{"id":29292,"date":"2024-08-16T14:02:41","date_gmt":"2024-08-16T18:02:41","guid":{"rendered":"http:\/\/www.bu.edu\/csmet\/?post_type=profile&#038;p=29292"},"modified":"2026-04-06T12:58:50","modified_gmt":"2026-04-06T16:58:50","slug":"avinash-mohan","status":"publish","type":"profile","link":"https:\/\/www.bu.edu\/csmet\/profile\/avinash-mohan\/","title":{"rendered":"Avinash Mohan"},"content":{"rendered":"<p>Dr. Mohan\u2019s research focuses on statistical learning, including reinforcement learning, online learning (multi-armed bandit problems), game theory, and convex optimization. He also works on computer networks and communication, including queueing theory, stochastic processes, resource allocation and network control. He was a postdoctoral fellow at Boston University (where he was awarded the Distinguished Educator-Scholar Fellowship for 2022\u20132023), the University of Michigan, and the Technion\u2013Israel Institute of Technology, where he was awarded the PBC Fellowship. He is recipient of the Best Presentation Award (MAC layer track) at the IEEE International Conference on Computer Communications (Infocom) 2018.<\/p>\n<div class=\"bu_collapsible_container \" aria-live=\"polite\" data-customize-animation=\"false\"><h3 class=\"bu_collapsible\" aria-expanded=\"false\"tabindex=\"0\" role=\"button\">Research Interests<\/h3><div class=\"bu_collapsible_section\" style=\"display: none;\"><\/p>\n<ul>\n<li>Reinforcement Learning<\/li>\n<li>Statistical Learning Theory<\/li>\n<li>Stochastic Control<\/li>\n<li>Stochastic Games (Competitive Markov Decision Processes)<\/li>\n<li>Deregulated Market Design<\/li>\n<li>Communication Network Optimization<\/li>\n<\/ul>\n<p><\/div>\n<\/div>\n\n<div class=\"bu_collapsible_container \" aria-live=\"polite\" data-customize-animation=\"false\"><h3 class=\"bu_collapsible\" aria-expanded=\"false\"tabindex=\"0\" role=\"button\">Scholarly Works<\/h3><div class=\"bu_collapsible_section\" style=\"display: none;\"><\/p>\n<h5><strong>Conference Papers<\/strong><\/h5>\n<p><span>Zaki, M., Mohan, A., Gopalan, A., and Mannor, S. &#8220;Actor Critic Based Improper Reinforcement Learning.&#8221;<em> Proceedings of the 39th International Conference on Machine Learning (ICML)<\/em>, in <em>Proceedings of Machine Learning Research<\/em> vol. 162\u00a0(July 17\u201323, 2022): <\/span>25867\u201325919<span>. https:\/\/proceedings.mlr.press\/v162\/zaki22a\/zaki22a.pdf<\/span><\/p>\n<p><span>Zaki, M., Mohan, A., and Gopalan, A. &#8220;Explicit Best Arm Identification in Linear Bandits Using No-Regret Learners.\u201d International Conference on Artificial Intelligence (IJCAI-ECAI), 2022.\u00a0https:\/\/arxiv.org\/pdf\/2006.07562<\/span><\/p>\n<p><span>Zaki, M., Mohan, A., Gopalan, A., and Mannor, S. &#8220;Actor Critic Based Improper Reinforcement Learning.&#8221;\u00a0<\/span><span>The Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM),<\/span><span>\u00a02022. <\/span><\/p>\n<p><span>Zaki, M., Mohan, A. and Gopalan, A., and Mannor, S. &#8220;Better than the Best: Gradient-based Improper Reinforcement Learning for Network Scheduling<em>.<\/em>&#8221; Reinforcement Learning in Networks and Queues Workshop,\u00a0ACM\u00a0SIGMETRICS, 2021. https:\/\/arxiv.org\/pdf\/2105.00210<\/span><\/p>\n<p><span>Mohan, A., Mannor, S., and Kizilkale, A. C. &#8220;On the Volatility of Optimal Control Policies of a Class of Linear Quadratic Regulators<em>.<\/em>&#8221; The 2021\u00a0American Control Conference\u00a0(ACC), 2021. https:\/\/arxiv.org\/pdf\/2002.06808<\/span><\/p>\n<p><span>Vatsa, S., Mohan, A., and Kumar, A. &#8220;Implementing QZMAC (a Decentralized Delay Optimal MAC) over 6TiSCH under the Contiki OS in an IEEE 802.15.4 Network.&#8221;\u00a0The Demos and Exhibits workshop at the International Conference on COMmunication Systems &amp; NETworkS (COMSNETS), 2021. Runner Up, Best Research Demo Award. https:\/\/arxiv.org\/pdf\/2012.02955<\/span><\/p>\n<p><span>Zaki, M., Mohan, A., and Gopalan, A. &#8220;Employing No Regret Learners for Pure Exploration in Linear Bandits.&#8221; Optimization for Machine Learning Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS), 2020. Selected for\u00a0Spotlight\u00a0presentation.<\/span><\/p>\n<p><span>Zaki, M., Mohan, A., and Gopalan, A. &#8220;Towards Optimal and Efficient Best Arm Identification in Linear Bandits.&#8221; CausalML Workshop at the 33rd Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2019.