Amazon Quick Suite's conversational AI from the ground up — and earlier, analytics infrastructure for Amazon Q Business.
My background is in research: three and a half years in the Multifunctional Materials & Machine Learning Group at Lehigh University (PI: Joshua Agar), building physics-constrained neural networks for scanning-probe microscopy — published at a NeurIPS 2023 workshop and in Advanced Materials. I'm now working through a part-time MS in computer science at UT Austin, specializing in machine learning.
I grew up in Kazakhstan and speak English, Russian, and Kazakh. Outside of work, I'm a second-degree black belt.
alibek.t.kaliyev@icloud.com GitHub Google Scholar X LinkedIn CV
News
- May ’26 “When Agents Disagree” published in Applied Sciences.
- Apr ’26 Joined Point72 as a machine learning engineer.
- Aug ’24 Started a part-time MS in computer science at UT Austin.
- Jun ’24 Joined AWS as a software development engineer in New York.
- May ’24 Graduated from Lehigh University — BS in Computer Science & Business.
- Dec ’23 Presented Rapid Fitting of Band-Excitation PFM at the NeurIPS 2023 AI for Accelerated Materials Design workshop, New Orleans.
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- Nov ’22 Our paper on linear ML models in ferroelectric switching published in Advanced Materials.
- Oct ’22 Presented our BE-PFM fitting work at the Gulf Coast Undergraduate Research Symposium, Rice University.
- Oct ’22 Presented Rapid Fitting of BE-PFM at the Fast Machine Learning for Science Workshop, SMU.
- Sep ’21 Presented at the MSE Undergraduate Research Symposium, Lehigh University.
- May ’21 Won the Most Novel Research Award at the Drexel AI Research Conference.
- Apr ’21 Presented at the David and Lorraine Freed Undergraduate Research Symposium, Lehigh University.
- Oct ’20 Presented at the Gulf Coast Undergraduate Research Symposium, Rice University.
- Aug ’20 Presented at the Center for Nanophase Materials Sciences User Meeting, Oak Ridge National Laboratory.
- Jun ’20 Joined the Multifunctional Materials & ML Group at Lehigh as an undergraduate researcher, working on real-time ML for experimental materials science.
Selected Work
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Applied Sciences · 2026
When Agents Disagree: The Selection Bottleneck in Multi-Agent LLM Pipelines
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NeurIPS 2023 · AI for Accelerated Materials Design Workshop
Rapid Fitting of Band-Excitation Piezoresponse Force Microscopy Using Physics Constrained Unsupervised Neural Networks
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Advanced Materials · 2022
Why it is Unfortunate that Linear Machine Learning Models “Work” so well in Electromechanical Switching of Ferroelectric Thin Films
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Project · 2026
Archaic AI