BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Asia/Kolkata BEGIN:STANDARD DTSTART:19451014T230000 TZOFFSETFROM:+0630 TZOFFSETTO:+0530 TZNAME:IST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20250429T172605Z UID:BAF9C0F6-0E41-4CDF-950A-DAD000E6F7DF DTSTART;TZID=Asia/Kolkata:20250422T110000 DTEND;TZID=Asia/Kolkata:20250422T130000 DESCRIPTION:In celebration of PES Day 2025\, the BMSCE IEEE PES & Sensors C ouncil\, in collaboration with the BMSCE\nACM Student Chapter\, hosted ALG OTHON — a high-impact\, fast-paced coding competition with a mission:\nc ode for a cleaner\, greener tomorrow.\nCentered around the theme of Green Energy and Sustainability\, ALGOTHON challenged participants to solve\nalg orithmic problems that simulated real-world issues tied to renewable energ y\, efficient resource utilization\,\nand sustainability-focused computing .\n\nWhat Went Down?\nALGOTHON featured three escalating rounds of competi tive coding\, designed to test both technical\nexpertise and strategic thi nking.\nAt the start of each round\, teams picked coding problem statement s at random from a pool of challenges\ninspired by green tech applications \, such as smart grid management\, power optimization\, and eco-routing\ns ystems. These problems were built to reflect scenarios where computational efficiency directly impacts\nsustainability outcomes.\nParticipants then had to:\n- Analyze the problem\n- Strategize their approach\n- Implement a nd submit optimized code\, with a specific emphasis on minimizing time com plexity\nAs rounds progressed\, the difficulty level increased\, moving fr om foundational logic problems to advanced\nalgorithm design. Each submiss ion was evaluated based on correctness\, efficiency\, and the\noptimal use of algorithms — simulating real-world constraints faced by engineers in the clean tech\nindustry.\nTheme Focus: Green Energy in Code\nSustainabil ity isn’t just about hardware or policy — it’s also about how we cod e.\nThrough this theme\, participants were encouraged to think critically about:\n- Energy-efficient algorithms\n\nThe event demonstrated how even d igital solutions contribute to environmental goals when\ntime and space co mplexity are treated as crucial resources.\nImpact\nALGOTHON was more than a competition — it was a meaningful learning experience rooted\nin purp ose-driven coding.\n\nKey takeaways for participants included:\n- Enhanced understanding of algorithmic optimization\n- Practice in coding under rea listic constraints and pressure\n- Exposure to green energy applications i n computing\n- Strengthened teamwork\, debugging\, and critical thinking s kills\nBy engaging with green energy-themed challenges\, participants walk ed away with a new\nperspective: smart code leads to a smarter\, more sust ainable world.\nOrganizing Team (POCs):-\nShashwat Goyal – Department of Computer Science & Engineering\nSrikanth Mandayam Annadoray – Departmen t of Artificial Intelligence & Machine Learning\n\nBMS College of Engineer ing\, Basavangudi\, Bengaluru\, Karnataka\, India\, 560011 LOCATION:BMS College of Engineering\, Basavangudi\, Bengaluru\, Karnataka\, India\, 560011 ORGANIZER:ieee.pes@bmsce.ac.in SEQUENCE:11 SUMMARY:BMSCE IEEE PES & SC- Algothon URL;VALUE=URI:https://events.vtools.ieee.org/m/480624 X-ALT-DESC:Description: <br /><p>In celebration of PES Day 2025\, the BMSCE IEEE PES &amp\; Sensors Council\, in collaboration with the BMSCE<br>ACM Student Chapter\, hosted ALGOTHON &mdash\; a high-impact\, fast-paced codi ng competition with a mission:<br>code for a cleaner\, greener tomorrow.<b r>Centered around the theme of Green Energy and Sustainability\, ALGOTHON challenged participants to solve<br>algorithmic problems that simulated re al-world issues tied to renewable energy\, efficient resource utilization\ ,<br>and sustainability-focused computing.