@@ -45,6 +45,23 @@ @inproceedings{liang2026rtneus
   themes={neurosymbolic}
 }
 
+@inproceedings{sanyal2026entrollm,
+  title={{EntroLLM}: Entropy Encoded Weight Compression for Efficient Large Language Model Inference on Edge Devices},
+  author={Sanyal, Arnab and Datta, Gourav and Mukherjee, Prithwish and Chinchali, Sandeep P. and Orshansky, Michael},
+  booktitle={ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
+  year={2026},
+  pages={19742--19746},
+  doi={10.1109/ICASSP55912.2026.11464777},
+  url={https://doi.org/10.1109/ICASSP55912.2026.11464777},
+  arxiv={https://arxiv.org/abs/2505.02380},
+  code={https://github.com/arnabsanyal/entrollm},
+  project={https://arnabsanyal.com/icassp2026/entrollm.html},
+  venue_short={ICASSP 2026},
+  themes={edge},
+  news={2026-05-04},
+  news_text={Arnab's paper <a href="https://arnabsanyal.com/icassp2026/entrollm.html">EntroLLM: Entropy Encoded Weight Compression for Efficient Large Language Model Inference on Edge Devices</a> was presented at ICASSP 2026! <a href="https://gist.science/paper/2505.02380">Read the blog post</a> and <a href="https://github.com/arnabsanyal/entrollm">explore the code</a>.}
+}
+
 @inproceedings{bhatt2025uncap,
   title={{UNCAP}: Uncertainty-Guided Neurosymbolic Planning Using Natural Language Communication for Cooperative Autonomous Vehicles},
   author={Neel P. Bhatt and Po-han Li and Kushagra Gupta and Rohan Siva and Daniel Milan and Alexander Todd Hogue and Sandeep P. Chinchali and David Fridovich-Keil and Zhangyang Wang and Ufuk Topcu},
 
@@ -10,7 +10,12 @@ website: https://arnabsanyal.com/
 scholar: https://scholar.google.com/citations?user=D9ebkwoAAAAJ
 github: https://github.com/arnabsanyal
 linkedin: https://www.linkedin.com/in/arnabsanyal17/
+fellowships:
+  - name: Industry funded PhD
 industry:
+  - company: Amazon Lab126
+    role: SysDE ML Compiler Engineer I
+    years: "2020–2022"
   - company: Qualcomm
     role: Senior Machine Learning Engineer
     years: "2023–2024"
@@ -23,19 +28,20 @@ industry:
 ---
 
 - _PhD Student, Electrical and Computer Engineering, UT Austin_<br>
+- _Senior ML Engineer II, Cruise LLC, General Motors_<br>
 
 <svg class="icon" aria-hidden="true"><use href="#i-mail"/></svg> `sanyal@utexas.edu`<br>
 <svg class="icon" aria-hidden="true"><use href="#i-pdf"/></svg> [Resume (pdf)](https://drive.google.com/open?id=1qmr7uleFa0IoCncOq6VHd0Pkg9Zh6q0o)<br>
-<svg class="icon" aria-hidden="true"><use href="#i-external"/></svg> [Personal Website](https://arnabsanyal.github.io/)
+<svg class="icon" aria-hidden="true"><use href="#i-external"/></svg> [Personal Website](https://arnabsanyal.com/)
 
 **Office**<br>
 EER 4.836, 2501 Speedway,<br>
 Austin, TX 78712
 
-<span class="sc">**Arnab Sanyal**</span> is a Ph.D. student in ECE since Fall 2023. He holds a M.S. in ECE and a M.S. in CSCI from University of Southern California. Prior to this, he completed his integrated B.Tech. and M.Tech. in Electrical Engineering from Indian Institute of Technology, Kharagpur. 
+<span class="sc">**Arnab Sanyal**</span> is a Ph.D. student in ECE since Fall 2023. He holds an M.S. in Electrical Engineering and an M.S. in Computer Science from the University of Southern California. Prior to this, he completed his dual-degree B.Tech. and M.Tech. in Electrical Engineering (Instrumentation & Signal Processing) from the Indian Institute of Technology, Kharagpur.
 
 
-Arnab is interested in designing energy-efficient, robust, machine learning inference algorithms for generative AI applications running on edge devices. His research interest lies in quantization, computer arithmatic, robust system design for efficiency and algorithm modification for AI accelerators. He has worked in industry for some time now while pursuing his education and is currently Member of Technical Staff at Advanced Micro Devices, Inc. 
+Arnab is interested in designing energy-efficient, robust machine learning algorithms for generative AI edge applications, with the goal of making generative AI cheap enough to run where it is needed: on phones, cars, image sensors and microcontrollers. His research interest lies in quantization, computer arithmetic, robust system design for efficiency and algorithm modification for AI accelerators. He has worked in industry while pursuing his education, at Amazon Lab126, Qualcomm AI Research and AMD, and is currently a Senior ML Engineer II at Cruise LLC, General Motors, where he builds ML compilers that optimize machine learning models for General Motors' advanced driver assistance and full autonomous vehicle systems.
 
 
-Outside of research, he likes to read novels, drive/ride cars and motorcycles and loves travelling. He loves animals and has a pet cat Oliver.
+Outside of research, he likes to read novels, drive/ride cars and motorcycles and loves travelling. He loves animals and has a pet cat, Oliver.