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<p class="MsoNormal"><span style="font-family:"Arial",sans-serif"><img width="600" height="171" style="width:6.25in;height:1.7812in" id="_x0000_i1026" src="https://www.egr.uh.edu/sites/www.egr.uh.edu/files/enews/2022/images/dissertation1.png" alt="Dissertation Defense Announcement at the Cullen College of Engineering"><o:p></o:p></span></p>
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<b><span style="font-size:18.0pt;color:#C8102E">Towards Mobile-Device Friendly Federated Learning: Efficiency, Privacy and Personalization</span></b><span style="font-size:18.0pt;color:#C8102E"><o:p></o:p></span></p>
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<strong><span style="font-size:13.5pt;font-family:"Arial",sans-serif;color:#222222">Pavana Prakash</span></strong><span style="font-size:13.5pt;color:black"><o:p></o:p></span></p>
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<span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:#222222">August 1, 2023</span><span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:black">;
</span><span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:#222222">08:30 AM - 10:30 AM (CST)</span><span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:black"><br>
</span><span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:#222222">Location: Zoom Meeting</span><span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:black"><br>
Zoom: </span><u><span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:#222222"><a href="https://urldefense.com/v3/__https:/uh-edu-cougarnet.zoom.us/j/9167221115__;!!LkSTlj0I!AYHlDOrfeq1r2lXCGKYp75YmD6rrKcmFd29Xzwtyxxwme4lK4dR4OZ0MtER5z6igMyUIrOakxS8f7g9HNYf_TA$" target="_blank"><span style="color:#CC0000">https://uh-edu-cougarnet.zoom.us/j/9167221115</span></a></span></u><span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:black"><o:p></o:p></span></p>
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<span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:#222222">Meeting ID: 916 722 1115</span><span style="font-size:10.5pt;font-family:"Arial",sans-serif;color:black"><o:p></o:p></span></p>
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<strong><span style="font-size:10.5pt;font-family:"Arial",sans-serif">Committee Chair:</span></strong><o:p></o:p></p>
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<span style="font-size:10.5pt;font-family:"Arial",sans-serif">Miao Pan, Ph.D.<o:p></o:p></span></p>
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<strong><span style="font-size:10.5pt;font-family:"Arial",sans-serif">Committee Members:</span></strong><span style="font-size:10.5pt;font-family:"Arial",sans-serif"><br>
Zhu Han, Ph.D. | Hien Van Nguyen, Ph.D. | Xin Fu, Ph.D. | Yuanxiong Guo, Ph.D.<o:p></o:p></span></p>
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<strong><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#C8102E">Abstract</span></strong><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#C8102E"><o:p></o:p></span></p>
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<span style="font-size:10.5pt;font-family:"Arial",sans-serif">The integration of deep learning capabilities and advanced mobile processors has significantly boosted the popularity of cutting-edge mobile devices such as smartphones. Moreover, the widespread
use of artificial intelligence and mobile internet has led to rapid growth in innovative applications such as smart healthcare, next word prediction, augmented/virtual reality and so on, targeted at mobile devices. However, deep learning applications generate
massive volumes of data, resulting in substantial burden on communication links and compute, as well as immense privacy implications when uploading and storing such data on servers. Edge Computing, a promising technology, can partly address these challenges
by reducing latency through enabling computation near the data source. Furthermore, federated learning (FL), a fast-growing distributed learning paradigm, can aid in instituting such pervasive applications over mobile devices at the edge. Despite its potential
benefits, FL involving large models faces challenges, including computation and communication expenses, system and data heterogeneity, and privacy concerns.<o:p></o:p></span></p>
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<span style="font-size:10.5pt;font-family:"Arial",sans-serif">The objectives of this dissertation are hence to address these key challenges by developing efficient mobile device-friendly FL designs through theoretical, simulation, and experimental studies.