<\/span><\/p>\n<p><span>Mohan, A., Gopalan, A., and Kumar, A. &#8220;Reduced-State, Optimal Medium Access Control for Wireless Data Collection Networks.&#8221; IEEE International Conference on Computer Communications (INFOCOM), 2018. Best Presentation Award.<\/span><\/p>\n<p><span>Mohan, A., Chattopadhyay, A., and Kumar, A. &#8220;Hybrid MAC Protocols for Low-delay Scheduling.&#8221; IEEE International Conference on Mobile Ad hoc and Sensor Systems (IEE MASS), 2016. IEEE CompSoc Student Travel Award.<\/span><\/p>\n<p><span>Mohan, A., and Hari, K. V. S. &#8220;Low complexity adaptation for channel shortening equalizers.&#8221; IEEE 54th International Midwest Symposium on Circuits and Systems (MWSCAS), 2011.<\/span><\/p>\n<h5><strong>Journal Papers<\/strong><\/h5>\n<p>Mohan, A., Chattopadhyay, A., Vatsa, S.V. and Kumar, A., 2024. A low-delay mac for iot applications: Decentralized optimal scheduling of queues without explicit state information sharing.\u00a0<em>IEEE Transactions on Control of Network Systems<\/em>. <a href=\"https:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?arnumber=10584286\">https:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?arnumber=10584286<\/a><\/p>\n<p><span>Mohan, A., Gopalan, A., and Kumar, A. &#8220;Reduced-State, Optimal Scheduling for Decentralized Medium Access Control of a Class of Wireless Networks.&#8221;\u00a0<em>IEEE\/ACM Transactions on Networking<\/em> 28, no. 3 (2020): 1017\u20131032. <\/span><a href=\"https:\/\/ieeexplore.ieee.org\/abstract\/document\/9078869\">https:\/\/ieeexplore.ieee.org\/abstract\/document\/9078869<\/a><\/p>\n<p><span>Mohan, A., and Hari, K. V. S. &#8220;Low complexity adaptation for SISO channel shortening equalizers.&#8221; <em>AEU-International Journal of Electronics and Communications<\/em> 66, no. 8 (2012): 600\u2013604.<\/span> <a href=\"https:\/\/doi.org\/10.1016\/j.aeue.2012.03.011\">https:\/\/doi.org\/10.1016\/j.aeue.2012.03.011<\/a><\/p>\n<h5><strong>Preprints and Techreports<\/strong><\/h5>\n<p>Fayza, C. Demirkiran, C. Chen, C. Liu, A. Mohan, H. Errahmouni, S. Yun, M. Imani, D. Zhang, D. Bunandar, and A. Joshi. \u201cTowards Efficient Hyperdimensional Computing Using Photonics\u201d (2023). https:\/\/arxiv.org\/pdf\/2311.17801<\/p>\n<p>Zaki, M., Mohan, A., Gopalan, A., and Mannor, S. &#8220;Actor-Critic based Improper Reinforcement Learning&#8221; (2022).<\/p>\n<p>Zaki, M., Mohan, A., and Gopalan, A. &#8220;Improved Pure Exploration in Linear Bandits with No-Regret Learning&#8221; (2021). https:\/\/doi.org\/10.13140\/RG.2.2.35458.20162<\/p>\n<p>Mohan, A., Vatsa, S., Kumar, A.,\u00a0and Chattopadhyay, A. &#8220;Decentralized, Hybrid MAC Design with Reduced State Information Exchange for Low-Delay IoT Applications&#8221; (2021). https:\/\/arxiv.org\/pdf\/2105.11213<\/p>\n<p>Zaki, M., Mohan, A., Gopalan, A., and Mannor, S. &#8220;Improper Learning with Gradient-based Policy Optimization&#8221; (2021). https:\/\/arxiv.org\/abs\/2102.08201<\/p>\n<p>Mohan, A., Mannor, S., and Kizilkale, A. C. &#8220;On the Volatility of Optimal Control Policies and the Capacity of a Class of Linear Quadratic Regulators&#8221; (2020). https:\/\/arxiv.org\/pdf\/2002.06808<\/p>\n<p>Zaki, M., Mohan, A., and Gopalan, A. &#8220;Explicit Best Arm Identification in Linear Bandits Using No-Regret Learners&#8221; (2020). https:\/\/arxiv.org\/pdf\/2006.07562<\/p>\n<p>Mohan, A., Gopalan, A., and Kumar, A. &#8220;Throughput Optimal Decentralized Scheduling with Single-bit State Feedback for a Class of Queueing Systems&#8221; (2020). https:\/\/arxiv.org\/pdf\/2002.08141<\/p>\n<p>Zaki, M., Mohan, A., and Gopalan, A. &#8220;Towards Optimal and Efficient Best Arm Identification in Linear Bandits&#8221; (2019). https:\/\/arxiv.org\/abs\/1911.01695<\/p>\n<p><\/div>\n<\/div>\n\n","protected":false},"author":22903,"template":"","_links":{"self":[{"href":"https:\/\/www.bu.edu\/csmet\/wp-json\/wp\/v2\/profile\/29292"}],"collection":[{"href":"https:\/\/www.bu.edu\/csmet\/wp-json\/wp\/v2\/profile"}],"about":[{"href":"https:\/\/www.bu.edu\/csmet\/wp-json\/wp\/v2\/types\/profile"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/csmet\/wp-json\/wp\/v2\/users\/22903"}],"version-history":[{"count":13,"href":"https:\/\/www.bu.edu\/csmet\/wp-json\/wp\/v2\/profile\/29292\/revisions"}],"predecessor-version":[{"id":31418,"href":"https:\/\/www.bu.edu\/csmet\/wp-json\/wp\/v2\/profile\/29292\/revisions\/31418"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/csmet\/wp-json\/wp\/v2\/media?parent=29292"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}