Akhilesh Gotmare

I am an AI Researcher with Salesforce Research in Singapore where I work on deep learning and its applications in processing natural language and code. My current focus is on building LLM Agents and workflows to improve the software development cycle.

I lead AI research on ApexGuru—Salesforce’s AI‑powered code review tool that is trusted by thousands of enterprise customers to optimize and maintain their business‑critical CRM applications. ApexGuru automatically flags anti‑patterns and recommends LLM‑generated fixes, and it has been showcased in Dreamforce keynote sessions for developers and architects.

I completed my MSc at the Department of Computer Science at EPFL, Switzerland, where I was working with Prof. Martin Jaggi's Machine Learning and Optimization laboratory for my thesis project on model parallel training of deep neural nets. Prior to EPFL, I completed my undergraduate studies in Electrical Engineering (with a CSE minor) from IIT Gandhinagar, where among other things I had the fun experience of organizing the maiden TEDx event on campus!

Email  |  Google Scholar  |  LinkedIn  |  GitHub

Publications
PerfCodeGen: Improving Performance of LLM Generated Code with Execution Feedback
Yun Peng, Akhilesh Gotmare, Michael Lyu, Caiming Xiong, Silvio Savarese, Doyen Sahoo
FORGE 2025 (ACM SIGSOFT Distinguished Paper Award)
[ arXiv, FORGE '25, Code ]

CodeT5+: Open Code LLMs for Code Understanding and Generation
Yue Wang, Hung Le, Akhilesh Gotmare, Nghi Bui, Junnan Li, Steven Hoi
EMNLP 2023
[ arXiv, Blog, Code ]

CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning
Hung Le, Yue Wang, Akhilesh Gotmare, Silvio Savarese, Steven Hoi
NeurIPS 2022
[ arXiv, Blog, Code, Media]

Cascaded Fast and Slow Models for Efficient Semantic Code Search
Akhilesh Gotmare, Junnan Li, Shafiq Joty, Steven Hoi
Foundations of Software Engineering 2023
[ FSE 2023 ]

Align before fuse: Vision and language representation learning with momentum distillation
Junnan Li, Ramprasaath Selvaraju, Akhilesh Gotmare, Shafiq Joty, Caiming Xiong, Steven Hoi
NeurIPS 2021 (Spotlight)
[ arXiv, Blog, Code ]

GeDi: Generative Discriminator Guided Sequence Generation
Ben Krause*, Akhilesh Gotmare*, Bryan McCann, Nitish Shirish Keskar, Shafiq Joty, Richard Socher, Nazneen Fatema Rajani
EMNLP 2021 (Findings)
[ arXiv, Blog, VB coverage, Import AI, Code, Demo ]

A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong and Richard Socher
ICLR 2019 (partial results presented at CRACT Workshop, NeurIPS 2018)
[ arXiv, OpenReview, Poster ]

Using Mode Connectivity for Loss Landscape Analysis
Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong and Richard Socher
Workshop on Modern Trends in Nonconvex Optimization for Machine Learning, ICML 2018.
[ arXiv, Poster ]
Decoupling Backpropagation using Constrained Optimization Methods
Akhilesh Gotmare*, Valentin Thomas*, Johanni Brea and Martin Jaggi
Workshop on Efficient Credit Assignment in Deep Learning and Deep Reinforement Learning, ICML 2018.
[ OpenReview, Poster ]

Unsupervised robust nonparametric learning of hidden community properties
Mikhail Langovoy, Akhilesh Gotmare, Martin Jaggi, Suvrit Sra
Mathematical Foundations of Computing 2 (2), 127-147
[ arXiv, AIMS MFC journal ]

Swarm and evolutionary computing algorithms for system identification and filter design: A comprehensive review
Akhilesh Gotmare, Sankha Subhra Bhattacharjee, Rohan Patidar, Nithin V. George
Swarm and Evolutionary Computation, 32, 68-84.
[ Elsevier SWEC journal ]

Nonlinear system identification using a cuckoo search optimized adaptive Hammerstein model
Akhilesh Gotmare, Rohan Patidar, Nithin V. George
Expert systems with applications, 42(5), 2538-2546.
[ Elsevier ESWA journal ]


Website style cloned from Jon Barron's website