I'm currently working on scaling autonomous discovery at Intology.
I graduated with a master's from the University of Illinois at Urbana-Champaign, supervised by Professor Lingming Zhang. My prior work has demonstrated state of the art performance on PostTrainBench, RE-Bench, MLE-Bench Lite, SWE-Bench, and SWE-Bench Multimodal (among other benchmarks) and has been used by OpenAI and DeepSeek in evaluating their models' software engineering capabilities.
News
- August 3rd, 2026Released Scaling Automated Post-Training: Locus sets SOTA on PostTrainBench (44.7, 2.9 points ahead of the next frontier agent), reaches 51.6% on PostTrainBench+ surpassing the official human-tuned Qwen3-1.7B (49.4%), ranks 4th by peak average rank across all live prize-money Kaggle competitions, and ships a production Bubble model at ~2.8× lower error and 105× lower cost.
- May 19th, 2026Led the release of NanoGPT-Bench, an autonomous AI R&D benchmark built on the NanoGPT Speedrun. Frontier coding agents (Claude Code, Codex, Autoresearch) given a 512 H100-hour budget recover less than 10% of 5 months of human world-record progress (top baseline 9.3%), spending the majority of their compute on hyperparameter tuning rather than the algorithmic research that drives 75.8% of human records.
- November 19th, 2025Previewed Locus, the first AI system to outperform human experts at AI R&D - matching/beating METR's human expert baseline on RE-Bench (1.30 vs 1.27 over a continuous 64-hour run), setting SOTA on MLE-Bench Lite (medals in 77% of competitions vs prior 68%), and achieving SOTA on KernelBench
- May 27th, 2025Zochi published in ACL 2025, “Tempest: Automatic Multi-Turn Jailbreaking of Large Language Models with Tree Search” - the first fully autonomous publication in a top scientific venue by an AI system.
- March 14th, 2025Debuted Zochi, an artificial scientist which produced papers averaging 7.67/10 on NeurIPS guidelines, 3 of which were accepted to ICLR 2025 workshops.
- February 26th, 2025Agentless Lite doubles state-of-the-art on SWE-bench Multimodal from 12.19% to 25.34% for 1/4th of the cost without even requiring a runtime environment!
- February 14th, 2025Released Agentless Lite - a generalized, lightweight adaptation of the Agentless scaffold which is competitive with SOTA agents while only requiring sampling from a single RAG prompt.
- January 31st, 2025Agentless used by both DeepSeek and OpenAI to evaluate their new reasoning models (r1 and o3-mini) on SWE-bench
- Dec 2nd, 2024Integrated Agentless with Claude 3.5 Sonnet to achieve 40.7% solve rate on SWE-bench lite and 50.8% solve rate on SWE-bench verified
- Oct 28th, 2024Released OpenAutoCoder-Agentless 1.5 which increases Agentless performance from 27.3% to 32.00% on SWE-bench lite
- September 26, 2024MedCalc-Bench was accepted as an oral presentation for the NeurIPS 2024 Datasets and Benchmark Track
- September 12, 2024Agentess was used by OpenAI as their scaffold of choice for evalauting gpt-4o, o1-mini, and o1-preview's model autonomy as part of their preparedness framework
- July 1st, 2024Released OpenAutoCoder-Agentless 1.0! Agentless currently is the best open-source approach on SWE-bench lite with 82 fixes (27.3%) and costing on average $0.34 per issue.