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 training CodeLLMs to improving the software development cycle.

I lead AI research on ApexGuru, which improves Apex code quality by identifying anti-patterns and generates optimizations for fixing them, and has been featured at Dreamforce's 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
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