The dissertation proposes equipping FL with the necessary tools from the perception of efficiency, privacy, and personalization. To this end, model compression and time/energy-conserving techniques are integrated with FL to enhance efficiency, and privacy
requirements are met through novel compressor incorporation and its additional properties. Likewise, adaptive training techniques are developed to balance model generalization and personalization. Overall, this dissertation contributes towards enabling low-end
mobile devices to effectively participate in the FL process.<o:p></o:p></span></p>
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<p class="MsoNormal"><span style="font-family:"Arial",sans-serif"><img border="0" width="600" height="82" style="width:6.25in;height:.8541in" id="_x0000_i1025" src="https://www.egr.uh.edu/sites/www.egr.uh.edu/files/enews/2022/images/dissertation2.png" alt="Engineered For What's Next"><o:p></o:p></span></p>
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<p class="MsoNormal">On Mon, Jul 24, 2023 at 11:53 AM Hutchinson, Inez A <<a href="mailto:iajackso@central.uh.edu" target="_blank">iajackso@central.uh.edu</a>> wrote:<o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:12.0pt;color:black">Hi there, </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:12.0pt;color:black"> </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;background:white">
<span style="font-size:12.0pt;color:black">Do you mind formatting the announcement like the attached file. <span style="background:white"> To use this layout, please follow these steps:</span></span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;background:white">
<span style="font-size:12.0pt;color:black"> </span><o:p></o:p></p>
<ul type="disc">
<li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo1;background:white">
<span style="font-size:12.0pt">Open the attached document in your preferred internet browser</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo1;background:white">
<span style="font-size:12.0pt">Select all and copy</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo1;background:white">
<span style="font-size:12.0pt">Open a new email message and paste the content directly into the email body</span><o:p></o:p></li><li class="MsoNormal" style="color:black;mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;mso-list:l0 level1 lfo1;background:white">
<span style="font-size:12.0pt">update your text in the email window</span><o:p></o:p></li></ul>
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<span style="font-size:12.0pt;color:black"> </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto;background:white">
<span style="font-size:12.0pt;color:black;background:white">Once these steps are complete, please resend to me for distribution. Let me know if you have any issues with the file attached. </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:12.0pt;color:black"> </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:12.0pt"> </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:12.0pt"> </span><o:p></o:p></p>
<div>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:13.0pt;color:black">Best Regards,</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:13.0pt;color:black"> </span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:13.0pt;color:black">Inez Hutchinson</span></b><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:13.0pt;color:black">Executive Director of Communications</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:13.0pt;color:black">Cullen College of Engineering</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:13.0pt;color:black">Engineering Building 2, Suite E311</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:13.0pt;color:black">University of Houston</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:13.0pt;color:black">Houston, TX 77204-4007</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:13.0pt;color:black"><a href="tel:(713)%20743-7593" target="_blank"><span style="color:#0563C1">(713) 743-7593</span></a> –
<a href="mailto:iajackso@central.uh.edu" target="_blank"><span style="color:#0563C1">iajackso@central.uh.edu</span></a>
</span><o:p></o:p></p>
<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><span style="font-size:12.0pt;color:black"> </span><o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"><b><span style="font-size:12.0pt;color:black">From:
</span></b><span style="font-size:12.0pt;color:black">Pavana Prakash <<a href="mailto:pavanaprakash88@gmail.com" target="_blank">pavanaprakash88@gmail.com</a>><br>
<b>Date: </b>Monday, July 24, 2023 at 11:51 AM<br>
<b>To: </b>"Hutchinson, Inez A" <<a href="mailto:iajackso@Central.UH.EDU" target="_blank">iajackso@Central.UH.EDU</a>>, "Hutchinson, Inez A" <<a href="mailto:iajackso@Central.UH.EDU" target="_blank">iajackso@Central.UH.EDU</a>><br>
<b>Cc: </b>"King, Kelly N" <<a href="mailto:knking@Central.UH.EDU" target="_blank">knking@Central.UH.EDU</a>><br>