</p>\n<p><br>What Went Down?<br> ALGOTHON featured three escalating rounds of competitive coding\, designed to test both technical<br>expertise and strategic thinking.<br>At the sta rt of each round\, teams picked coding problem statements at random from a pool of challenges<br>inspired by green tech applications\, such as smart grid management\, power optimization\, and eco-routing<br>systems. These problems were built to reflect scenarios where computational efficiency di rectly impacts<br>sustainability outcomes.<br>Participants then had to:<br >- Analyze the problem<br>- Strategize their approach<br>- Implement and s ubmit optimized code\, with a specific emphasis on minimizing time complex ity<br>As rounds progressed\, the difficulty level increased\, moving from foundational logic problems to advanced<br>algorithm design. Each submiss ion was evaluated based on correctness\, efficiency\, and the<br>optimal u se of algorithms &mdash\; simulating real-world constraints faced by engin eers in the clean tech<br>industry.<br>Theme Focus: Green Energy in Code<b r>Sustainability isn&rsquo\;t just about hardware or policy &mdash\; it&rs quo\;s also about how we code.<br>Through this theme\, participants were e ncouraged to think critically about:<br>- Energy-efficient algorithms</p>\ n<p>The event demonstrated how even digital solutions contribute to enviro nmental goals when<br>time and space complexity are treated as crucial res ources.<br>Impact<br>ALGOTHON was more than a competition &mdash\; it was a meaningful learning experience rooted<br>in purpose-driven coding.</p>\n <p><br>Key takeaways for participants included:<br>- Enhanced understandin g of algorithmic optimization<br>- Practice in coding under realistic cons traints and pressure<br>- Exposure to green energy applications in computi ng<br>- Strengthened teamwork\, debugging\, and critical thinking skills<b r>By engaging with green energy-themed challenges\, participants walked aw ay with a new<br>perspective: smart code leads to a smarter\, more sustain able world.<br>Organizing Team (POCs):-<br>Shashwat Goyal &ndash\; Departm ent of Computer Science &amp\; Engineering<br>Srikanth Mandayam Annadoray &ndash\; Department of Artificial Intelligence &amp\; Machine Learning</p> \n<p><strong id="docs-internal-guid-d3e5dbf5-7fff-96a5-0cee-c2b474b8497b"> <img src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXc6Hoh_WjRP8Ta9M bv96DovMrvqZBlKcdc5Q_BcPv648kHB1cZ6UHyCCcoX7ivTS6ry4Sn-E2Y1b1q5Zot05fusTif RK-vq6RldZMoGQe4xPH3DiZXecgnMYIQsZ3_yw8yRX3M_Qw?key=ut9O_OHORVFEf8351qt-p2 TY" width="306" height="391"></strong><strong id="docs-internal-guid-6026c b88-7fff-e5a0-1c9d-4ce3a2ddbfe1"><img src="https://lh7-rt.googleuserconten t.com/docsz/AD_4nXf4rvRE8nCPZKkvW5oUxCdY7mAVzMLq39N5n-U8d3tOXoTsA0k-nh2BLG KzfWIIdeUEKklyaBTp_osY18ppreGIPKrm1TwbflCWRzEYKvNCqzpmQteR__B_F1RA6JVyRfNN MsF8-w?key=ut9O_OHORVFEf8351qt-p2TY" width="228" height="405"></strong></p >\n<p><strong id="docs-internal-guid-cb432172-7fff-09ee-c82a-b94ae9a6716e" ><img src="https://lh7-rt.googleusercontent.com/docsz/AD_4nXd1pNLADHDAWXne 8w51ZKZR0uiSqIMXdFlhwVHOmx80qfJ61W21ETrbeGiYlB4U83LK115LbcO9GtLjuMGs3G6rwz 1xgl468AdmMy3DNrLW9s_rMG2kMgqhrdiDqaLrRQCM_SYqdg?key=ut9O_OHORVFEf8351qt-p 2TY" width="291" height="517"></strong><strong id="docs-internal-guid-9442 5268-7fff-31ff-1744-2747663d2838"><img src="https://lh7-rt.googleuserconte nt.com/docsz/AD_4nXdR6d6Gi2iLNF5ckhkIibo31ZbovYPiiFXF1XN8erRzWMHxsktkGxS1G SW0AlrCom9V_avzVCY7yVDqTHqUmAFTXx054Jw-yLGLA9gU9tv4f5R5dSvbFfGPSLfV9nfN0fd KNiQ1xg?key=ut9O_OHORVFEf8351qt-p2TY" width="296" height="527"></strong></ p> END:VEVENT END:VCALENDAR