<b>Subject: </b>Dissertation Announcement - Pavana Prakash, Electrical Engineering</span><o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"> <o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">Dear Inez,<o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"> <o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">Please find my dissertation announcement attached with this email. <o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"> <o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">My details are as follows,<o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">Name: Pavana Prakash<o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">PSID: 1679936<o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">Advisor: Dr. Miao Pan<o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"> <o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">Thank you very much for your time and consideration.<o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"> <o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">Also, please find the email message of the same below,<o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto"> <o:p></o:p></p>
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<b><span style="font-size:18.0pt;font-family:"Arial",sans-serif;color:#C8102E">Towards Mobile-Device Friendly Federated Learning: Efficiency, Privacy and Personalization</span></b><o:p></o:p></p>
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<strong><span style="font-size:13.5pt;font-family:"Arial",sans-serif">Pavana Prakash</span></strong><o:p></o:p></p>
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<span style="font-size:10.5pt;font-family:"Arial",sans-serif">August 1, 2023; 08:30 AM - 10:30 AM (CST)<br>
Location: Zoom Meeting<br>
Zoom: <u><span style="color:#C8102E"><a href="https://urldefense.com/v3/__https:/uh-edu-cougarnet.zoom.us/j/9167221115__;!!LkSTlj0I!AYHlDOrfeq1r2lXCGKYp75YmD6rrKcmFd29Xzwtyxxwme4lK4dR4OZ0MtER5z6igMyUIrOakxS8f7g9HNYf_TA$" target="_blank">https://uh-edu-cougarnet.zoom.us/j/9167221115</a></span></u></span><o:p></o:p></p>
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<strong><span style="font-size:10.5pt;font-family:"Arial",sans-serif">Committee Chair:</span></strong><span style="font-size:10.5pt;font-family:"Arial",sans-serif"><br>
Miao Pan, Ph.D.</span><o:p></o:p></p>
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<strong><span style="font-size:10.5pt;font-family:"Arial",sans-serif">Committee Members:</span></strong><span style="font-size:10.5pt;font-family:"Arial",sans-serif"><br>
Zhu Han, Ph.D. | Hien Van Nguyen, Ph.D. | Xin Fu, Ph.D. | Yuanxiong Guo, Ph.D.</span><o:p></o:p></p>
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<p style="margin-bottom:11.25pt;line-height:16.5pt"><strong><span style="font-size:12.0pt;font-family:"Arial",sans-serif;color:#C8102E">Abstract</span></strong><o:p></o:p></p>
<p style="margin-bottom:11.25pt;line-height:16.5pt"><span style="font-size:10.5pt;font-family:"Arial",sans-serif">The integration of deep learning capabilities and advanced mobile processors has significantly boosted the popularity of cutting-edge mobile devices
such as smartphones. Moreover, the widespread use of artificial intelligence and mobile internet has led to rapid growth in innovative applications such as smart healthcare, next word prediction, augmented/virtual reality and so on, targeted at mobile devices.
However, deep learning applications generate massive volumes of data, resulting in substantial burden on communication links and compute, as well as immense privacy implications when uploading and storing such data on servers. Edge Computing, a promising technology,
can partly address these challenges by reducing latency through enabling computation near the data source. Furthermore, federated learning (FL), a fast-growing distributed learning paradigm, can aid in instituting such pervasive applications over mobile devices
at the edge. Despite its potential benefits, FL involving large models faces challenges, including compute and communication expenses, system and data heterogeneity, and privacy concerns.</span><o:p></o:p></p>
<p style="margin-bottom:11.25pt;line-height:16.5pt"><span style="font-size:10.5pt;font-family:"Arial",sans-serif">The objectives of this dissertation are hence to address these key challenges by developing efficient mobile device-friendly FL designs through
theoretical, simulation, and experimental studies. The dissertation proposes equipping FL with the necessary tools from the perception of efficiency, privacy, and personalization. To this end, model compression and time/energy-conserving techniques are integrated
with FL to enhance efficiency, and privacy requirements are met through novel compressor incorporation and its additional properties. Likewise, adaptive training techniques are developed to balance model generalization and personalization. Overall, this dissertation
contributes towards enabling low-end mobile devices to effectively participate in the FL process.</span><o:p></o:p></p>
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<p class="MsoNormal" style="mso-margin-top-alt:auto;mso-margin-bottom-alt:auto">Regards,<br>
Pavana Prakash<o:p></o:p></p>
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<p class="MsoNormal">Regards,<br>
Pavana Prakash<o:p></o:p></p>
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